HitPick: a web server for hit identification and target prediction of chemical screenings
HitPick: a web server for hit identification and target prediction of chemical screenings
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DOI：
10.1093/bioinformatics/btt303
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发表时间：
2013-08-01
期刊：
影响因子：
5.8
通讯作者：
Campillos, Monica
中科院分区：
文献类型：
--
作者：
Liu, Xueping;Vogt, Ingo;Campillos, Monica
高通量表型分析揭示了调节生物过程的分子信息，如疾病表型和信号通路。在这些分析中，识别命中及其分子靶标对于理解调节生物系统的化学活动至关重要。在这里，我们介绍了HitPick，一个用于识别高通量化学筛选和预测其分子靶点的网络服务器。HitPick将B-score方法应用于命中识别，并将一种新开发的方法结合1-近邻（1NN）相似性搜索和拉普拉斯修正朴素贝叶斯目标模型来预测识别命中的目标。介绍并讨论了HitPick web服务器的性能。
High-throughput phenotypic assays reveal information about the molecules that modulate biological processes, such as a disease phenotype and a signaling pathway. In these assays, the identification of hits along with their molecular targets is critical to understand the chemical activities modulating the biological system. Here, we present HitPick, a web server for identification of hits in high-throughput chemical screenings and prediction of their molecular targets. HitPick applies the B-score method for hit identification and a newly developed approach combining 1-nearest-neighbor (1NN) similarity searching and Laplacian-modified naive Bayesian target models to predict targets of identified hits. The performance of the HitPick web server is presented and discussed.