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Chemoinformatics and Drug Discovery
This article reviews current achievements in the field of chemoinformatics and their impact on modern drug discovery processes. The main data mining approaches used in cheminformatics, such as descriptor computations, structural similarity matrices, and classification algorithms, are outlined. The a...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2002
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6146447/ http://dx.doi.org/10.3390/70800566 |
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author | Xu, Jun Hagler, Arnold |
author_facet | Xu, Jun Hagler, Arnold |
author_sort | Xu, Jun |
collection | PubMed |
description | This article reviews current achievements in the field of chemoinformatics and their impact on modern drug discovery processes. The main data mining approaches used in cheminformatics, such as descriptor computations, structural similarity matrices, and classification algorithms, are outlined. The applications of cheminformatics in drug discovery, such as compound selection, virtual library generation, virtual high throughput screening, HTS data mining, and in silico ADMET are discussed. At the conclusion, future directions of chemoinformatics are suggested. |
format | Online Article Text |
id | pubmed-6146447 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2002 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61464472018-11-19 Chemoinformatics and Drug Discovery Xu, Jun Hagler, Arnold Molecules Review This article reviews current achievements in the field of chemoinformatics and their impact on modern drug discovery processes. The main data mining approaches used in cheminformatics, such as descriptor computations, structural similarity matrices, and classification algorithms, are outlined. The applications of cheminformatics in drug discovery, such as compound selection, virtual library generation, virtual high throughput screening, HTS data mining, and in silico ADMET are discussed. At the conclusion, future directions of chemoinformatics are suggested. MDPI 2002-08-30 /pmc/articles/PMC6146447/ http://dx.doi.org/10.3390/70800566 Text en © 2002 by MDPI (http://www.mdpi.org). Reproduction is permitted for noncommercial purposes. |
spellingShingle | Review Xu, Jun Hagler, Arnold Chemoinformatics and Drug Discovery |
title | Chemoinformatics and Drug Discovery |
title_full | Chemoinformatics and Drug Discovery |
title_fullStr | Chemoinformatics and Drug Discovery |
title_full_unstemmed | Chemoinformatics and Drug Discovery |
title_short | Chemoinformatics and Drug Discovery |
title_sort | chemoinformatics and drug discovery |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6146447/ http://dx.doi.org/10.3390/70800566 |
work_keys_str_mv | AT xujun chemoinformaticsanddrugdiscovery AT haglerarnold chemoinformaticsanddrugdiscovery |