title: iNuc-PhysChem: a sequence-based predictor for identifying nucleosomes via physicochemical properties.
abstract: Nucleosome positioning has important roles in key cellular processes. Although intensive efforts have been made in this area, the rules defining nucleosome positioning is still elusive and debated. In this study, we carried out a systematic comparison among the profiles of twelve DNA physicochemical features between the nucleosomal and linker sequences in the Saccharomyces cerevisiae genome. We found that nucleosomal sequences have some position-specific physicochemical features, which can be used for in-depth studying nucleosomes. Meanwhile, a new predictor, called iNuc-PhysChem, was developed for identification of nucleosomal sequences by incorporating these physicochemical properties into a 1788-D (dimensional) feature vector, which was further reduced to a 884-D vector via the IFS (incremental feature selection) procedure to optimize the feature set. It was observed by a cross-validation test on a benchmark dataset that the overall success rate achieved by iNuc-PhysChem was over 96% in identifying nucleosomal or linker sequences. As a web-server, iNuc-PhysChem is freely accessible to the public at http://lin.uestc.edu.cn/server/iNuc-PhysChem. For the convenience of the vast majority of experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated mathematics that were presented just for the integrity in developing the predictor. Meanwhile, for those who prefer to run predictions in their own computers, the predictor's code can be easily downloaded from the web-server. It is anticipated that iNuc-PhysChem may become a useful high throughput tool for both basic research and drug design.
authors.affiliation: Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan, China. wchen@gordonlifescience.org
authors.forename: Wei
authors.initials: W
authors.lastname: Chen
authors.forename: Hao
authors.initials: H
authors.lastname: Lin
authors.forename: Peng-Mian
authors.initials: PM
authors.lastname: Feng
authors.forename: Chen
authors.initials: C
authors.lastname: Ding
authors.forename: Yong-Chun
authors.initials: YC
authors.lastname: Zuo
authors.forename: Kuo-Chen
authors.initials: KC
authors.lastname: Chou
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods*; D004271:DNA, Fungal / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D006657:Histones / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D020407:Internet; D008957:Models, Genetic; D008958:Models, Molecular; D008969:Molecular Sequence Data; D009707:Nucleosomes / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D012441:Saccharomyces cerevisiae / Q000235:genetics* / Q000378:metabolism; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism
chemical_list: D004271:DNA, Fungal; D006657:Histones; D009707:Nucleosomes; D029701:Saccharomyces cerevisiae Proteins