ArticlePloS one2012
iNuc-PhysChem: a sequence-based predictor for identifying nucleosomes via physicochemical properties.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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Who cites it
52 citing papers in PubMed.
- HDGS-Net: nucleosome occupancy prediction based on a hybrid dilated gated separable convolutional neural network.BMC genomics · 2026Article
- Comparative analysis and prediction of nucleosome positioning using integrative feature representation and machine learning algorithms.BMC bioinformatics · 2021Article
- A deformation energy model reveals sequence-dependent property of nucleosome positioning.Chromosoma · 2021Article
- Epigenetic Marks and Variation of Sequence-Based Information Along Genomic Regions Are Predictive of Recombination Hot/Cold Spots inFrontiers in genetics · 2021Article
- Iterative sure independent ranking and screening for drug response prediction.BMC medical informatics and decision making · 2020Article
- Article
- PrESOgenesis: A two-layer multi-label predictor for identifying fertility-related proteins using support vector machine and pseudo amino acid composition approach.Scientific reports · 2018Article
- The implication of DNA bending energy for nucleosome positioning and sliding.Scientific reports · 2018Article
- LeNup: learning nucleosome positioning from DNA sequences with improved convolutional neural networks.Bioinformatics (Oxford, England) · 2018Article
- Article
- Improving Prediction of Self-interacting Proteins Using Stacked Sparse Auto-Encoder with PSSM profiles.International journal of biological sciences · 2018Article
- Identifying RNA NFrontiers in microbiology · 2018Article
- A systematic evaluation of nucleotide properties for CRISPR sgRNA design.BMC bioinformatics · 2017Article
- Pse-Analysis: a python package for DNA/RNA and protein/ peptide sequence analysis based on pseudo components and kernel methods.Oncotarget · 2017Article
- Prediction of nucleosome positioning by the incorporation of frequencies and distributions of three different nucleotide segment lengths into a general pseudo k-tuple nucleotide composition.Bioinformatics (Oxford, England) · 2017Article
- iAFP-Ense: An Ensemble Classifier for Identifying Antifreeze Protein by Incorporating Grey Model and PSSM into PseAAC.The Journal of membrane biology · 2016Article
- iOri-Human: identify human origin of replication by incorporating dinucleotide physicochemical properties into pseudo nucleotide composition.Oncotarget · 2016Article
- Comparison of genomic data via statistical distribution.Journal of theoretical biology · 2016Article
- Combined sequence and sequence-structure based methods for analyzing FGF23, CYP24A1 and VDR genes.Meta gene · 2016Article
- Classifying Multifunctional Enzymes by Incorporating Three Different Models into Chou's General Pseudo Amino Acid Composition.The Journal of membrane biology · 2016Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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