title: An improved systematic approach to predicting transcription factor target genes using support vector machine.
abstract: Biological prediction of transcription factor binding sites and their corresponding transcription factor target genes (TFTGs) makes great contribution to understanding the gene regulatory networks. However, these approaches are based on laborious and time-consuming biological experiments. Numerous computational approaches have shown great potential to circumvent laborious biological methods. However, the majority of these algorithms provide limited performances and fail to consider the structural property of the datasets. We proposed a refined systematic computational approach for predicting TFTGs. Based on previous work done on identifying auxin response factor target genes from Arabidopsis thaliana co-expression data, we adopted a novel reverse-complementary distance-sensitive n-gram profile algorithm. This algorithm converts each upstream sub-sequence into a high-dimensional vector data point and transforms the prediction task into a classification problem using support vector machine-based classifier. Our approach showed significant improvement compared to other computational methods based on the area under curve value of the receiver operating characteristic curve using 10-fold cross validation. In addition, in the light of the highly skewed structure of the dataset, we also evaluated other metrics and their associated curves, such as precision-recall curves and cost curves, which provided highly satisfactory results.
authors.affiliation: School of Agribusiness and Agriscience, Middle Tennessee State University, Murfreesboro, Tennessee, United States of America.
authors.forename: Song
authors.initials: S
authors.lastname: Cui
authors.affiliation: Department of Computer Science, Texas Tech University, Lubbock, Texas, United States of America.
authors.forename: Eunseog
authors.initials: E
authors.lastname: Youn
authors.affiliation: Department of Plant and Soil Science, Texas Tech University, Lubbock, Texas, United States of America.
authors.forename: Joohyun
authors.initials: J
authors.lastname: Lee
authors.affiliation: Department of Plant and Soil Science, Texas Tech University, Lubbock, Texas, United States of America.
authors.forename: Stephan J
authors.initials: SJ
authors.lastname: Maas
mesh_terms: D000465:Algorithms; D017360:Arabidopsis / Q000235:genetics* / Q000378:metabolism*; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods*; D017343:Genes, Plant / Q000235:genetics*; D060388:Support Vector Machine; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D014157:Transcription Factors
references.citation: Bioinformatics. 2000 Jan;16(1):16-23
references.pmid: 10812473
references.citation: PLoS Comput Biol. 2009 Apr;5(4):e1000352
references.pmid: 19360128
references.citation: Nucleic Acids Res. 2002 Dec 15;30(24):5549-60
references.pmid: 12490723
references.citation: J Mol Biol. 1998 Nov 27;284(2):241-54
references.pmid: 9813115
references.citation: Plant Cell. 1994 May;6(5):645-57
references.pmid: 8038604
references.citation: Science. 2001 Oct 26;294(5543):797-9
references.pmid: 11679654
references.citation: Mol Syst Biol. 2011 Dec 06;7:555
references.pmid: 22146299
references.citation: Nucleic Acids Res. 2010 Jun;38(11):e126
references.pmid: 20375099
references.citation: Microb Ecol. 2010 Apr;59(3):511-22
references.pmid: 20037795
references.citation: Nucleic Acids Res. 2003 Jul 1;31(13):3576-9
references.pmid: 12824369
references.citation: Nat Methods. 2011 Mar;8(3):191-2
references.pmid: 21358620
references.citation: Plant Physiol. 2004 Apr;134(4):1555-73
references.pmid: 15047898
references.citation: Nucleic Acids Res. 2006 Jan 1;34(Database issue):D108-10
references.pmid: 16381825
references.citation: Nucleic Acids Res. 2011 Jan;39(2):e6
references.pmid: 21051340
references.citation: Nucleic Acids Res. 2007;35(13):4433-40
references.pmid: 17576669
references.citation: Nature. 2001 May 24;411(6836):494-8
references.pmid: 11373684
references.citation: Plant Cell. 1995 Oct;7(10):1611-23
references.pmid: 7580254
references.citation: Bioinformatics. 2008 Jan 1;24(1):110-7
references.pmid: 18048398
references.citation: Appl Environ Microbiol. 2007 Aug;73(16):5261-7
references.pmid: 17586664
references.citation: Bioinformatics. 2005 Jul 1;21(13):2933-42
references.pmid: 15860560
references.citation: Nat Biotechnol. 2005 Jan;23(1):137-44
references.pmid: 15637633
references.citation: BMC Bioinformatics. 2005 Apr 04;6:84
references.pmid: 15807889
references.citation: Science. 1993 Oct 8;262(5131):208-14
references.pmid: 8211139
references.citation: BMC Genomics. 2009 May 16;10:229
references.pmid: 19445709
references.citation: Nat Rev Genet. 2011 Dec 29;13(2):71
references.pmid: 22207166
references.citation: Protein Sci. 2007 Feb;16(2):216-26
references.pmid: 17189479
references.citation: Nucleic Acids Res. 2003 Jul 1;31(13):3666-8
references.pmid: 12824389
references.citation: Nucleic Acids Res. 2001 Feb 1;29(3):774-82
references.pmid: 11160901
references.citation: J Mol Biol. 2000 Mar 10;296(5):1205-14
references.pmid: 10698627