Last modified by emacasali on 2023/01/11 16:05

From version 6.1
edited by emacasali
on 2023/01/11 11:03
Change comment: There is no comment for this version
To version 5.1
edited by emacasali
on 2023/01/11 10:53
Change comment: There is no comment for this version

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4 4  (((
5 5  = MEDIUM - Machine lEarning Drug dIscovery throUgh dynaMics =
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8 8  
9 -Giorgio Colombo Group (UNIPV)
10 +ML-based DF classification tool
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11 11  )))
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17 -= Why this tool is useful? =
18 += What can I find here? =
18 18  
19 -The prediction of the best ligand for a specific protein could be a huge challenge using the classical approaches like molecular docking and stabilisation energy calculations.
20 +* Notice how the table of contents on the right
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21 -Here we report on a fast and solid workflow which starts from our DF-matrix method to analyse how the protein globally behaves in the presence of a ligand. Machine Learning (ML) trains a Convolutional Neural Network (CNN) model directly on the pixel images of DF: train is preformed using a known ligand and the different behaviour of the protein is evaluated in the presence and in absence of it.
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23 -With the so trained model further predictions can be performed using different ligands.
24 -
25 25  = Who has access? =
26 26  
27 27  Describe the audience of this collab.