Re: [ccp4bb] AI papers in experimental macromolecular structure determination
Not sure someone already mentioned these (highly likely) https://www.nature.com/articles/s41586-019-1923-7 https://www.nature.com/articles/s41586-021-03819-2 https://science.sciencemag.org/content/early/2021/07/19/science.abj8754 On Tue, Aug 3, 2021 at 12:53 PM Thorn, Dr. Andrea < andrea.th...@uni-hamburg.de> wrote: > Dear colleagues, > > I have compiled a list of papers that cover the application of AI/machine > learning methods in single-crystal structure determination (mostly > macromolecular crystallography) and single-particle Cryo-EM. The draft list > is attached below. > > > > If I missed any papers, please let me know. I will send the final list > back here, for the benefit of all who are interested in the topic. > > > > Best wishes, > > > > > > Andrea. > > > > > > __ > > General: > > - Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B. & > Rosenberg, J. M. (2004). Acta Cryst D. 60, 1705–1716. > > - Morris, R. J. (2004). Acta Cryst D. 60, 2133–2143. > > > > Micrograph preparation: > > - (2020). Journal of Structural Biology. 210, 107498. > > > > Particle Picking: > > - Sanchez-Garcia, R., Segura, J., Maluenda, D., Carazo, J. M. & Sorzano, > C. O. S. (2018). IUCrJ. 5, 854–865. > > - Al-Azzawi, A., Ouadou, A., Tanner, J. J. & Cheng, J. (2019). BMC > Bioinformatics. 20, 1–26. > > - George, B., Assaiya, A., Roy, R. J., Kembhavi, A., Chauhan, R., Paul, > G., Kumar, J. & Philip, N. S. (2021). Commun Biol. 4, 1–12. > > - Lata, K. R., Penczek, P. & Frank, J. (1995). Ultramicroscopy. 58, > 381–391. > > - Nguyen, N. P., Ersoy, I., Gotberg, J., Bunyak, F. & White, T. A. (2021). > BMC Bioinformatics. 22, 1–28. > > - Wang, F., Gong, H., Liu, G., Li, M., Yan, C., Xia, T., Li, X. & Zeng, J. > (2016). Journal of Structural Biology. 195, 325–336. > > - Wong, H. C., Chen, J., Mouche, F., Rouiller, I. & Bern, M. (2004). > Journal of Structural Biology. 145, 157–167. > > > > Motion description in Cryo-EM: > > - Matsumoto, S., Ishida, S., Araki, M., Kato, T., Terayama, K. & Okuno, Y. > (2021). Nat Mach Intell. 3, 153–160. > > - Zhong, E. D., Bepler, T., Berger, B. & Davis, J. H. (2021). Nat Methods. > 18, 176–185. > > > > Local resolution: > > - Avramov, T. K., Vyenielo, D., Gomez-Blanco, J., Adinarayanan, S., > Vargas, J. & Si, D. (2019). Molecules. 24, 1181. > > - Ramírez-Aportela, E., Mota, J., Conesa, P., Carazo, J. M. & Sorzano, C. > O. S. (2019). IUCrJ. 6, 1054–1063. > > - (2021). QAEmap: A Novel Local Quality Assessment Method for Protein > Crystal Structures Using Machine Learning. > > > > Map post-processing: > > - Sanchez-Garcia, R., Gomez-Blanco, J., Cuervo, A., Carazo, J. M., > Sorzano, C. O. S. & Vargas, J. (2020). BioRxiv. 2020.06.12.148296. > > > > Secondary structure assignment in map: > > - Subramaniya, S. R. M. V., Terashi, G. & Kihara, D. (2019). Nat Methods. > 16, 911–917. > > - Li, R., Si, D., Zeng, T., Ji, S. & He, J. (2016). 2016 IEEE > International Conference on Bioinformatics and Biomedicine (BIBM), Vol. pp. > 41–46. > > - Si, D., Ji, S., Nasr, K. A. & He, J. (2012). Biopolymers. 97, 698–708. > > - He, J. & Huang, S.-Y. Brief Bioinform. > > - Lyu, Z., Wang, Z., Luo, F., Shuai, J. & Huang, Y. (2021). Frontiers in > Bioengineering and Biotechnology. 9,. > > - Mostosi, P., Schindelin, H., Kollmannsberger, P. & Thorn, A. (2020). > Angewandte Chemie International Edition. > > > > Automatic structure building: > > - Alnabati, E. & Kihara, D. (2020). Molecules. 25, 82. > > - Si, D., Moritz, S. A., Pfab, J., Hou, J., Cao, R., Wang, L., Wu, T. & > Cheng, J. (2020). Sci Rep. 10, 1–22. > > - Moritz, S. A., Pfab, J., Wu, T., Hou, J., Cheng, J., Cao, R., Wang, L. & > Si, D. (2019). > > - Chojnowski, G., Pereira, J. & Lamzin, V. S. (2019). Acta Cryst D. 75, > 753–763. > > > > Crystallization: > > - Liu, R., Freund, Y. & Spraggon, G. (2008). Acta Cryst D. 64, 1187–1195. > > - (2004). Methods. 34, 390–407. > > - Bruno, A. E., Charbonneau, P., Newman, J., Snell, E. H., So, D. R., > Vanhoucke, V., Watkins, C. J., Williams, S. & Wilson, J. (2018). PLOS ONE. > 13, e0198883. > > > > Crystal centering: > > - Ito, S., Ueno, G. & Yamamoto, M. (2019). J Synchrotron Rad. 26, > 1361–1366. > > - Crystal centering using deep learning in X-ray crystallography. > > - Elbasir, A., Moovarkumudalvan, B., Kunji, K., Kolatkar, P. R., Mall, R. > & Bensmail, H. (2019). Bioinformatics. 35, 2216–2225. > > > > Diffraction image analysis: > > - Czyzewski, A., Krawiec, F., Brzezinski, D., Porebski, P. J. & Minor, W. > (2021). Expert Systems with Applications. 174, 114740. > > > > Peak search in serial crystallography: > > Ke, T.-W., Brewster, A. S., Yu, S. X., Ushizima, D., Yang, C. & Sauter, N. > K. (2018). J Synchrotron Rad. 25, 655–670. > > > > Space group assignment from diffraction image (small molecules): > > Aguiar, J. A., Gong, M. L., Unocic, R. R., Tasdizen, T. & Miller, B. D. > (2019). Science Advances. 5, eaaw1949. > > > > Data quality assessment in MX: > > - Vollmar, M., Parkhurst, J. M., Jaques, D., Baslé,
Re: [ccp4bb] AI papers in experimental macromolecular structure determination
Hi folks This is probably a good time to mention that both Melanie and Andrea will be giving presentations at the IUCr in Prague in a couple of weeks or so in the Commission for Crystallographic Computing session chaired by Rita Giordano - MS-73 Machine learning in biological and structural sciences Friday 20th August 2021 10:20 - 12:45 Harry > On 4 Aug 2021, at 10:11, Vollmar, Melanie (DLSLtd,RAL,LSCI) > <64fe7ccc6b4d-dmarc-requ...@jiscmail.ac.uk> wrote: > > I don't have a list to add here, as my review on the topic awaits feedback on > the corrections (self-advertisement ) but perhaps we should consider that > machine learning and AI are two different beasts. Admittingly, I don't always > make a proper distinction either. > > Surely, many of us get their heads around machine learning, which usually > covers so called shallow learners that firmly sit in well-known concepts of > statistics. This type of machine learning doesn't require many resources and > is accessible to almost anyone with an average laptop. Plenty of software in > MX and EM use these tools and no-one every thinks about them. > > I think, Andrea, perhaps, was looking more into the direction of AI (based on > so many cryo-EM references listed , where this is a standard tool), which > requires a lot more understanding and thought as well as resources and would > appear to many as a magic black box. This type of machine learning has only > recently taken off due to huge leaps in hardware development, which many of > us can't afford to buy, unless it is provided through some shared resource. > Having said that, an average graphics card GPU is often a good start. And if > one isn't the book reading kind (usually due to lack of time), there are lots > of good blogs, videos and other online resources to get one into the basics. > > The papers that should clearly be added, are those for protein structure > prediction, as, in a way, they determine a structure, albeit with a different > kind of experiment: > > https://science.sciencemag.org/content/early/2021/07/19/science.abj8754 > https://www.nature.com/articles/s41586-021-03819-2 > > Cheers > > M > From: CCP4 bulletin board on behalf of Nave, Colin > (DLSLtd,RAL,LSCI) <000064fdcfc6624b-dmarc-requ...@jiscmail.ac.uk> > Sent: 04 August 2021 09:34 > To: CCP4BB@JISCMAIL.AC.UK > Subject: Re: [ccp4bb] AI papers in experimental macromolecular structure > determination > > Bernhard > What qualifies? Good question. > There are plenty of books on AI/machine learning but, as always, it is more > efficient/lazier to read reviews than the books themselves. I think the > London Review of Books allows limited access to its articles so most should > be able to read this > https://www.lrb.co.uk/the-paper/v43/n02/paul-taylor/insanely-complicated-hopelessly-inadequate?referrer=https%3A%2F%2Fwww.google.com%2F > It might be interesting (though perhaps not useful) to classify the examples > for macromolecular structure determination in to categories such as GOFAI > etc. However, this particular term is rather pejorative as it would mean > describing the developers as old fashioned! > > Colin > > > > > -Original Message- > From: CCP4 bulletin board On Behalf Of Bernhard Rupp > Sent: 03 August 2021 21:00 > To: CCP4BB@JISCMAIL.AC.UK > Subject: Re: [ccp4bb] AI papers in experimental macromolecular structure > determination > > Maybe we should get to the root of this - what qualifies as machine learning > and what not? > > Do nonparametric predictors such as KDE qualify? > > https://www.ruppweb.org/mattprob/default.html > > Happy toa dd to the confusion. > > -Original Message- > From: CCP4 bulletin board On Behalf Of Tim Gruene > Sent: Tuesday, August 3, 2021 11:59 > To: CCP4BB@JISCMAIL.AC.UK > Subject: Re: [ccp4bb] AI papers in experimental macromolecular structure > determination > > Hello Andrea, > > profile fitting, like it is done in mosflm > (https://doi.org/10.1107/S090744499900846X) or evalccd, or ... probably also > qualify as AI/machine learning. > > Best wishes, > Tim > > On Tue, 3 Aug 2021 11:43:06 + > "Thorn, Dr. Andrea" wrote: > > > Dear colleagues, > > I have compiled a list of papers that cover the application of > > AI/machine learning methods in single-crystal structure determination > > (mostly macromolecular crystallography) and single-particle Cryo-EM. > > The draft list is attached below. > > > > If I missed any papers, please let me know. I will send the final list > > back here, for the benefit of all who are interested in the topic. &
Re: [ccp4bb] AI papers in experimental macromolecular structure determination
I don't have a list to add here, as my review on the topic awaits feedback on the corrections (self-advertisement ) but perhaps we should consider that machine learning and AI are two different beasts. Admittingly, I don't always make a proper distinction either. Surely, many of us get their heads around machine learning, which usually covers so called shallow learners that firmly sit in well-known concepts of statistics. This type of machine learning doesn't require many resources and is accessible to almost anyone with an average laptop. Plenty of software in MX and EM use these tools and no-one every thinks about them. I think, Andrea, perhaps, was looking more into the direction of AI (based on so many cryo-EM references listed , where this is a standard tool), which requires a lot more understanding and thought as well as resources and would appear to many as a magic black box. This type of machine learning has only recently taken off due to huge leaps in hardware development, which many of us can't afford to buy, unless it is provided through some shared resource. Having said that, an average graphics card GPU is often a good start. And if one isn't the book reading kind (usually due to lack of time), there are lots of good blogs, videos and other online resources to get one into the basics. The papers that should clearly be added, are those for protein structure prediction, as, in a way, they determine a structure, albeit with a different kind of experiment: https://science.sciencemag.org/content/early/2021/07/19/science.abj8754 https://www.nature.com/articles/s41586-021-03819-2 Cheers M From: CCP4 bulletin board on behalf of Nave, Colin (DLSLtd,RAL,LSCI) <64fdcfc6624b-dmarc-requ...@jiscmail.ac.uk> Sent: 04 August 2021 09:34 To: CCP4BB@JISCMAIL.AC.UK Subject: Re: [ccp4bb] AI papers in experimental macromolecular structure determination Bernhard What qualifies? Good question. There are plenty of books on AI/machine learning but, as always, it is more efficient/lazier to read reviews than the books themselves. I think the London Review of Books allows limited access to its articles so most should be able to read this https://www.lrb.co.uk/the-paper/v43/n02/paul-taylor/insanely-complicated-hopelessly-inadequate?referrer=https%3A%2F%2Fwww.google.com%2F It might be interesting (though perhaps not useful) to classify the examples for macromolecular structure determination in to categories such as GOFAI etc. However, this particular term is rather pejorative as it would mean describing the developers as old fashioned! Colin -Original Message- From: CCP4 bulletin board On Behalf Of Bernhard Rupp Sent: 03 August 2021 21:00 To: CCP4BB@JISCMAIL.AC.UK Subject: Re: [ccp4bb] AI papers in experimental macromolecular structure determination Maybe we should get to the root of this - what qualifies as machine learning and what not? Do nonparametric predictors such as KDE qualify? https://www.ruppweb.org/mattprob/default.html Happy toa dd to the confusion. -Original Message- From: CCP4 bulletin board On Behalf Of Tim Gruene Sent: Tuesday, August 3, 2021 11:59 To: CCP4BB@JISCMAIL.AC.UK Subject: Re: [ccp4bb] AI papers in experimental macromolecular structure determination Hello Andrea, profile fitting, like it is done in mosflm (https://doi.org/10.1107/S090744499900846X) or evalccd, or ... probably also qualify as AI/machine learning. Best wishes, Tim On Tue, 3 Aug 2021 11:43:06 + "Thorn, Dr. Andrea" wrote: > Dear colleagues, > I have compiled a list of papers that cover the application of > AI/machine learning methods in single-crystal structure determination > (mostly macromolecular crystallography) and single-particle Cryo-EM. > The draft list is attached below. > > If I missed any papers, please let me know. I will send the final list > back here, for the benefit of all who are interested in the topic. > > Best wishes, > > > Andrea. > > > __ > General: > - Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B. & > Rosenberg, J. M. (2004). Acta Cryst D. 60, 1705–1716. > - Morris, R. J. (2004). Acta Cryst D. 60, 2133–2143. > > Micrograph preparation: > - (2020). Journal of Structural Biology. 210, 107498. > > Particle Picking: > - Sanchez-Garcia, R., Segura, J., Maluenda, D., Carazo, J. M. & > Sorzano, C. O. S. (2018). IUCrJ. 5, 854–865. > - Al-Azzawi, A., Ouadou, A., Tanner, J. J. & Cheng, J. (2019). BMC > Bioinformatics. 20, 1–26. > - George, B., Assaiya, A., Roy, R. J., Kembhavi, A., Chauhan, R., > Paul, G., Kumar, J. & Philip, N. S. (2021). Commun Biol. 4, 1–12. > - Lata, K. R., Penczek, P. & Frank, J. (1995). Ultramicroscopy. 58, > 381–391. > - Nguyen, N. P., Ersoy, I., Gotberg, J., Bunyak, F. & White, T. A. > (2021). BMC Bioinformatics. 22, 1–28
Re: [ccp4bb] AI papers in experimental macromolecular structure determination
Bernhard What qualifies? Good question. There are plenty of books on AI/machine learning but, as always, it is more efficient/lazier to read reviews than the books themselves. I think the London Review of Books allows limited access to its articles so most should be able to read this https://www.lrb.co.uk/the-paper/v43/n02/paul-taylor/insanely-complicated-hopelessly-inadequate?referrer=https%3A%2F%2Fwww.google.com%2F It might be interesting (though perhaps not useful) to classify the examples for macromolecular structure determination in to categories such as GOFAI etc. However, this particular term is rather pejorative as it would mean describing the developers as old fashioned! Colin -Original Message- From: CCP4 bulletin board On Behalf Of Bernhard Rupp Sent: 03 August 2021 21:00 To: CCP4BB@JISCMAIL.AC.UK Subject: Re: [ccp4bb] AI papers in experimental macromolecular structure determination Maybe we should get to the root of this - what qualifies as machine learning and what not? Do nonparametric predictors such as KDE qualify? https://www.ruppweb.org/mattprob/default.html Happy toa dd to the confusion. -Original Message- From: CCP4 bulletin board On Behalf Of Tim Gruene Sent: Tuesday, August 3, 2021 11:59 To: CCP4BB@JISCMAIL.AC.UK Subject: Re: [ccp4bb] AI papers in experimental macromolecular structure determination Hello Andrea, profile fitting, like it is done in mosflm (https://doi.org/10.1107/S090744499900846X) or evalccd, or ... probably also qualify as AI/machine learning. Best wishes, Tim On Tue, 3 Aug 2021 11:43:06 + "Thorn, Dr. Andrea" wrote: > Dear colleagues, > I have compiled a list of papers that cover the application of > AI/machine learning methods in single-crystal structure determination > (mostly macromolecular crystallography) and single-particle Cryo-EM. > The draft list is attached below. > > If I missed any papers, please let me know. I will send the final list > back here, for the benefit of all who are interested in the topic. > > Best wishes, > > > Andrea. > > > __ > General: > - Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B. & > Rosenberg, J. M. (2004). Acta Cryst D. 60, 1705–1716. > - Morris, R. J. (2004). Acta Cryst D. 60, 2133–2143. > > Micrograph preparation: > - (2020). Journal of Structural Biology. 210, 107498. > > Particle Picking: > - Sanchez-Garcia, R., Segura, J., Maluenda, D., Carazo, J. M. & > Sorzano, C. O. S. (2018). IUCrJ. 5, 854–865. > - Al-Azzawi, A., Ouadou, A., Tanner, J. J. & Cheng, J. (2019). BMC > Bioinformatics. 20, 1–26. > - George, B., Assaiya, A., Roy, R. J., Kembhavi, A., Chauhan, R., > Paul, G., Kumar, J. & Philip, N. S. (2021). Commun Biol. 4, 1–12. > - Lata, K. R., Penczek, P. & Frank, J. (1995). Ultramicroscopy. 58, > 381–391. > - Nguyen, N. P., Ersoy, I., Gotberg, J., Bunyak, F. & White, T. A. > (2021). BMC Bioinformatics. 22, 1–28. > - Wang, F., Gong, H., Liu, G., Li, M., Yan, C., Xia, T., Li, X. & > Zeng, J. (2016). Journal of Structural Biology. 195, 325–336. > - Wong, H. C., Chen, J., Mouche, F., Rouiller, I. & Bern, M. (2004). > Journal of Structural Biology. 145, 157–167. > > Motion description in Cryo-EM: > - Matsumoto, S., Ishida, S., Araki, M., Kato, T., Terayama, K. & > Okuno, Y. (2021). Nat Mach Intell. 3, 153–160. > - Zhong, E. D., Bepler, T., Berger, B. & Davis, J. H. (2021). Nat > Methods. 18, 176–185. > > Local resolution: > - Avramov, T. K., Vyenielo, D., Gomez-Blanco, J., Adinarayanan, S., > Vargas, J. & Si, D. (2019). Molecules. 24, 1181. > - Ramírez-Aportela, E., Mota, J., Conesa, P., Carazo, J. M. & Sorzano, > C. O. S. (2019). IUCrJ. 6, 1054–1063. > - (2021). QAEmap: A Novel Local Quality Assessment Method for Protein > Crystal Structures Using Machine Learning. > > Map post-processing: > - Sanchez-Garcia, R., Gomez-Blanco, J., Cuervo, A., Carazo, J. M., > Sorzano, C. O. S. & Vargas, J. (2020). BioRxiv. 2020.06.12.148296. > > Secondary structure assignment in map: > - Subramaniya, S. R. M. V., Terashi, G. & Kihara, D. (2019). Nat > Methods. 16, 911–917. > - Li, R., Si, D., Zeng, T., Ji, S. & He, J. (2016). 2016 IEEE > International Conference on Bioinformatics and Biomedicine (BIBM), > Vol. pp. 41–46. > - Si, D., Ji, S., Nasr, K. A. & He, J. (2012). Biopolymers. 97, > 698–708. > - He, J. & Huang, S.-Y. Brief Bioinform. > - Lyu, Z., Wang, Z., Luo, F., Shuai, J. & Huang, Y. (2021). Frontiers > in Bioengineering and Biotechnology. 9,. > - Mostosi, P., Schindelin, H., Kollmannsberger, P. & Thorn, A. > (2020). Angewandte Chemie International Edition. > > Automatic structure building: > - Alnabati, E. & Kihara, D. (2020)
Re: [ccp4bb] AI papers in experimental macromolecular structure determination
Dear Andrea, https://journals.iucr.org/s/issues/2000/06/00/hi2016/index.html Greetings, John Emeritus Professor John R Helliwell DSc > On 3 Aug 2021, at 12:53, Thorn, Dr. Andrea > wrote: > > > Dear colleagues, > I have compiled a list of papers that cover the application of AI/machine > learning methods in single-crystal structure determination (mostly > macromolecular crystallography) and single-particle Cryo-EM. The draft list > is attached below. > > If I missed any papers, please let me know. I will send the final list back > here, for the benefit of all who are interested in the topic. > > Best wishes, > > > Andrea. > > > __ > General: > - Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B. & Rosenberg, > J. M. (2004). Acta Cryst D. 60, 1705–1716. > - Morris, R. J. (2004). Acta Cryst D. 60, 2133–2143. > > Micrograph preparation: > - (2020). Journal of Structural Biology. 210, 107498. > > Particle Picking: > - Sanchez-Garcia, R., Segura, J., Maluenda, D., Carazo, J. M. & Sorzano, C. > O. S. (2018). IUCrJ. 5, 854–865. > - Al-Azzawi, A., Ouadou, A., Tanner, J. J. & Cheng, J. (2019). BMC > Bioinformatics. 20, 1–26. > - George, B., Assaiya, A., Roy, R. J., Kembhavi, A., Chauhan, R., Paul, G., > Kumar, J. & Philip, N. S. (2021). Commun Biol. 4, 1–12. > - Lata, K. R., Penczek, P. & Frank, J. (1995). Ultramicroscopy. 58, 381–391. > - Nguyen, N. P., Ersoy, I., Gotberg, J., Bunyak, F. & White, T. A. (2021). > BMC Bioinformatics. 22, 1–28. > - Wang, F., Gong, H., Liu, G., Li, M., Yan, C., Xia, T., Li, X. & Zeng, J. > (2016). Journal of Structural Biology. 195, 325–336. > - Wong, H. C., Chen, J., Mouche, F., Rouiller, I. & Bern, M. (2004). Journal > of Structural Biology. 145, 157–167. > > Motion description in Cryo-EM: > - Matsumoto, S., Ishida, S., Araki, M., Kato, T., Terayama, K. & Okuno, Y. > (2021). Nat Mach Intell. 3, 153–160. > - Zhong, E. D., Bepler, T., Berger, B. & Davis, J. H. (2021). Nat Methods. > 18, 176–185. > > Local resolution: > - Avramov, T. K., Vyenielo, D., Gomez-Blanco, J., Adinarayanan, S., Vargas, > J. & Si, D. (2019). Molecules. 24, 1181. > - Ramírez-Aportela, E., Mota, J., Conesa, P., Carazo, J. M. & Sorzano, C. O. > S. (2019). IUCrJ. 6, 1054–1063. > - (2021). QAEmap: A Novel Local Quality Assessment Method for Protein Crystal > Structures Using Machine Learning. > > Map post-processing: > - Sanchez-Garcia, R., Gomez-Blanco, J., Cuervo, A., Carazo, J. M., Sorzano, > C. O. S. & Vargas, J. (2020). BioRxiv. 2020.06.12.148296. > > Secondary structure assignment in map: > - Subramaniya, S. R. M. V., Terashi, G. & Kihara, D. (2019). Nat Methods. 16, > 911–917. > - Li, R., Si, D., Zeng, T., Ji, S. & He, J. (2016). 2016 IEEE International > Conference on Bioinformatics and Biomedicine (BIBM), Vol. pp. 41–46. > - Si, D., Ji, S., Nasr, K. A. & He, J. (2012). Biopolymers. 97, 698–708. > - He, J. & Huang, S.-Y. Brief Bioinform. > - Lyu, Z., Wang, Z., Luo, F., Shuai, J. & Huang, Y. (2021). Frontiers in > Bioengineering and Biotechnology. 9,. > - Mostosi, P., Schindelin, H., Kollmannsberger, P. & Thorn, A. (2020). > Angewandte Chemie International Edition. > > Automatic structure building: > - Alnabati, E. & Kihara, D. (2020). Molecules. 25, 82. > - Si, D., Moritz, S. A., Pfab, J., Hou, J., Cao, R., Wang, L., Wu, T. & > Cheng, J. (2020). Sci Rep. 10, 1–22. > - Moritz, S. A., Pfab, J., Wu, T., Hou, J., Cheng, J., Cao, R., Wang, L. & > Si, D. (2019). > - Chojnowski, G., Pereira, J. & Lamzin, V. S. (2019). Acta Cryst D. 75, > 753–763. > > Crystallization: > - Liu, R., Freund, Y. & Spraggon, G. (2008). Acta Cryst D. 64, 1187–1195. > - (2004). Methods. 34, 390–407. > - Bruno, A. E., Charbonneau, P., Newman, J., Snell, E. H., So, D. R., > Vanhoucke, V., Watkins, C. J., Williams, S. & Wilson, J. (2018). PLOS ONE. > 13, e0198883. > > Crystal centering: > - Ito, S., Ueno, G. & Yamamoto, M. (2019). J Synchrotron Rad. 26, 1361–1366. > - Crystal centering using deep learning in X-ray crystallography. > - Elbasir, A., Moovarkumudalvan, B., Kunji, K., Kolatkar, P. R., Mall, R. & > Bensmail, H. (2019). Bioinformatics. 35, 2216–2225. > > Diffraction image analysis: > - Czyzewski, A., Krawiec, F., Brzezinski, D., Porebski, P. J. & Minor, W. > (2021). Expert Systems with Applications. 174, 114740. > > Peak search in serial crystallography: > Ke, T.-W., Brewster, A. S., Yu, S. X., Ushizima, D., Yang, C. & Sauter, N. K. > (2018). J Synchrotron Rad. 25, 655–670. > > Space group assignment from diffraction image (small molecules): > Aguiar, J. A., Gong, M. L., Unocic, R. R., Tasdizen, T. & Miller, B. D. > (2019). Science Advances. 5, eaaw1949. > > Data quality assessment in MX: > - Vollmar, M., Parkhurst, J. M., Jaques, D., Baslé, A., Murshudov, G. N., > Waterman, D. G. & Evans, G. (2020). IUCrJ. 7, 342–354. > > Ligand recognition: > Kowiel, M., Brzezinski, D., Porebski, P. J., Shabalin, I. G., Jaskolski, M. & > Minor, W. (2019).
Re: [ccp4bb] AI papers in experimental macromolecular structure determination
Hi Andrea, Here is something interesting on the extraction of information on protein dynamics from cryo-EM data: https://doi.org/10.1038/s42256-020-00290-y Best, Tushar. On Tue, 3 Aug 2021 at 19:48, Shekhar Mande wrote: > In particle picking, you may wish to include the following: > > George, B., Assaiya, A., Roy, R.J. *et al.* CASSPER is a semantic > segmentation-based particle picking algorithm for single-particle > cryo-electron microscopy. *Commun Biol* 4, 200 (2021). > https://doi.org/10.1038/s42003-021-01721-1 > > On Tue, Aug 3, 2021 at 9:17 PM Guillaume Gaullier < > guillaume.gaull...@icm.uu.se> wrote: > >> Hello, >> >> In the particle picking section, you may want to include these two: >> >> Wagner T, Merino F, Stabrin M, Moriya T, Antoni C, Apelbaum A, Hagel P, >> Sitsel O, Raisch T, Prumbaum D, et al (2019) SPHIRE-crYOLO is a fast and >> accurate fully automated particle picker for cryo-EM. Communications >> Biology 2: 218 https://doi.org/10.1038/s42003-019-0437-z >> >> Bepler T, Morin A, Rapp M, Brasch J, Shapiro L, Noble AJ & Berger B >> (2019) Positive-unlabeled convolutional neural networks for particle >> picking in cryo-electron micrographs. Nat Methods: 1–8 >> https://doi.org/10.1038/s41592-019-0575-8 >> >> And this paper on micrograph denoising could go in the "micrograph >> preparation" section I suppose, or in its own section: >> >> Bepler T, Kelley K, Noble AJ & Berger B (2020) Topaz-Denoise: general >> deep denoising models for cryoEM and cryoET. Nature Communications 11: 5208 >> https://doi.org/10.1038/s41467-020-18952-1 >> >> I hope this is useful. >> Cheers, >> >> Guillaume >> >> >> On 3 Aug 2021, at 13:43, Thorn, Dr. Andrea >> wrote: >> >> Dear colleagues, >> I have compiled a list of papers that cover the application of AI/machine >> learning methods in single-crystal structure determination (mostly >> macromolecular crystallography) and single-particle Cryo-EM. The draft list >> is attached below. >> >> If I missed any papers, please let me know. I will send the final list >> back here, for the benefit of all who are interested in the topic. >> >> Best wishes, >> >> >> Andrea. >> >> >> __ >> General: >> - Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B. & >> Rosenberg, J. M. (2004). Acta Cryst D. 60, 1705–1716. >> - Morris, R. J. (2004). Acta Cryst D. 60, 2133–2143. >> >> Micrograph preparation: >> - (2020). Journal of Structural Biology. 210, 107498. >> >> Particle Picking: >> - Sanchez-Garcia, R., Segura, J., Maluenda, D., Carazo, J. M. & Sorzano, >> C. O. S. (2018). IUCrJ. 5, 854–865. >> - Al-Azzawi, A., Ouadou, A., Tanner, J. J. & Cheng, J. (2019). BMC >> Bioinformatics. 20, 1–26. >> - George, B., Assaiya, A., Roy, R. J., Kembhavi, A., Chauhan, R., Paul, >> G., Kumar, J. & Philip, N. S. (2021). Commun Biol. 4, 1–12. >> - Lata, K. R., Penczek, P. & Frank, J. (1995). Ultramicroscopy. 58, >> 381–391. >> - Nguyen, N. P., Ersoy, I., Gotberg, J., Bunyak, F. & White, T. A. >> (2021). BMC Bioinformatics. 22, 1–28. >> - Wang, F., Gong, H., Liu, G., Li, M., Yan, C., Xia, T., Li, X. & Zeng, >> J. (2016). Journal of Structural Biology. 195, 325–336. >> - Wong, H. C., Chen, J., Mouche, F., Rouiller, I. & Bern, M. (2004). >> Journal of Structural Biology. 145, 157–167. >> >> Motion description in Cryo-EM: >> - Matsumoto, S., Ishida, S., Araki, M., Kato, T., Terayama, K. & Okuno, >> Y. (2021). Nat Mach Intell. 3, 153–160. >> - Zhong, E. D., Bepler, T., Berger, B. & Davis, J. H. (2021). Nat >> Methods. 18, 176–185. >> >> Local resolution: >> - Avramov, T. K., Vyenielo, D., Gomez-Blanco, J., Adinarayanan, S., >> Vargas, J. & Si, D. (2019). Molecules. 24, 1181. >> - Ramírez-Aportela, E., Mota, J., Conesa, P., Carazo, J. M. & Sorzano, C. >> O. S. (2019). IUCrJ. 6, 1054–1063. >> - (2021). QAEmap: A Novel Local Quality Assessment Method for Protein >> Crystal Structures Using Machine Learning. >> >> Map post-processing: >> - Sanchez-Garcia, R., Gomez-Blanco, J., Cuervo, A., Carazo, J. M., >> Sorzano, C. O. S. & Vargas, J. (2020). BioRxiv. 2020.06.12.148296. >> >> Secondary structure assignment in map: >> - Subramaniya, S. R. M. V., Terashi, G. & Kihara, D. (2019). Nat Methods. >> 16, 911–917. >> - Li, R., Si, D., Zeng, T., Ji, S. & He, J. (2016). 2016 IEEE >> International Conference on Bioinformatics and Biomedicine (BIBM), Vol. pp. >> 41–46. >> - Si, D., Ji, S., Nasr, K. A. & He, J. (2012). Biopolymers. 97, 698–708. >> - He, J. & Huang, S.-Y. Brief Bioinform. >> - Lyu, Z., Wang, Z., Luo, F., Shuai, J. & Huang, Y. (2021). Frontiers in >> Bioengineering and Biotechnology. 9,. >> - Mostosi, P., Schindelin, H., Kollmannsberger, P. & Thorn, A. (2020). >> Angewandte Chemie International Edition. >> >> Automatic structure building: >> - Alnabati, E. & Kihara, D. (2020). Molecules. 25, 82. >> - Si, D., Moritz, S. A., Pfab, J., Hou, J., Cao, R., Wang, L., Wu, T. & >> Cheng, J. (2020). Sci Rep. 10, 1–22. >> - Moritz, S. A., Pfab, J., Wu, T., Hou, J., Cheng, J., Cao, R., Wang, L. >>
Re: [ccp4bb] AI papers in experimental macromolecular structure determination
Thanks Andrea for this! One more for crystallization: Ng JT., Dekker C., Kroemer M., Osborne M., von Delft F., (2014), Acta D, 70, 2702 - 2718 On 03/08/2021 12:43, Thorn, Dr. Andrea wrote: Dear colleagues, I have compiled a list of papers that cover the application of AI/machine learning methods in single-crystal structure determination (mostly macromolecular crystallography) and single-particle Cryo-EM. The draft list is attached below. If I missed any papers, please let me know. I will send the final list back here, for the benefit of all who are interested in the topic. Best wishes, Andrea. __ General: - Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B. & Rosenberg, J. M. (2004). Acta Cryst D. 60, 1705–1716. - Morris, R. J. (2004). Acta Cryst D. 60, 2133–2143. Micrograph preparation: - (2020). Journal of Structural Biology. 210, 107498. Particle Picking: - Sanchez-Garcia, R., Segura, J., Maluenda, D., Carazo, J. M. & Sorzano, C. O. S. (2018). IUCrJ. 5, 854–865. - Al-Azzawi, A., Ouadou, A., Tanner, J. J. & Cheng, J. (2019). BMC Bioinformatics. 20, 1–26. - George, B., Assaiya, A., Roy, R. J., Kembhavi, A., Chauhan, R., Paul, G., Kumar, J. & Philip, N. S. (2021). Commun Biol. 4, 1–12. - Lata, K. R., Penczek, P. & Frank, J. (1995). Ultramicroscopy. 58, 381–391. - Nguyen, N. P., Ersoy, I., Gotberg, J., Bunyak, F. & White, T. A. (2021). BMC Bioinformatics. 22, 1–28. - Wang, F., Gong, H., Liu, G., Li, M., Yan, C., Xia, T., Li, X. & Zeng, J. (2016). Journal of Structural Biology. 195, 325–336. - Wong, H. C., Chen, J., Mouche, F., Rouiller, I. & Bern, M. (2004). Journal of Structural Biology. 145, 157–167. Motion description in Cryo-EM: - Matsumoto, S., Ishida, S., Araki, M., Kato, T., Terayama, K. & Okuno, Y. (2021). Nat Mach Intell. 3, 153–160. - Zhong, E. D., Bepler, T., Berger, B. & Davis, J. H. (2021). Nat Methods. 18, 176–185. Local resolution: - Avramov, T. K., Vyenielo, D., Gomez-Blanco, J., Adinarayanan, S., Vargas, J. & Si, D. (2019). Molecules. 24, 1181. - Ramírez-Aportela, E., Mota, J., Conesa, P., Carazo, J. M. & Sorzano, C. O. S. (2019). IUCrJ. 6, 1054–1063. - (2021). QAEmap: A Novel Local Quality Assessment Method for Protein Crystal Structures Using Machine Learning. Map post-processing: - Sanchez-Garcia, R., Gomez-Blanco, J., Cuervo, A., Carazo, J. M., Sorzano, C. O. S. & Vargas, J. (2020). BioRxiv. 2020.06.12.148296. Secondary structure assignment in map: - Subramaniya, S. R. M. V., Terashi, G. & Kihara, D. (2019). Nat Methods. 16, 911–917. - Li, R., Si, D., Zeng, T., Ji, S. & He, J. (2016). 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Vol. pp. 41–46. - Si, D., Ji, S., Nasr, K. A. & He, J. (2012). Biopolymers. 97, 698–708. - He, J. & Huang, S.-Y. Brief Bioinform. - Lyu, Z., Wang, Z., Luo, F., Shuai, J. & Huang, Y. (2021). Frontiers in Bioengineering and Biotechnology. 9,. - Mostosi, P., Schindelin, H., Kollmannsberger, P. & Thorn, A. (2020). Angewandte Chemie International Edition. Automatic structure building: - Alnabati, E. & Kihara, D. (2020). Molecules. 25, 82. - Si, D., Moritz, S. A., Pfab, J., Hou, J., Cao, R., Wang, L., Wu, T. & Cheng, J. (2020). Sci Rep. 10, 1–22. - Moritz, S. A., Pfab, J., Wu, T., Hou, J., Cheng, J., Cao, R., Wang, L. & Si, D. (2019). - Chojnowski, G., Pereira, J. & Lamzin, V. S. (2019). Acta Cryst D. 75, 753–763. Crystallization: - Liu, R., Freund, Y. & Spraggon, G. (2008). Acta Cryst D. 64, 1187–1195. - (2004). Methods. 34, 390–407. - Bruno, A. E., Charbonneau, P., Newman, J., Snell, E. H., So, D. R., Vanhoucke, V., Watkins, C. J., Williams, S. & Wilson, J. (2018). PLOS ONE. 13, e0198883. Crystal centering: - Ito, S., Ueno, G. & Yamamoto, M. (2019). J Synchrotron Rad. 26, 1361–1366. - Crystal centering using deep learning in X-ray crystallography. - Elbasir, A., Moovarkumudalvan, B., Kunji, K., Kolatkar, P. R., Mall, R. & Bensmail, H. (2019). Bioinformatics. 35, 2216–2225. Diffraction image analysis: - Czyzewski, A., Krawiec, F., Brzezinski, D., Porebski, P. J. & Minor, W. (2021). Expert Systems with Applications. 174, 114740. Peak search in serial crystallography: Ke, T.-W., Brewster, A. S., Yu, S. X., Ushizima, D., Yang, C. & Sauter, N. K. (2018). J Synchrotron Rad. 25, 655–670. Space group assignment from diffraction image (small molecules): Aguiar, J. A., Gong, M. L., Unocic, R. R., Tasdizen, T. & Miller, B. D. (2019). Science Advances. 5, eaaw1949. Data quality assessment in MX: - Vollmar, M., Parkhurst, J. M., Jaques, D., Baslé, A., Murshudov, G. N., Waterman, D. G. & Evans, G. (2020). IUCrJ. 7, 342–354. Ligand recognition: Kowiel, M., Brzezinski, D., Porebski, P. J., Shabalin, I. G., Jaskolski, M. & Minor, W. (2019). Bioinformatics. 35, 452–461. Prediction of missing atoms in small molecular structures: Thomas, N., Smidt, T., Kearnes, S., Yang, L., Li, L., Kohlhoff, K. & Riley, P.
Re: [ccp4bb] AI papers in experimental macromolecular structure determination
In particle picking, you may wish to include the following: George, B., Assaiya, A., Roy, R.J. *et al.* CASSPER is a semantic segmentation-based particle picking algorithm for single-particle cryo-electron microscopy. *Commun Biol* 4, 200 (2021). https://doi.org/10.1038/s42003-021-01721-1 On Tue, Aug 3, 2021 at 9:17 PM Guillaume Gaullier < guillaume.gaull...@icm.uu.se> wrote: > Hello, > > In the particle picking section, you may want to include these two: > > Wagner T, Merino F, Stabrin M, Moriya T, Antoni C, Apelbaum A, Hagel P, > Sitsel O, Raisch T, Prumbaum D, et al (2019) SPHIRE-crYOLO is a fast and > accurate fully automated particle picker for cryo-EM. Communications > Biology 2: 218 https://doi.org/10.1038/s42003-019-0437-z > > Bepler T, Morin A, Rapp M, Brasch J, Shapiro L, Noble AJ & Berger B (2019) > Positive-unlabeled convolutional neural networks for particle picking in > cryo-electron micrographs. Nat Methods: 1–8 > https://doi.org/10.1038/s41592-019-0575-8 > > And this paper on micrograph denoising could go in the "micrograph > preparation" section I suppose, or in its own section: > > Bepler T, Kelley K, Noble AJ & Berger B (2020) Topaz-Denoise: general deep > denoising models for cryoEM and cryoET. Nature Communications 11: 5208 > https://doi.org/10.1038/s41467-020-18952-1 > > I hope this is useful. > Cheers, > > Guillaume > > > On 3 Aug 2021, at 13:43, Thorn, Dr. Andrea > wrote: > > Dear colleagues, > I have compiled a list of papers that cover the application of AI/machine > learning methods in single-crystal structure determination (mostly > macromolecular crystallography) and single-particle Cryo-EM. The draft list > is attached below. > > If I missed any papers, please let me know. I will send the final list > back here, for the benefit of all who are interested in the topic. > > Best wishes, > > > Andrea. > > > __ > General: > - Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B. & > Rosenberg, J. M. (2004). Acta Cryst D. 60, 1705–1716. > - Morris, R. J. (2004). Acta Cryst D. 60, 2133–2143. > > Micrograph preparation: > - (2020). Journal of Structural Biology. 210, 107498. > > Particle Picking: > - Sanchez-Garcia, R., Segura, J., Maluenda, D., Carazo, J. M. & Sorzano, > C. O. S. (2018). IUCrJ. 5, 854–865. > - Al-Azzawi, A., Ouadou, A., Tanner, J. J. & Cheng, J. (2019). BMC > Bioinformatics. 20, 1–26. > - George, B., Assaiya, A., Roy, R. J., Kembhavi, A., Chauhan, R., Paul, > G., Kumar, J. & Philip, N. S. (2021). Commun Biol. 4, 1–12. > - Lata, K. R., Penczek, P. & Frank, J. (1995). Ultramicroscopy. 58, > 381–391. > - Nguyen, N. P., Ersoy, I., Gotberg, J., Bunyak, F. & White, T. A. (2021). > BMC Bioinformatics. 22, 1–28. > - Wang, F., Gong, H., Liu, G., Li, M., Yan, C., Xia, T., Li, X. & Zeng, J. > (2016). Journal of Structural Biology. 195, 325–336. > - Wong, H. C., Chen, J., Mouche, F., Rouiller, I. & Bern, M. (2004). > Journal of Structural Biology. 145, 157–167. > > Motion description in Cryo-EM: > - Matsumoto, S., Ishida, S., Araki, M., Kato, T., Terayama, K. & Okuno, Y. > (2021). Nat Mach Intell. 3, 153–160. > - Zhong, E. D., Bepler, T., Berger, B. & Davis, J. H. (2021). Nat Methods. > 18, 176–185. > > Local resolution: > - Avramov, T. K., Vyenielo, D., Gomez-Blanco, J., Adinarayanan, S., > Vargas, J. & Si, D. (2019). Molecules. 24, 1181. > - Ramírez-Aportela, E., Mota, J., Conesa, P., Carazo, J. M. & Sorzano, C. > O. S. (2019). IUCrJ. 6, 1054–1063. > - (2021). QAEmap: A Novel Local Quality Assessment Method for Protein > Crystal Structures Using Machine Learning. > > Map post-processing: > - Sanchez-Garcia, R., Gomez-Blanco, J., Cuervo, A., Carazo, J. M., > Sorzano, C. O. S. & Vargas, J. (2020). BioRxiv. 2020.06.12.148296. > > Secondary structure assignment in map: > - Subramaniya, S. R. M. V., Terashi, G. & Kihara, D. (2019). Nat Methods. > 16, 911–917. > - Li, R., Si, D., Zeng, T., Ji, S. & He, J. (2016). 2016 IEEE > International Conference on Bioinformatics and Biomedicine (BIBM), Vol. pp. > 41–46. > - Si, D., Ji, S., Nasr, K. A. & He, J. (2012). Biopolymers. 97, 698–708. > - He, J. & Huang, S.-Y. Brief Bioinform. > - Lyu, Z., Wang, Z., Luo, F., Shuai, J. & Huang, Y. (2021). Frontiers in > Bioengineering and Biotechnology. 9,. > - Mostosi, P., Schindelin, H., Kollmannsberger, P. & Thorn, A. (2020). > Angewandte Chemie International Edition. > > Automatic structure building: > - Alnabati, E. & Kihara, D. (2020). Molecules. 25, 82. > - Si, D., Moritz, S. A., Pfab, J., Hou, J., Cao, R., Wang, L., Wu, T. & > Cheng, J. (2020). Sci Rep. 10, 1–22. > - Moritz, S. A., Pfab, J., Wu, T., Hou, J., Cheng, J., Cao, R., Wang, L. & > Si, D. (2019). > - Chojnowski, G., Pereira, J. & Lamzin, V. S. (2019). Acta Cryst D. 75, > 753–763. > > Crystallization: > - Liu, R., Freund, Y. & Spraggon, G. (2008). Acta Cryst D. 64, 1187–1195. > - (2004). Methods. 34, 390–407. > - Bruno, A. E., Charbonneau, P., Newman, J., Snell, E. H., So, D. R., > Vanhoucke, V., Watkins, C. J., Williams,
Re: [ccp4bb] AI papers in experimental macromolecular structure determination
For model validation, this paper used machine learning (Random Forest) to detect peptide problems: https://doi.org/10.1107/S1399004715008263 Cheers, Robbie > -Original Message- > From: CCP4 bulletin board On Behalf Of Bernhard > Rupp > Sent: Tuesday, August 3, 2021 22:00 > To: CCP4BB@JISCMAIL.AC.UK > Subject: Re: [ccp4bb] AI papers in experimental macromolecular structure > determination > > Maybe we should get to the root of this - what qualifies as machine learning > and what not? > > Do nonparametric predictors such as KDE qualify? > > https://www.ruppweb.org/mattprob/default.html > > Happy toa dd to the confusion. > > -Original Message- > From: CCP4 bulletin board On Behalf Of Tim > Gruene > Sent: Tuesday, August 3, 2021 11:59 > To: CCP4BB@JISCMAIL.AC.UK > Subject: Re: [ccp4bb] AI papers in experimental macromolecular structure > determination > > Hello Andrea, > > profile fitting, like it is done in mosflm > (https://doi.org/10.1107/S090744499900846X) or evalccd, or ... probably also > qualify as AI/machine learning. > > Best wishes, > Tim > > On Tue, 3 Aug 2021 11:43:06 + > "Thorn, Dr. Andrea" wrote: > > > Dear colleagues, > > I have compiled a list of papers that cover the application of > > AI/machine learning methods in single-crystal structure determination > > (mostly macromolecular crystallography) and single-particle Cryo-EM. > > The draft list is attached below. > > > > If I missed any papers, please let me know. I will send the final list > > back here, for the benefit of all who are interested in the topic. > > > > Best wishes, > > > > > > Andrea. > > > > > > __ > > General: > > - Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B. & > > Rosenberg, J. M. (2004). Acta Cryst D. 60, 1705–1716. > > - Morris, R. J. (2004). Acta Cryst D. 60, 2133–2143. > > > > Micrograph preparation: > > - (2020). Journal of Structural Biology. 210, 107498. > > > > Particle Picking: > > - Sanchez-Garcia, R., Segura, J., Maluenda, D., Carazo, J. M. & > > Sorzano, C. O. S. (2018). IUCrJ. 5, 854–865. > > - Al-Azzawi, A., Ouadou, A., Tanner, J. J. & Cheng, J. (2019). BMC > > Bioinformatics. 20, 1–26. > > - George, B., Assaiya, A., Roy, R. J., Kembhavi, A., Chauhan, R., > > Paul, G., Kumar, J. & Philip, N. S. (2021). Commun Biol. 4, 1–12. > > - Lata, K. R., Penczek, P. & Frank, J. (1995). Ultramicroscopy. 58, > > 381–391. > > - Nguyen, N. P., Ersoy, I., Gotberg, J., Bunyak, F. & White, T. A. > > (2021). BMC Bioinformatics. 22, 1–28. > > - Wang, F., Gong, H., Liu, G., Li, M., Yan, C., Xia, T., Li, X. & > > Zeng, J. (2016). Journal of Structural Biology. 195, 325–336. > > - Wong, H. C., Chen, J., Mouche, F., Rouiller, I. & Bern, M. (2004). > > Journal of Structural Biology. 145, 157–167. > > > > Motion description in Cryo-EM: > > - Matsumoto, S., Ishida, S., Araki, M., Kato, T., Terayama, K. & > > Okuno, Y. (2021). Nat Mach Intell. 3, 153–160. > > - Zhong, E. D., Bepler, T., Berger, B. & Davis, J. H. (2021). Nat > > Methods. 18, 176–185. > > > > Local resolution: > > - Avramov, T. K., Vyenielo, D., Gomez-Blanco, J., Adinarayanan, S., > > Vargas, J. & Si, D. (2019). Molecules. 24, 1181. > > - Ramírez-Aportela, E., Mota, J., Conesa, P., Carazo, J. M. & Sorzano, > > C. O. S. (2019). IUCrJ. 6, 1054–1063. > > - (2021). QAEmap: A Novel Local Quality Assessment Method for Protein > > Crystal Structures Using Machine Learning. > > > > Map post-processing: > > - Sanchez-Garcia, R., Gomez-Blanco, J., Cuervo, A., Carazo, J. M., > > Sorzano, C. O. S. & Vargas, J. (2020). BioRxiv. 2020.06.12.148296. > > > > Secondary structure assignment in map: > > - Subramaniya, S. R. M. V., Terashi, G. & Kihara, D. (2019). Nat > > Methods. 16, 911–917. > > - Li, R., Si, D., Zeng, T., Ji, S. & He, J. (2016). 2016 IEEE > > International Conference on Bioinformatics and Biomedicine (BIBM), > > Vol. pp. 41–46. > > - Si, D., Ji, S., Nasr, K. A. & He, J. (2012). Biopolymers. 97, > > 698–708. > > - He, J. & Huang, S.-Y. Brief Bioinform. > > - Lyu, Z., Wang, Z., Luo, F., Shuai, J. & Huang, Y. (2021). Frontiers > > in Bioengineering and Biotechnology. 9,. > > - Mostosi, P., Schindelin, H., Kollmannsberger, P. & Thorn, A. > > (2020). Angewandte Chemie International Edition. > > > > Automatic structure building: > > - Alnabati, E. & Kihara, D. (2020). Molecules. 25, 82
Re: [ccp4bb] AI papers in experimental macromolecular structure determination
Maybe we should get to the root of this - what qualifies as machine learning and what not? Do nonparametric predictors such as KDE qualify? https://www.ruppweb.org/mattprob/default.html Happy toa dd to the confusion. -Original Message- From: CCP4 bulletin board On Behalf Of Tim Gruene Sent: Tuesday, August 3, 2021 11:59 To: CCP4BB@JISCMAIL.AC.UK Subject: Re: [ccp4bb] AI papers in experimental macromolecular structure determination Hello Andrea, profile fitting, like it is done in mosflm (https://doi.org/10.1107/S090744499900846X) or evalccd, or ... probably also qualify as AI/machine learning. Best wishes, Tim On Tue, 3 Aug 2021 11:43:06 + "Thorn, Dr. Andrea" wrote: > Dear colleagues, > I have compiled a list of papers that cover the application of > AI/machine learning methods in single-crystal structure determination > (mostly macromolecular crystallography) and single-particle Cryo-EM. > The draft list is attached below. > > If I missed any papers, please let me know. I will send the final list > back here, for the benefit of all who are interested in the topic. > > Best wishes, > > > Andrea. > > > __ > General: > - Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B. & > Rosenberg, J. M. (2004). Acta Cryst D. 60, 1705–1716. > - Morris, R. J. (2004). Acta Cryst D. 60, 2133–2143. > > Micrograph preparation: > - (2020). Journal of Structural Biology. 210, 107498. > > Particle Picking: > - Sanchez-Garcia, R., Segura, J., Maluenda, D., Carazo, J. M. & > Sorzano, C. O. S. (2018). IUCrJ. 5, 854–865. > - Al-Azzawi, A., Ouadou, A., Tanner, J. J. & Cheng, J. (2019). BMC > Bioinformatics. 20, 1–26. > - George, B., Assaiya, A., Roy, R. J., Kembhavi, A., Chauhan, R., > Paul, G., Kumar, J. & Philip, N. S. (2021). Commun Biol. 4, 1–12. > - Lata, K. R., Penczek, P. & Frank, J. (1995). Ultramicroscopy. 58, > 381–391. > - Nguyen, N. P., Ersoy, I., Gotberg, J., Bunyak, F. & White, T. A. > (2021). BMC Bioinformatics. 22, 1–28. > - Wang, F., Gong, H., Liu, G., Li, M., Yan, C., Xia, T., Li, X. & > Zeng, J. (2016). Journal of Structural Biology. 195, 325–336. > - Wong, H. C., Chen, J., Mouche, F., Rouiller, I. & Bern, M. (2004). > Journal of Structural Biology. 145, 157–167. > > Motion description in Cryo-EM: > - Matsumoto, S., Ishida, S., Araki, M., Kato, T., Terayama, K. & > Okuno, Y. (2021). Nat Mach Intell. 3, 153–160. > - Zhong, E. D., Bepler, T., Berger, B. & Davis, J. H. (2021). Nat > Methods. 18, 176–185. > > Local resolution: > - Avramov, T. K., Vyenielo, D., Gomez-Blanco, J., Adinarayanan, S., > Vargas, J. & Si, D. (2019). Molecules. 24, 1181. > - Ramírez-Aportela, E., Mota, J., Conesa, P., Carazo, J. M. & Sorzano, > C. O. S. (2019). IUCrJ. 6, 1054–1063. > - (2021). QAEmap: A Novel Local Quality Assessment Method for Protein > Crystal Structures Using Machine Learning. > > Map post-processing: > - Sanchez-Garcia, R., Gomez-Blanco, J., Cuervo, A., Carazo, J. M., > Sorzano, C. O. S. & Vargas, J. (2020). BioRxiv. 2020.06.12.148296. > > Secondary structure assignment in map: > - Subramaniya, S. R. M. V., Terashi, G. & Kihara, D. (2019). Nat > Methods. 16, 911–917. > - Li, R., Si, D., Zeng, T., Ji, S. & He, J. (2016). 2016 IEEE > International Conference on Bioinformatics and Biomedicine (BIBM), > Vol. pp. 41–46. > - Si, D., Ji, S., Nasr, K. A. & He, J. (2012). Biopolymers. 97, > 698–708. > - He, J. & Huang, S.-Y. Brief Bioinform. > - Lyu, Z., Wang, Z., Luo, F., Shuai, J. & Huang, Y. (2021). Frontiers > in Bioengineering and Biotechnology. 9,. > - Mostosi, P., Schindelin, H., Kollmannsberger, P. & Thorn, A. > (2020). Angewandte Chemie International Edition. > > Automatic structure building: > - Alnabati, E. & Kihara, D. (2020). Molecules. 25, 82. > - Si, D., Moritz, S. A., Pfab, J., Hou, J., Cao, R., Wang, L., Wu, T. > & Cheng, J. (2020). Sci Rep. 10, 1–22. > - Moritz, S. A., Pfab, J., Wu, T., Hou, J., Cheng, J., Cao, R., Wang, > L. & Si, D. (2019). > - Chojnowski, G., Pereira, J. & Lamzin, V. S. (2019). Acta Cryst D. > 75, 753–763. > > Crystallization: > - Liu, R., Freund, Y. & Spraggon, G. (2008). Acta Cryst D. 64, > 1187–1195. > - (2004). Methods. 34, 390–407. > - Bruno, A. E., Charbonneau, P., Newman, J., Snell, E. H., So, D. R., > Vanhoucke, V., Watkins, C. J., Williams, S. & Wilson, J. (2018). PLOS > ONE. 13, e0198883. > > Crystal centering: > - Ito, S., Ueno, G. & Yamamoto, M. (2019). J Synchrotron Rad. 26, > 1361–1366. > - Crystal centering using deep learning in X-ray crystallography. > - Elbasir, A., Moovarkumudalvan, B., Kunji, K., Kolatkar,
Re: [ccp4bb] AI papers in experimental macromolecular structure determination
One more: BraggNet: integrating Bragg peaks using neural networks B. Sullivan, R. Archibald, J. Azadmanesh, V. G. Vandavasi, P. S. Langan, L. Coates, V. Lynch and P. Langan J. Appl. Cryst. (2019). 52, 854-863 Pavel On Tue, Aug 3, 2021 at 4:53 AM Thorn, Dr. Andrea < andrea.th...@uni-hamburg.de> wrote: > Dear colleagues, > > I have compiled a list of papers that cover the application of AI/machine > learning methods in single-crystal structure determination (mostly > macromolecular crystallography) and single-particle Cryo-EM. The draft list > is attached below. > > > > If I missed any papers, please let me know. I will send the final list > back here, for the benefit of all who are interested in the topic. > > > > Best wishes, > > > > > > Andrea. > > > > > > __ > > General: > > - Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B. & > Rosenberg, J. M. (2004). Acta Cryst D. 60, 1705–1716. > > - Morris, R. J. (2004). Acta Cryst D. 60, 2133–2143. > > > > Micrograph preparation: > > - (2020). Journal of Structural Biology. 210, 107498. > > > > Particle Picking: > > - Sanchez-Garcia, R., Segura, J., Maluenda, D., Carazo, J. M. & Sorzano, > C. O. S. (2018). IUCrJ. 5, 854–865. > > - Al-Azzawi, A., Ouadou, A., Tanner, J. J. & Cheng, J. (2019). BMC > Bioinformatics. 20, 1–26. > > - George, B., Assaiya, A., Roy, R. J., Kembhavi, A., Chauhan, R., Paul, > G., Kumar, J. & Philip, N. S. (2021). Commun Biol. 4, 1–12. > > - Lata, K. R., Penczek, P. & Frank, J. (1995). Ultramicroscopy. 58, > 381–391. > > - Nguyen, N. P., Ersoy, I., Gotberg, J., Bunyak, F. & White, T. A. (2021). > BMC Bioinformatics. 22, 1–28. > > - Wang, F., Gong, H., Liu, G., Li, M., Yan, C., Xia, T., Li, X. & Zeng, J. > (2016). Journal of Structural Biology. 195, 325–336. > > - Wong, H. C., Chen, J., Mouche, F., Rouiller, I. & Bern, M. (2004). > Journal of Structural Biology. 145, 157–167. > > > > Motion description in Cryo-EM: > > - Matsumoto, S., Ishida, S., Araki, M., Kato, T., Terayama, K. & Okuno, Y. > (2021). Nat Mach Intell. 3, 153–160. > > - Zhong, E. D., Bepler, T., Berger, B. & Davis, J. H. (2021). Nat Methods. > 18, 176–185. > > > > Local resolution: > > - Avramov, T. K., Vyenielo, D., Gomez-Blanco, J., Adinarayanan, S., > Vargas, J. & Si, D. (2019). Molecules. 24, 1181. > > - Ramírez-Aportela, E., Mota, J., Conesa, P., Carazo, J. M. & Sorzano, C. > O. S. (2019). IUCrJ. 6, 1054–1063. > > - (2021). QAEmap: A Novel Local Quality Assessment Method for Protein > Crystal Structures Using Machine Learning. > > > > Map post-processing: > > - Sanchez-Garcia, R., Gomez-Blanco, J., Cuervo, A., Carazo, J. M., > Sorzano, C. O. S. & Vargas, J. (2020). BioRxiv. 2020.06.12.148296. > > > > Secondary structure assignment in map: > > - Subramaniya, S. R. M. V., Terashi, G. & Kihara, D. (2019). Nat Methods. > 16, 911–917. > > - Li, R., Si, D., Zeng, T., Ji, S. & He, J. (2016). 2016 IEEE > International Conference on Bioinformatics and Biomedicine (BIBM), Vol. pp. > 41–46. > > - Si, D., Ji, S., Nasr, K. A. & He, J. (2012). Biopolymers. 97, 698–708. > > - He, J. & Huang, S.-Y. Brief Bioinform. > > - Lyu, Z., Wang, Z., Luo, F., Shuai, J. & Huang, Y. (2021). Frontiers in > Bioengineering and Biotechnology. 9,. > > - Mostosi, P., Schindelin, H., Kollmannsberger, P. & Thorn, A. (2020). > Angewandte Chemie International Edition. > > > > Automatic structure building: > > - Alnabati, E. & Kihara, D. (2020). Molecules. 25, 82. > > - Si, D., Moritz, S. A., Pfab, J., Hou, J., Cao, R., Wang, L., Wu, T. & > Cheng, J. (2020). Sci Rep. 10, 1–22. > > - Moritz, S. A., Pfab, J., Wu, T., Hou, J., Cheng, J., Cao, R., Wang, L. & > Si, D. (2019). > > - Chojnowski, G., Pereira, J. & Lamzin, V. S. (2019). Acta Cryst D. 75, > 753–763. > > > > Crystallization: > > - Liu, R., Freund, Y. & Spraggon, G. (2008). Acta Cryst D. 64, 1187–1195. > > - (2004). Methods. 34, 390–407. > > - Bruno, A. E., Charbonneau, P., Newman, J., Snell, E. H., So, D. R., > Vanhoucke, V., Watkins, C. J., Williams, S. & Wilson, J. (2018). PLOS ONE. > 13, e0198883. > > > > Crystal centering: > > - Ito, S., Ueno, G. & Yamamoto, M. (2019). J Synchrotron Rad. 26, > 1361–1366. > > - Crystal centering using deep learning in X-ray crystallography. > > - Elbasir, A., Moovarkumudalvan, B., Kunji, K., Kolatkar, P. R., Mall, R. > & Bensmail, H. (2019). Bioinformatics. 35, 2216–2225. > > > > Diffraction image analysis: > > - Czyzewski, A., Krawiec, F., Brzezinski, D., Porebski, P. J. & Minor, W. > (2021). Expert Systems with Applications. 174, 114740. > > > > Peak search in serial crystallography: > > Ke, T.-W., Brewster, A. S., Yu, S. X., Ushizima, D., Yang, C. & Sauter, N. > K. (2018). J Synchrotron Rad. 25, 655–670. > > > > Space group assignment from diffraction image (small molecules): > > Aguiar, J. A., Gong, M. L., Unocic, R. R., Tasdizen, T. & Miller, B. D. > (2019). Science Advances. 5, eaaw1949. > > > > Data quality assessment in MX: > > - Vollmar, M., Parkhurst, J. M., Jaques, D., Baslé, A., Murshudov,
Re: [ccp4bb] AI papers in experimental macromolecular structure determination
Hello Andrea, profile fitting, like it is done in mosflm (https://doi.org/10.1107/S090744499900846X) or evalccd, or ... probably also qualify as AI/machine learning. Best wishes, Tim On Tue, 3 Aug 2021 11:43:06 + "Thorn, Dr. Andrea" wrote: > Dear colleagues, > I have compiled a list of papers that cover the application of > AI/machine learning methods in single-crystal structure determination > (mostly macromolecular crystallography) and single-particle Cryo-EM. > The draft list is attached below. > > If I missed any papers, please let me know. I will send the final > list back here, for the benefit of all who are interested in the > topic. > > Best wishes, > > > Andrea. > > > __ > General: > - Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B. & > Rosenberg, J. M. (2004). Acta Cryst D. 60, 1705–1716. > - Morris, R. J. (2004). Acta Cryst D. 60, 2133–2143. > > Micrograph preparation: > - (2020). Journal of Structural Biology. 210, 107498. > > Particle Picking: > - Sanchez-Garcia, R., Segura, J., Maluenda, D., Carazo, J. M. & > Sorzano, C. O. S. (2018). IUCrJ. 5, 854–865. > - Al-Azzawi, A., Ouadou, A., Tanner, J. J. & Cheng, J. (2019). BMC > Bioinformatics. 20, 1–26. > - George, B., Assaiya, A., Roy, R. J., Kembhavi, A., Chauhan, R., > Paul, G., Kumar, J. & Philip, N. S. (2021). Commun Biol. 4, 1–12. > - Lata, K. R., Penczek, P. & Frank, J. (1995). Ultramicroscopy. 58, > 381–391. > - Nguyen, N. P., Ersoy, I., Gotberg, J., Bunyak, F. & White, T. A. > (2021). BMC Bioinformatics. 22, 1–28. > - Wang, F., Gong, H., Liu, G., Li, M., Yan, C., Xia, T., Li, X. & > Zeng, J. (2016). Journal of Structural Biology. 195, 325–336. > - Wong, H. C., Chen, J., Mouche, F., Rouiller, I. & Bern, M. (2004). > Journal of Structural Biology. 145, 157–167. > > Motion description in Cryo-EM: > - Matsumoto, S., Ishida, S., Araki, M., Kato, T., Terayama, K. & > Okuno, Y. (2021). Nat Mach Intell. 3, 153–160. > - Zhong, E. D., Bepler, T., Berger, B. & Davis, J. H. (2021). Nat > Methods. 18, 176–185. > > Local resolution: > - Avramov, T. K., Vyenielo, D., Gomez-Blanco, J., Adinarayanan, S., > Vargas, J. & Si, D. (2019). Molecules. 24, 1181. > - Ramírez-Aportela, E., Mota, J., Conesa, P., Carazo, J. M. & > Sorzano, C. O. S. (2019). IUCrJ. 6, 1054–1063. > - (2021). QAEmap: A Novel Local Quality Assessment Method for Protein > Crystal Structures Using Machine Learning. > > Map post-processing: > - Sanchez-Garcia, R., Gomez-Blanco, J., Cuervo, A., Carazo, J. M., > Sorzano, C. O. S. & Vargas, J. (2020). BioRxiv. 2020.06.12.148296. > > Secondary structure assignment in map: > - Subramaniya, S. R. M. V., Terashi, G. & Kihara, D. (2019). Nat > Methods. 16, 911–917. > - Li, R., Si, D., Zeng, T., Ji, S. & He, J. (2016). 2016 IEEE > International Conference on Bioinformatics and Biomedicine (BIBM), > Vol. pp. 41–46. > - Si, D., Ji, S., Nasr, K. A. & He, J. (2012). Biopolymers. 97, > 698–708. > - He, J. & Huang, S.-Y. Brief Bioinform. > - Lyu, Z., Wang, Z., Luo, F., Shuai, J. & Huang, Y. (2021). Frontiers > in Bioengineering and Biotechnology. 9,. > - Mostosi, P., Schindelin, H., Kollmannsberger, P. & Thorn, A. > (2020). Angewandte Chemie International Edition. > > Automatic structure building: > - Alnabati, E. & Kihara, D. (2020). Molecules. 25, 82. > - Si, D., Moritz, S. A., Pfab, J., Hou, J., Cao, R., Wang, L., Wu, T. > & Cheng, J. (2020). Sci Rep. 10, 1–22. > - Moritz, S. A., Pfab, J., Wu, T., Hou, J., Cheng, J., Cao, R., Wang, > L. & Si, D. (2019). > - Chojnowski, G., Pereira, J. & Lamzin, V. S. (2019). Acta Cryst D. > 75, 753–763. > > Crystallization: > - Liu, R., Freund, Y. & Spraggon, G. (2008). Acta Cryst D. 64, > 1187–1195. > - (2004). Methods. 34, 390–407. > - Bruno, A. E., Charbonneau, P., Newman, J., Snell, E. H., So, D. R., > Vanhoucke, V., Watkins, C. J., Williams, S. & Wilson, J. (2018). PLOS > ONE. 13, e0198883. > > Crystal centering: > - Ito, S., Ueno, G. & Yamamoto, M. (2019). J Synchrotron Rad. 26, > 1361–1366. > - Crystal centering using deep learning in X-ray crystallography. > - Elbasir, A., Moovarkumudalvan, B., Kunji, K., Kolatkar, P. R., > Mall, R. & Bensmail, H. (2019). Bioinformatics. 35, 2216–2225. > > Diffraction image analysis: > - Czyzewski, A., Krawiec, F., Brzezinski, D., Porebski, P. J. & > Minor, W. (2021). Expert Systems with Applications. 174, 114740. > > Peak search in serial crystallography: > Ke, T.-W., Brewster, A. S., Yu, S. X., Ushizima, D., Yang, C. & > Sauter, N. K. (2018). J Synchrotron Rad. 25, 655–670. > > Space group assignment from diffraction image (small molecules): > Aguiar, J. A., Gong, M. L., Unocic, R. R., Tasdizen, T. & Miller, B. > D. (2019). Science Advances. 5, eaaw1949. > > Data quality assessment in MX: > - Vollmar, M., Parkhurst, J. M., Jaques, D., Baslé, A., Murshudov, G. > N., Waterman, D. G. & Evans, G. (2020). IUCrJ. 7, 342–354. > > Ligand recognition: > Kowiel, M., Brzezinski, D., Porebski, P. J., Shabalin, I. G., > Jaskolski, M. & Minor, W.
Re: [ccp4bb] AI papers in experimental macromolecular structure determination
Andrea, you may want to include this one: Using support vector machines to improve elemental ion identification in macromolecular crystal structures. Morshed N, Echols N, Adams PD Acta Cryst. D71, 1147-58 (2015). Pavel On Tue, Aug 3, 2021 at 4:53 AM Thorn, Dr. Andrea < andrea.th...@uni-hamburg.de> wrote: > Dear colleagues, > > I have compiled a list of papers that cover the application of AI/machine > learning methods in single-crystal structure determination (mostly > macromolecular crystallography) and single-particle Cryo-EM. The draft list > is attached below. > > > > If I missed any papers, please let me know. I will send the final list > back here, for the benefit of all who are interested in the topic. > > > > Best wishes, > > > > > > Andrea. > > > > > > __ > > General: > > - Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B. & > Rosenberg, J. M. (2004). Acta Cryst D. 60, 1705–1716. > > - Morris, R. J. (2004). Acta Cryst D. 60, 2133–2143. > > > > Micrograph preparation: > > - (2020). Journal of Structural Biology. 210, 107498. > > > > Particle Picking: > > - Sanchez-Garcia, R., Segura, J., Maluenda, D., Carazo, J. M. & Sorzano, > C. O. S. (2018). IUCrJ. 5, 854–865. > > - Al-Azzawi, A., Ouadou, A., Tanner, J. J. & Cheng, J. (2019). BMC > Bioinformatics. 20, 1–26. > > - George, B., Assaiya, A., Roy, R. J., Kembhavi, A., Chauhan, R., Paul, > G., Kumar, J. & Philip, N. S. (2021). Commun Biol. 4, 1–12. > > - Lata, K. R., Penczek, P. & Frank, J. (1995). Ultramicroscopy. 58, > 381–391. > > - Nguyen, N. P., Ersoy, I., Gotberg, J., Bunyak, F. & White, T. A. (2021). > BMC Bioinformatics. 22, 1–28. > > - Wang, F., Gong, H., Liu, G., Li, M., Yan, C., Xia, T., Li, X. & Zeng, J. > (2016). Journal of Structural Biology. 195, 325–336. > > - Wong, H. C., Chen, J., Mouche, F., Rouiller, I. & Bern, M. (2004). > Journal of Structural Biology. 145, 157–167. > > > > Motion description in Cryo-EM: > > - Matsumoto, S., Ishida, S., Araki, M., Kato, T., Terayama, K. & Okuno, Y. > (2021). Nat Mach Intell. 3, 153–160. > > - Zhong, E. D., Bepler, T., Berger, B. & Davis, J. H. (2021). Nat Methods. > 18, 176–185. > > > > Local resolution: > > - Avramov, T. K., Vyenielo, D., Gomez-Blanco, J., Adinarayanan, S., > Vargas, J. & Si, D. (2019). Molecules. 24, 1181. > > - Ramírez-Aportela, E., Mota, J., Conesa, P., Carazo, J. M. & Sorzano, C. > O. S. (2019). IUCrJ. 6, 1054–1063. > > - (2021). QAEmap: A Novel Local Quality Assessment Method for Protein > Crystal Structures Using Machine Learning. > > > > Map post-processing: > > - Sanchez-Garcia, R., Gomez-Blanco, J., Cuervo, A., Carazo, J. M., > Sorzano, C. O. S. & Vargas, J. (2020). BioRxiv. 2020.06.12.148296. > > > > Secondary structure assignment in map: > > - Subramaniya, S. R. M. V., Terashi, G. & Kihara, D. (2019). Nat Methods. > 16, 911–917. > > - Li, R., Si, D., Zeng, T., Ji, S. & He, J. (2016). 2016 IEEE > International Conference on Bioinformatics and Biomedicine (BIBM), Vol. pp. > 41–46. > > - Si, D., Ji, S., Nasr, K. A. & He, J. (2012). Biopolymers. 97, 698–708. > > - He, J. & Huang, S.-Y. Brief Bioinform. > > - Lyu, Z., Wang, Z., Luo, F., Shuai, J. & Huang, Y. (2021). Frontiers in > Bioengineering and Biotechnology. 9,. > > - Mostosi, P., Schindelin, H., Kollmannsberger, P. & Thorn, A. (2020). > Angewandte Chemie International Edition. > > > > Automatic structure building: > > - Alnabati, E. & Kihara, D. (2020). Molecules. 25, 82. > > - Si, D., Moritz, S. A., Pfab, J., Hou, J., Cao, R., Wang, L., Wu, T. & > Cheng, J. (2020). Sci Rep. 10, 1–22. > > - Moritz, S. A., Pfab, J., Wu, T., Hou, J., Cheng, J., Cao, R., Wang, L. & > Si, D. (2019). > > - Chojnowski, G., Pereira, J. & Lamzin, V. S. (2019). Acta Cryst D. 75, > 753–763. > > > > Crystallization: > > - Liu, R., Freund, Y. & Spraggon, G. (2008). Acta Cryst D. 64, 1187–1195. > > - (2004). Methods. 34, 390–407. > > - Bruno, A. E., Charbonneau, P., Newman, J., Snell, E. H., So, D. R., > Vanhoucke, V., Watkins, C. J., Williams, S. & Wilson, J. (2018). PLOS ONE. > 13, e0198883. > > > > Crystal centering: > > - Ito, S., Ueno, G. & Yamamoto, M. (2019). J Synchrotron Rad. 26, > 1361–1366. > > - Crystal centering using deep learning in X-ray crystallography. > > - Elbasir, A., Moovarkumudalvan, B., Kunji, K., Kolatkar, P. R., Mall, R. > & Bensmail, H. (2019). Bioinformatics. 35, 2216–2225. > > > > Diffraction image analysis: > > - Czyzewski, A., Krawiec, F., Brzezinski, D., Porebski, P. J. & Minor, W. > (2021). Expert Systems with Applications. 174, 114740. > > > > Peak search in serial crystallography: > > Ke, T.-W., Brewster, A. S., Yu, S. X., Ushizima, D., Yang, C. & Sauter, N. > K. (2018). J Synchrotron Rad. 25, 655–670. > > > > Space group assignment from diffraction image (small molecules): > > Aguiar, J. A., Gong, M. L., Unocic, R. R., Tasdizen, T. & Miller, B. D. > (2019). Science Advances. 5, eaaw1949. > > > > Data quality assessment in MX: > > - Vollmar, M., Parkhurst, J. M., Jaques, D., Baslé, A.,
Re: [ccp4bb] AI papers in experimental macromolecular structure determination
Hello, In the particle picking section, you may want to include these two: Wagner T, Merino F, Stabrin M, Moriya T, Antoni C, Apelbaum A, Hagel P, Sitsel O, Raisch T, Prumbaum D, et al (2019) SPHIRE-crYOLO is a fast and accurate fully automated particle picker for cryo-EM. Communications Biology 2: 218 https://doi.org/10.1038/s42003-019-0437-z Bepler T, Morin A, Rapp M, Brasch J, Shapiro L, Noble AJ & Berger B (2019) Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs. Nat Methods: 1–8 https://doi.org/10.1038/s41592-019-0575-8 And this paper on micrograph denoising could go in the "micrograph preparation" section I suppose, or in its own section: Bepler T, Kelley K, Noble AJ & Berger B (2020) Topaz-Denoise: general deep denoising models for cryoEM and cryoET. Nature Communications 11: 5208 https://doi.org/10.1038/s41467-020-18952-1 I hope this is useful. Cheers, Guillaume On 3 Aug 2021, at 13:43, Thorn, Dr. Andrea mailto:andrea.th...@uni-hamburg.de>> wrote: Dear colleagues, I have compiled a list of papers that cover the application of AI/machine learning methods in single-crystal structure determination (mostly macromolecular crystallography) and single-particle Cryo-EM. The draft list is attached below. If I missed any papers, please let me know. I will send the final list back here, for the benefit of all who are interested in the topic. Best wishes, Andrea. __ General: - Gopalakrishnan, V., Livingston, G., Hennessy, D., Buchanan, B. & Rosenberg, J. M. (2004). Acta Cryst D. 60, 1705–1716. - Morris, R. J. (2004). Acta Cryst D. 60, 2133–2143. Micrograph preparation: - (2020). Journal of Structural Biology. 210, 107498. Particle Picking: - Sanchez-Garcia, R., Segura, J., Maluenda, D., Carazo, J. M. & Sorzano, C. O. S. (2018). IUCrJ. 5, 854–865. - Al-Azzawi, A., Ouadou, A., Tanner, J. J. & Cheng, J. (2019). BMC Bioinformatics. 20, 1–26. - George, B., Assaiya, A., Roy, R. J., Kembhavi, A., Chauhan, R., Paul, G., Kumar, J. & Philip, N. S. (2021). Commun Biol. 4, 1–12. - Lata, K. R., Penczek, P. & Frank, J. (1995). Ultramicroscopy. 58, 381–391. - Nguyen, N. P., Ersoy, I., Gotberg, J., Bunyak, F. & White, T. A. (2021). BMC Bioinformatics. 22, 1–28. - Wang, F., Gong, H., Liu, G., Li, M., Yan, C., Xia, T., Li, X. & Zeng, J. (2016). Journal of Structural Biology. 195, 325–336. - Wong, H. C., Chen, J., Mouche, F., Rouiller, I. & Bern, M. (2004). Journal of Structural Biology. 145, 157–167. Motion description in Cryo-EM: - Matsumoto, S., Ishida, S., Araki, M., Kato, T., Terayama, K. & Okuno, Y. (2021). Nat Mach Intell. 3, 153–160. - Zhong, E. D., Bepler, T., Berger, B. & Davis, J. H. (2021). Nat Methods. 18, 176–185. Local resolution: - Avramov, T. K., Vyenielo, D., Gomez-Blanco, J., Adinarayanan, S., Vargas, J. & Si, D. (2019). Molecules. 24, 1181. - Ramírez-Aportela, E., Mota, J., Conesa, P., Carazo, J. M. & Sorzano, C. O. S. (2019). IUCrJ. 6, 1054–1063. - (2021). QAEmap: A Novel Local Quality Assessment Method for Protein Crystal Structures Using Machine Learning. Map post-processing: - Sanchez-Garcia, R., Gomez-Blanco, J., Cuervo, A., Carazo, J. M., Sorzano, C. O. S. & Vargas, J. (2020). BioRxiv. 2020.06.12.148296. Secondary structure assignment in map: - Subramaniya, S. R. M. V., Terashi, G. & Kihara, D. (2019). Nat Methods. 16, 911–917. - Li, R., Si, D., Zeng, T., Ji, S. & He, J. (2016). 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Vol. pp. 41–46. - Si, D., Ji, S., Nasr, K. A. & He, J. (2012). Biopolymers. 97, 698–708. - He, J. & Huang, S.-Y. Brief Bioinform. - Lyu, Z., Wang, Z., Luo, F., Shuai, J. & Huang, Y. (2021). Frontiers in Bioengineering and Biotechnology. 9,. - Mostosi, P., Schindelin, H., Kollmannsberger, P. & Thorn, A. (2020). Angewandte Chemie International Edition. Automatic structure building: - Alnabati, E. & Kihara, D. (2020). Molecules. 25, 82. - Si, D., Moritz, S. A., Pfab, J., Hou, J., Cao, R., Wang, L., Wu, T. & Cheng, J. (2020). Sci Rep. 10, 1–22. - Moritz, S. A., Pfab, J., Wu, T., Hou, J., Cheng, J., Cao, R., Wang, L. & Si, D. (2019). - Chojnowski, G., Pereira, J. & Lamzin, V. S. (2019). Acta Cryst D. 75, 753–763. Crystallization: - Liu, R., Freund, Y. & Spraggon, G. (2008). Acta Cryst D. 64, 1187–1195. - (2004). Methods. 34, 390–407. - Bruno, A. E., Charbonneau, P., Newman, J., Snell, E. H., So, D. R., Vanhoucke, V., Watkins, C. J., Williams, S. & Wilson, J. (2018). PLOS ONE. 13, e0198883. Crystal centering: - Ito, S., Ueno, G. & Yamamoto, M. (2019). J Synchrotron Rad. 26, 1361–1366. - Crystal centering using deep learning in X-ray crystallography. - Elbasir, A., Moovarkumudalvan, B., Kunji, K., Kolatkar, P. R., Mall, R. & Bensmail, H. (2019). Bioinformatics. 35, 2216–2225. Diffraction image analysis: - Czyzewski, A., Krawiec, F., Brzezinski, D., Porebski, P. J. & Minor, W. (2021). Expert Systems with Applications. 174, 114740. Peak search in
