國家衛生研究院 NHRI:Item 3990099045/12232
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 12189/12972 (94%)
造访人次 : 956612      在线人数 : 842
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 查询小技巧：
  • 您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果
  • 若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据
    •  进阶搜寻
    主页 ‧ 登入 ‧ 上传 ‧ 说明 ‧ 关于NHRI ‧ 管理 到手机版


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://ir.nhri.org.tw/handle/3990099045/12232


    题名: Logistic regression method for ligand discovery
    作者: Chen, C;Wang, HY
    贡献者: Institute of Population Health Sciences
    摘要: Protein-based virtual screening is integral to the modern drug discovery process. Most protein-based virtual screening experiments are performed using docking programs. The accuracy of a docking program strongly relies on the incorporated scoring function used, which is based on various energy terms. The existing scoring functions deal with the energy terms that use the equal weight function or other weight functions, which do not depend on characteristics of the protein. To improve the existing methods, Lu and Wang proposed a protein-specific scoring function based on a regression analysis that was shown to have higher performance than the existing methods. In this study, we propose a protein-specific scoring approach to select potential ligands based on logistic regression analysis. The performance of our method was evaluated using the Directory of Useful Decoys docked data set, which contains 40 protein targets. The results showed that the proposed method can increase the enrichment factors for most of the 40 protein targets.
    日期: 2020-06
    關聯: Journal of Computational Biology. 2020 Jun;27(6): 934-940.
    Link to: http://dx.doi.org/10.1089/cmb.2019.0232
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1066-5277&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000487270600001
    显示于类别:[其他] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    ISI000487270600001.pdf127KbAdobe PDF216检视/开启


    在NHRI中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈