Browsing by Author "Wild, David J."

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  • Chen, Bin; Ding, Ying; Wild, David J. (PLoS Computational Biology, 2012-07)
    The rapidly increasing amount of public data in chemistry and biology provides new opportunities for large-scale data mining for drug discovery. Systematic integration of these heterogeneous sets and provision of algorithms ...
  • Wiggins, Gary; Wild, David J. (Elsevier, 2006)
    Surveys the curriculum developed at Indiana University for teaching cheminformatics in the IU School of Informatics
  • Ding, Ying; Zhu, Qian; Wang, Huijun; Jiao, Dazhi; Dong, Xiao; Chen, Bin; Wild, David J. (BioMed Central, 2010)
    Background: Recently there has been an explosion of new data sources about genes, proteins, genetic variations, chemical compounds, diseases and drugs. Integration of these data sources and the identification of patterns ...
  • Wild, David J.; Qiu, Judy; He, Bing; Dong, Xiao; Tang, Jie; Ding, Ying; Wang, Huijun (PLoS, 2011-03-23)
    The overwhelming amount of available scholarly literature in the life sciences poses significant challenges to scientists wishing to keep up with important developments related to their research, but also provides a useful ...
  • Wild, David J.; Ding, Ying; Chen, Bin (Chemistry Central Ltd., 2012-03-08)
    Background: Systems chemical biology and chemogenomics are considered critical, integrative disciplines in modern biomedical research, but require data mining of large, integrated, heterogeneous datasets from chemistry and ...
  • Kulkarni, Varsha S. ([Bloomington, Ind.] : Indiana University, 2016-12)
    Highly chemically similar drugs usually possess similar biological activities but small changes in chemistry result in large differences in biological effects. Chemically similar drug pairs showing extreme deviations in ...
  • Wild, David J.; Desai, Pankaj; Qiu, Judy; Moorthy, Ganesh; Chen, Bin; Shin, Jae Hong; Sun, Yuyin; Wang, Huijun; Ding, Ying; Tang, Jie; He, Bing (Public Library of Science, 2011-12-06)
    Much life science and biology research requires an understanding of complex relationships between biological entities (genes, compounds, pathways, diseases, and so on). There is a wealth of data on such relationships in ...
  • Seal, Abhik ([Bloomington, Ind.] : Indiana University, 2016-01)
    Prediction of unknown drug target interactions from bioassay data is critical not only for the understanding of various interactions but also crucial for the development of new drugs and repurposing of old ones. Conventional ...
  • Wild, David J.; Lajiness, Michael S.; Ding, Ying; Challa, Sashikiran; Sun, Yuyin; Zhu, Qian (BioMed Central Ltd., 2011-06-23)
    Background: Semantic Web Technology (SWT) makes it possible to integrate and search the large volume of life science datasets in the public domain, as demonstrated by well-known linked data projects such as LODD, Bio2RDF, ...
  • Zhu, Qian; Lajiness, Michael S.; Ding, Ying; Wild, David J. (Chemistry Central, 2010)
    Background: In recent years, there has been a huge increase in the amount of publicly-available and proprietary information pertinent to drug discovery. However, there is a distinct lack of data mining tools available to ...

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