title: HitPick: a web server for hit identification and target prediction of chemical screenings.
abstract: BACKGROUND
  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 naïve Bayesian target models to predict targets of identified hits. The performance of the HitPick web server is presented and discussed.
  
  
  BACKGROUND
  The server can be accessed at http://mips.helmholtz-muenchen.de/proj/hitpick.
  
  
  BACKGROUND
  monica.campillos@helmholtz-muenchen.de.
authors.affiliation: Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
authors.forename: Xueping
authors.initials: X
authors.lastname: Liu
authors.forename: Ingo
authors.initials: I
authors.lastname: Vogt
authors.forename: Tanzeem
authors.initials: T
authors.lastname: Haque
authors.forename: Mónica
authors.initials: M
authors.lastname: Campillos
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D057166:High-Throughput Screening Assays / Q000379:methods*; D006801:Humans; D020407:Internet; D008024:Ligands; D011506:Proteins / Q000737:chemistry; D012984:Software
chemical_list: D008024:Ligands; D011506:Proteins