title: CLIP-GENE: a web service of the condition specific context-laid integrative analysis for gene prioritization in mouse TF knockout experiments.
abstract: Transcriptome data from the gene knockout experiment in mouse is widely used to investigate functions of genes and relationship to phenotypes. When a gene is knocked out, it is important to identify which genes are affected by the knockout gene. Existing methods, including differentially expressed gene (DEG) methods, can be used for the analysis. However, existing methods require cutoff values to select candidate genes, which can produce either too many false positives or false negatives. This hurdle can be addressed either by improving the accuracy of gene selection or by providing a method to rank candidate genes effectively, or both. Prioritization of candidate genes should consider the goals or context of the knockout experiment. As of now, there are no tools designed for both selecting and prioritizing genes from the mouse knockout data. Hence, the necessity of a new tool arises.
  
  
  
  In this study, we present CLIP-GENE, a web service that selects gene markers by utilizing differentially expressed genes, mouse transcription factor (TF) network, and single nucleotide variant information. Then, protein-protein interaction network and literature information are utilized to find genes that are relevant to the phenotypic differences. One of the novel features is to allow researchers to specify their contexts or hypotheses in a set of keywords to rank genes according to the contexts that the user specify. We believe that CLIP-GENE will be useful in characterizing functions of TFs in mouse experiments.
  
  
  
  http://epigenomics.snu.ac.kr/CLIP-GENE REVIEWERS: This article was reviewed by Dr. Lee and Dr. Pongor.
authors: Interdisciplinary Program in Bioinformatics, Seoul National University, Daehak-dong, Seoul, 151-742, Korea.
authors: Benjamin
authors: B
authors: Hur
authors: Interdisciplinary Program in Bioinformatics, Seoul National University, Daehak-dong, Seoul, 151-742, Korea.
authors: Sangsoo
authors: S
authors: Lim
authors: Department of Computer Science, School of Informatics and Computing, Indiana University, 150 S. Woodlawn Avenue, Bloomington, 47404, USA.
authors: Heejoon
authors: H
authors: Chae
authors: Department of Computer Science and Engineering, Seoul National University, Daehak-dong, 151-742, Seoul, Korea.
authors: Seokjun
authors: S
authors: Seo
authors: Department of Computer Science and Engineering, Korea University, Seoul, Korea.
authors: Sunwon
authors: S
authors: Lee
authors: Department of Computer Science and Engineering, Korea University, Seoul, Korea.
authors: Jaewoo
authors: J
authors: Kang
authors: Interdisciplinary Program in Bioinformatics, Seoul National University, Daehak-dong, Seoul, 151-742, Korea. sunkim.bioinfo@snu.ac.kr.|Department of Computer Science and Engineering, Seoul National University, Daehak-dong, 151-742, Seoul, Korea. sunkim.bioinfo@snu.ac.kr.|Bioinformatics Institute, Seoul National University, Daehak-dong, Seoul, 151-742, Korea. sunkim.bioinfo@snu.ac.kr.
authors: Sun
authors: S
authors: Kim
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D020407:Internet; D051379:Mice; D018345:Mice, Knockout; D020411:Oligonucleotide Array Sequence Analysis; D014157:Transcription Factors / Q000235:genetics*; D059467:Transcriptome
chemical_list: D014157:Transcription Factors
keywords: Gene prioritization; Gene selection; Knockout mouse; Web tool