Literature DB >> 21262382

Exploiting personalized information for reagent selection in drug design.

Jonas Boström1, Niklas Falk, Christian Tyrchan.   

Abstract

Drug discovery is currently being industrialized. This fact is confusing, given that it is happening in times when the rest of the world has entered the subsequent information age. Here, we introduce a concept and an infrastructure for the now popular and well-known recommender systems in the context of exploiting one of the cornerstones of drug design: chemical reagent selection. The goal is to create and transfer information openly to facilitate intuition and serendipity in drug design. The system is tailored to highlight reagents from our corporate reagent database; reagents that a chemist might not have considered based purely on their own experience.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21262382     DOI: 10.1016/j.drudis.2011.01.006

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  2 in total

1.  Using matched molecular series as a predictive tool to optimize biological activity.

Authors:  Noel M O'Boyle; Jonas Boström; Roger A Sayle; Adrian Gill
Journal:  J Med Chem       Date:  2014-03-14       Impact factor: 7.446

2.  Hybrid semantic recommender system for chemical compounds in large-scale datasets.

Authors:  Marcia Barros; Andre Moitinho; Francisco M Couto
Journal:  J Cheminform       Date:  2021-02-23       Impact factor: 5.514

  2 in total

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