For what it's worth, the RDKit allows you to get the adjacency matrix for a
molecule with the function Chem.GetAdjacencyMatrix (from python) or
MolOps::getAdjacencyMatrix (from c++).

-greg

On Wednesday, 3 February 2016, Maciek Wójcikowski <mac...@wojcikowski.pl>
wrote:

> So my initial guess was wrong. They also include a github repo, where you
> can exactly see how the graph is formed:
> https://github.com/HIPS/neural-fingerprint/blob/master/neuralfingerprint/mol_graph.py#L75
>
> ----
> Pozdrawiam,  |  Best regards,
> Maciek Wójcikowski
> mac...@wojcikowski.pl
> <javascript:_e(%7B%7D,'cvml','mac...@wojcikowski.pl');>
>
> 2016-02-03 14:35 GMT+01:00 Giuseppe Marco Randazzo <gmranda...@gmail.com
> <javascript:_e(%7B%7D,'cvml','gmranda...@gmail.com');>>:
>
>> The graph it’s a simple adjacency matrix (square matrix) which is able to
>> represent the connectivity of the  molecule.
>>
>> The element of this matrix are the atoms which can be connected.
>>
>> If you have a simple smile like c1ccccc1 this means that your molecule is
>> a ring of six atoms (6*c), and the small letter “c” means that your atom is
>> of aromatic type. thus you can write
>> your adjacency matrix in this manner:
>>
>>
>>
>> Adjacency matrix:
>>
>>
>>   c1 c2 c3 c4 c5 c6
>> c1 0 1 0 0 0 1
>> c2 1 0 1 0 0 0
>> c3 0 1 0 1 0 0
>> c4 0 0 1 0 1 0
>> c5 0 0 0 1 0 1
>> c6 1 0 0 0 1 0
>>
>> 1 means that there is a bond between two atoms.
>>
>> That’s it.
>>
>> Marco
>>
>>
>> On 03 Feb 2016, at 14:24, Guillaume GODIN <guillaume.go...@firmenich.com
>> <javascript:_e(%7B%7D,'cvml','guillaume.go...@firmenich.com');>> wrote:
>>
>> Dear All,
>>
>> Can you explain me a little how to reproduce this paper experimental
>> process:
>> http://www.broadinstitute.org/~jbloom/smrc/neural-fingerprints.pdf page
>> 5 using RDKit.
>>
>> Look like they tweak RDKit:
>>
>> From page 5: “Experimental setup:
>> 1 Our pipeline takes as input the SMILES [30] string encoding of each
>> molecule, which is then converted into a graph using RDKit [20].
>> 2 We also used RDKit to produce the extended circular fingerprints used
>> in the baseline.
>> 3 Hydrogen atoms were treated implicitly.
>>
>> In our convolutional networks, the initial atom and bond features were
>> chosen to be similar to those used by ECFP: Initial atom features
>> concatenated a one-hot encoding of the atom’s element, its degree, the
>> number of attached hydrogen atoms, and the implicit valence, and an
>> aromaticity indicator.
>> The bond features were a concatenation of whether the bond type was
>> single, double, triple, or aromatic, whether the bond was conjugated, and
>> whether the bond was part of a ring.”
>>
>> My question: I don’t see how to obtain the graph from the smile.
>>
>> Best regards,
>>
>> *Dr. Guillaume GODIN*
>> Project Manager
>> Innovation
>> CORPORATE R&D DIVISION
>> DIRECT LINE +41 (0)22 780 3645
>> MOBILE       +41 (0)79 536 1039
>> *Firmenich SA*
>> RUE DES JEUNES 1 | CASE POSTALE 239 | CH-1211 GENEVE 8
>>
>>
>>
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