Re: [ccp4bb] AI papers in experimental macromolecular structure determination

2021-08-03 Thread Tushar R. 
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

2021-08-03 Thread Frank von Delft 

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

2021-08-03 Thread Shekhar Mande 
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

2021-08-03 Thread Robbie Joosten 
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.
> > - 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:
> > -

Re: [ccp4bb] AI papers in experimental macromolecular structure determination

2021-08-03 Thread Bernhard Rupp 
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, 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,

Re: [ccp4bb] AI papers in experimental macromolecular structure determination

2021-08-03 Thread Pavel Afonine 
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

2021-08-03 Thread Tim Gruene 
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

2021-08-03 Thread Pavel Afonine 
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

2021-08-03 Thread Guillaume Gaullier 
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

[ccp4bb] Postdoctoral Fellowship at Pfizer

2021-08-03 Thread Mashalidis, Ellene 
Dear all,

We are seeking an enthusiastic and driven postdoctoral fellow to join the 
Structural and Molecular Sciences (SMS) Department at the Pfizer campus in 
Groton, Connecticut. This fellowship offers the unique opportunity to learn 
about the drug and vaccine development process in the laboratories of an 
innovative industry leader. The successful candidate will receive 
state-of-the-art training in protein structural biology and biochemistry with 
access to unparalleled resources supporting prokaryotic and eukaryotic protein 
expression, purification, and structure determination by both X-ray 
crystallography and cryo-EM. At SMS, we have regular access to all the major 
synchrotron beam lines in the world and dedicated in-house cryo-EM facilities. 
Ideal candidates will have extensive experience in molecular biology, protein 
expression, protein purification, and structure determination.

To apply, please follow the link below:
Postdoctoral Fellow, Structural Biology and Biophysics 
(myworkdayjobs.com)


Kind regards,
Ellene

Ellene H. Mashalidis, PhD
Senior Scientist
Structural and Molecular Sciences
Pfizer Global Research and Development
445 Eastern Point Road
Groton, CT 06340
Building 220/322J
Phone: 860-441-6172
ellene.mashali...@pfizer.com




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https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB=1

This message was issued to members of www.jiscmail.ac.uk/CCP4BB, a mailing list 
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[ccp4bb] AI papers in experimental macromolecular structure determination

2021-08-03 Thread Thorn, Dr. Andrea 
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. 
(2018).

ADP estimation (small molecules):
Gagner, V. A., Jensen, M. & Katona, G. (2021). Mach. Learn.: Sci. Technol. 2, 
035033.


--
Dr. Andrea Thorn | group leader
andrea.th...@uni-hamburg.de

Institute for Nanostructure and Solid State Physics, Universität Hamburg

[ccp4bb] Call for MX beamtime proposals at HZB, BESSY II, deadline September 01, 2021

2021-08-03 Thread Manfred S. Weiss 

Dear all,

the next MX-proposal application deadline: September 01, 2021 is approaching

NEW: REMOTE OPERATION IS NOW POSSIBLE AT BLs14.1 AND 14.2.
PARTICPATION IN REMOTE TRAINING COURSE IS REQUIRED.

As usual, all proposals will be handled by our electronic user portal GATE,
https://www.helmholtz-berlin.de/pubbin/hzbgate

Hereby we would like to invite the submission of new proposals for
MX-beamtime at the HZB-MX beamlines for the next beam time period
(01/2022-05/2022). Please note that in 2022 we are facing an very
long summer shutdown (May-August 2022, weeks 18-34).

In order to apply for beamtime, please register in GATE and submit
a new beam time application proposal.

Please note that we now expect from each research group only ONE proposal,
which can contain up to 20 individual projects.

IMPORTANT: If you have a running 2020-1 or a running 2021-1 proposal, you
may ask for extension. For a 2021-1 proposal, an interim report is necessary,
and for a 2020-1 proposal a full report including highlights. You will also
be able to edit and modify your proposals by adding and deleting projects.

HZB provides MX-beamtime at the three MX-beamlines BL14.1, BL14.2
and BL14.3. The three beamlines are equipped with state-of-the-art
instrumentation and are currently the most productive MX-stations in
Germany with almost 4000 PDB depositions in total. Beamtime is granted
based on the reviewed proposals and on reports from previous research
activities. Please make sure to include them if available.

Experimental setup:

BL14.1:
- Photon energy range: 5.5-16 keV (wavelength: 0.775-2.25 A)
- Photon flux: 1.8x10¹¹ Phot/sec x 100 mA at sample position
 (0.04-1 sec exposure time per frame)
- PILATUS3 S 6M detector with 1000 µm Si sensor thickness, 141 mm-680 mm max. 
distance from the sample
- Microdiffractometer (MD2) with Mini-kappa goniometer
- Automatic sample changer (CATS), 144 sample storage capacity
IMPORTANT: Only UNIPUCKS are possible from now on.
- User defined beam shaping from 50 µm-100 µm diameter possible
- Multi-core XEON-CPU server, with 10GB uplink to Pilatus 6M
- Data collection control via MXCuBE2
- Common MX-software installed including EDNA, XDS, iMOSFLM, CCP4,
 Phenix, SHELXC-D-E, etc.
- Automated data processing using XDSAPP3
- Remotely controlled cryo-shutter for crystal annealing
- AMPTEK-XRF detector and XFEPLOT software available

We are also offering the hard- and software environment for
carrying out UV-RIP experiments at BL14.1. For further information,
please visit:
https://www.helmholtz-berlin.de/forschung/oe/ps/macromolecular-crystallography/ancillary-facilities/uvrip_en.html

BL14.2:
- Photon energy range: 5.5-16 keV (wavelength: 0.775-2.25 A)
- Photon flux: 1.6x10¹¹ Phot/sec x 100 mA at sample position
 (0.05-1 sec exposure time per frame)
- PILATUS3 S 2M detector with 1000 µm Si sensor thickness,
 85 mm - 800 mm distance from the sample (a special mode with
 56 mm distance is also available upon request)
- Nanodiffractometer with fast air-bearing axis and on-axis sample
 microscope
- User defined beam shaping from 30 µm-150 µm diameter possible
- Data collection control via MXCuBE2
- G-ROB sample changer for SPINE support
PLEASE NOTE: For them time being, only SPINE/ESRF pucks are accepted
(Unipuck upgrade is planned for 2022).
- Multi-core XEON-CPU server, with fibre channel SAN up-link data
 processing environment
- Common MX-software installed including EDNA, XDS, iMOSFLM, CCP4,
 Phenix, SHELXC-D-E, etc.
- Automated data processing using XDSAPP
- AMPTEK-XRF detector and XFEPLOT software available
- UV-Microsprectrophotometer offline setup available

If you need atomic resolution or better, BL14.2 is the beamline
of choice for you!!

BL14.3:
- Fixed photon energy: 13.8 keV (wavelength: 0.89 A)
- Photon flux: 1.6x10exp10 Phot/sec x 100mA at sample position
 (3-20 sec exposure time per frame)
- PILATUS 6M detector, 54 mm-450 mm distance from the sample
- MD2S microdiffractometer with mini-kappa goniometer
- RT data collection
- Data collection at 50 K using a He cryostat
- Multi-core XEON-CPU server, with fibre channel SAN up-link data
 processing environment
- Data collection control via MXCuBE2
- Common MX software installed including EDNA, XDS, iMOSFLM, CCP4,
 Phenix, SHELXC-D-E, etc.
- Automated data processing using XDSAPP
- Remotely controlled cryo-shutter for crystal annealing
- REX rapid nozzle exchanger
- HC-Lab dehydration device installed (please specify HC-Lab-beamtime
 in your proposal if needed)
- AMPTEK-XRF detector and XFEPLOT software available

Other facilities:
- Ultra high performance stereo microscope Leica M205A, 20-255x zoom,
 8 Mpix CCD-camera
- Pressure chamber for noble gas derivatization (Xe, Kr available
 upon request)

S1-biolab facilities (separate

[ccp4bb] Extended PDB IDs and PDB DOIs now available in PDBx/mmCIF files

2021-08-03 Thread David Armstrong 

Dear CCP4BB,

wwPDB, in collaboration with the PDBx/mmCIF Working Group 
, has set plans 
 to 
extend the length of ID codes for PDB and Chemical Component Dictionary 
(CCD) ID entries in the future. These extended formats are not supported 
by the legacy PDB file format.


As announced previously 
, 
wwPDB has extended PDB ID length to eight characters prefixed by ‘PDB’, 
e.g., pdb_1abc.


Each PDB ID is issued a corresponding Digital Object Identifier (DOI), 
often required for manuscript submission to journals and described in 
publications by the structure authors.


To help depositors provide information to journals, OneDep now displays 
the PDB ID and DOI on the submission confirmation page.


The extended PDB IDs and corresponding PDB DOIs, along with existing 
four character PDB IDs, are now included in the PDBx/mmCIF formatted 
files. Initially, this will only be available for updated and 
newly-released PDB entries, with an archive-wide update at a later date.


The additional accessions will be provided in the _database_2 PDBx/mmCIF 
category.


For example, PDB entry 1ABC will have the extended PDB ID (pdb_1abc) 
and the corresponding PDB DOI (10.2210/pdb1abc/pdb).


loop_
_database_2.database_id
_database_2.database_code
_database_2.pdbx_database_accession
_database_2.pdbx_DOI
PDB 1abc pdb_1abc 10.2210/pdb1abc/pdb
WWPDB D_1x    ?     ?

Once all available four-character PDB IDs have been consumed, 
newly-deposited PDB entries will only be issued extended PDB ID codes. 
These entries will only be distributed in PDBx/mmCIF format.


wwPDB asks journals, users, and software developers to review code and 
remove related limitations.


Kind Regards,
David Armstrong

--
David Armstrong
Outreach and Training Coordinator
PDBe
European Bioinformatics Institute (EMBL-EBI)
European Molecular Biology Laboratory
Wellcome Trust Genome Campus
Hinxton
Cambridge CB10 1SD UK
Tel: +44 1223 492544




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