Literature DB >> 12954196

Self-organizing neural networks for pharmacophore mapping.

Jaroslaw Polanski1.   

Abstract

We have shown that the SOM network can be a useful tool in pharmacophore mapping strategy. A possibility for the generation of fuzzy molecular representations together with its ability for discovering such aspects of molecular similarity that can be easily overlooked by a human chemist is an important advantage. The reduction in complexity resulting from the data compression is another one. The main disadvantage of SOM usage is the need for the application of special software packages not usually organized in user friendly toolboxes that can be applied easily. Instead, it needs some experience and time to optimize the parameters controlling the performance of the network.

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Year:  2003        PMID: 12954196     DOI: 10.1016/s0169-409x(03)00116-9

Source DB:  PubMed          Journal:  Adv Drug Deliv Rev        ISSN: 0169-409X            Impact factor:   15.470


  3 in total

1.  Self-organizing neural networks for modeling robust 3D and 4D QSAR: application to dihydrofolate reductase inhibitors.

Authors:  Jaroslaw Polanski; Andrzej Bak; Rafal Gieleciak; Tomasz Magdziarz
Journal:  Molecules       Date:  2004-12-31       Impact factor: 4.411

Review 2.  Unsupervised Learning in Drug Design from Self-Organization to Deep Chemistry.

Authors:  Jaroslaw Polanski
Journal:  Int J Mol Sci       Date:  2022-03-03       Impact factor: 5.923

3.  Functional group and substructure searching as a tool in metabolomics.

Authors:  Masaaki Kotera; Andrew G McDonald; Sinéad Boyce; Keith F Tipton
Journal:  PLoS One       Date:  2008-02-06       Impact factor: 3.240

  3 in total

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