{"title":"Exploratory analysis of the BioAssay Network with implications to therapeutic discovery","authors":"Jintao Zhang, G. Lushington, Jun Huan","doi":"10.1109/BIBM.2010.5706630","DOIUrl":null,"url":null,"abstract":"Despite intense investment growth and technology development, there is an observed bottleneck in drug discovery and development over the past decade. NIH started the Molecular Libraries Initiative (MLI) in 2004 to enlarge the pool for potential drug targets, especially from the “undruggable” part of human genome, and potential drug candidates from much broader types of drug-like small molecules. In this paper we used the concepts of network biology to integrate MLI data with other biological databases such as DrugBank and UniHI, and evaluated the potential of MLI target proteins being new drug targets. Our analysis provided some measures of the value of the MLI data as a resource for both basic chemical biology research and future therapeutic discovery.","PeriodicalId":275098,"journal":{"name":"2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2010.5706630","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Despite intense investment growth and technology development, there is an observed bottleneck in drug discovery and development over the past decade. NIH started the Molecular Libraries Initiative (MLI) in 2004 to enlarge the pool for potential drug targets, especially from the “undruggable” part of human genome, and potential drug candidates from much broader types of drug-like small molecules. In this paper we used the concepts of network biology to integrate MLI data with other biological databases such as DrugBank and UniHI, and evaluated the potential of MLI target proteins being new drug targets. Our analysis provided some measures of the value of the MLI data as a resource for both basic chemical biology research and future therapeutic discovery.