A decision tree learning approach for the classification and analysis of high-throughput screening data

被引:0
|
作者
Engels, MFM [1 ]
De Winter, H [1 ]
Tollenaere, JP [1 ]
机构
[1] Janssen Res Fdn, Dept Theoret Med Chem, B-2340 Beerse, Belgium
关键词
D O I
暂无
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
引用
收藏
页码:429 / 430
页数:2
相关论文
共 50 条
  • [41] A parallel high-throughput approach to liquid crystal screening
    Cull, T
    Goulding, M
    Bradley, M
    REVIEW OF SCIENTIFIC INSTRUMENTS, 2005, 76 (06):
  • [42] A statistical approach to high-throughput screening of predicted orthologs
    Min, Jeong Eun
    Whiteside, Matthew D.
    Brinkman, Fiona S. L.
    McNeney, Brad
    Graham, Jinko
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2011, 55 (01) : 935 - 943
  • [43] Quantitative high-throughput approach to chalkophore screening in freshwaters
    Zhang, Xiaokai
    Li, Boling
    Deng, Jianming
    Qin, Boqiang
    Wells, Mona
    Tefsen, Boris
    SCIENCE OF THE TOTAL ENVIRONMENT, 2020, 735
  • [44] Approaches for mining high-throughput screening data sets
    Engels, MFM
    Knapen, K
    Tollenaere, JP
    RATIONAL APPROACHES TO DRUG DESIGN, 2001, : 496 - 505
  • [45] Creating knowledge from high-throughput screening data
    Engels, MFM
    SMALL MOLECULE-PROTEIN INTERACTIONS, 2003, 42 : 87 - 101
  • [46] GUItars: A GUI Tool for Analysis of High-Throughput RNA Interference Screening Data
    Goktug, Asli N.
    Ong, Su Sien
    Chen, Taosheng
    PLOS ONE, 2012, 7 (11):
  • [47] Machine Learning-Driven Data Valuation for Optimizing High-Throughput Screening Pipelines
    Hesse, Joshua
    Boldini, Davide
    Sieber, Stephan A.
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2024, 64 (21) : 8142 - 8152
  • [48] Deep Fish: Deep Learning-Based Classification of Zebrafish Deformation for High-Throughput Screening
    Ishaq, Omer
    Sadanandan, Sajith Kecheril
    Wahlby, Carolina
    SLAS DISCOVERY, 2017, 22 (01) : 102 - 107
  • [49] Retrospective analysis of an experimental high-throughput screening data set by recursive partitioning
    van Rhee, AM
    Stocker, J
    Printzenhoff, D
    Creech, C
    Wagoner, PK
    Spear, KL
    JOURNAL OF COMBINATORIAL CHEMISTRY, 2001, 3 (03): : 267 - 277
  • [50] Comparative study of machine-learning and chemometric tools for analysis of in-vivo high-throughput screening data
    Simmons, Kirk
    Kinney, John
    Owens, Aaron
    Kleier, Dan
    Bloch, Karen
    Argentar, Dave
    Walsh, Alicia
    Vaidyanathan, Ganesh
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2008, 48 (08) : 1663 - 1668