Inuc-pseknc: A sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition
Open accessAbstract
Motivation: Nucleosome positioning participates in many cellular activities and plays significant roles in regulating cellular processes. With the avalanche of genome sequences generated in the post-genomic age, it is highly desired to develop automated methods for rapidly and effectively identifying nucleosome positioning. Although some computational methods were proposed, most of them were species specific and neglected the intrinsic local structural properties that might play important roles in determining the nucleosome positioning on a DNA sequence. Results: Here a predictor called ‘iNuc-PseKNC’ was developed for predicting nucleosome positioning in Homo sapiens, Caenorhabditis elegans and Drosophila melanogaster genomes, respectively. In the new predictor, the samples of DNA sequences were formulated by a novel feature-vector called ‘pseudo k-tuple nucleotide composition’, into which six DNA local structural properties were incorporated. It was observed by the rigorous cross-validation tests on the three stringent benchmark datasets that the overall success rates achieved by iNuc-PseKNC in predicting the nucleosome positioning of the aforementioned three genomes were 86.27%, 86.90% and 79.97%, respectively. Meanwhile, the results obtained by iNuc-PseKNC on various benchmark datasets used by the previous investigators for different genomes also indicated that the current predictor remarkably outperformed its counterparts. Availability: A user-friendly web-server, iNuc-PseKNC is freely accessible at http://lin.uestc.edu.cn/server/iNuc-PseKNC. Contact: hlin@uestc.edu.cn, wchen@gordonlifescience.org, kcchou@gordonlifescience.org Supplementary information: Supplementary data are available at Bioinformatics online.
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The AUC of the proposed method is 0.857 on the UniProt dataset.
“The value of AUC for our method was 0.857 according to the UniProt dataset [41].”
From An Efficient Classifier for Alzheimer’s Disease Genes Identification (2018) · cites this paper as [41]
Most works in bioinformatics use SVM for classification.
“Most works in bioinformatics [41,46,47,48,49,50,51,52,53,54,55,56,57,58,59] also use SVM for classification.”
From An Efficient Classifier for Alzheimer’s Disease Genes Identification (2018) · cites this paper as [41]
Cites
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
Cristianini, N., & Shawe-Taylor, J. (2000) · doi:10.1017/cbo9780511801389 · Cited by 13,855 · see citing works
Cd-hit: Accelerated for clustering the next-generation sequencing data
Fu, L., Niu, B., Zhu, Z., Wu, S., & Li, W. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts565 · Cited by 11,175 · see citing works
Crystal structure of the nucleosome core particle at 2.8 Å resolution
Luger, K., Mäder, A. W., Richmond, R. K., Sargent, D. F., & Richmond, T. J. (1997) · Nature · doi:10.1038/38444 · Cited by 9,466 · see citing works
Prediction of protein cellular attributes using pseudo‐amino acid composition
Chou, K. (2001) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.1035 · Cited by 1,947 · see citing works
Self-citationA genomic code for nucleosome positioning
Segal, E., Fondufe‐Mittendorf, Y. N., Chen, L., Thåström, A., Field, Y., Moore, I. K., Wang, J.-P. Z., & Widom, J. (2006) · Nature · doi:10.1038/nature04979 · Cited by 1,492 · see citing works
Working Set Selection Using Second Order Information for Training Support Vector Machines
Fan, R.-E., Chen, P.-H., & Lin, C. (2005) · Journal of Machine Learning Research · Cited by 1,409 · see citing works
Dynamic Regulation of Nucleosome Positioning in the Human Genome
Schones, D. E., Cui, K., Cuddapah, S., Roh, T., Barski, A., Wang, Z., Wei, G., & Zhao, K. (2008) · Cell · doi:10.1016/j.cell.2008.02.022 · Cited by 1,396 · see citing works
Kornberg, R. D. (1977) · Annual Review of Biochemistry · doi:10.1146/annurev.bi.46.070177.004435 · Cited by 1,304 · see citing works
The structure of DNA in the nucleosome core
Richmond, T. J., & Davey, C. A. (2003) · Nature · doi:10.1038/nature01595 · Cited by 1,287 · see citing works
Chou, K., & Shen, H. (2008) · Nature Protocols · doi:10.1038/nprot.2007.494 · Cited by 1,226 · see citing works
Self-citationSome remarks on protein attribute prediction and pseudo amino acid composition
Chou, K.-C. (2011) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2010.12.024 · Cited by 1,225 · see citing works
Self-citationPrediction of Protein Structural Classes
Chou, K., & Zhang, C. (1995) · Critical Reviews in Biochemistry and Molecular Biology · doi:10.3109/10409239509083488 · Cited by 1,058 · see citing works
Self-citationUsing amphiphilic pseudo amino acid composition to predict enzyme subfamily classes
Chou, K. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth466 · Cited by 994 · see citing works
Self-citationSequence periodicities in chicken nucleosome core DNA
Satchwell, S. C., Drew, H. R., & TRAVERS, A. A. (1986) · Journal of Molecular Biology · doi:10.1016/0022-2836(86)90452-3 · Cited by 929 · see citing works
A high-resolution atlas of nucleosome occupancy in yeast
Lee, W., Tillo, D., Bray, N., Morse, R. H., Davis, R. W., Hughes, T. R., & Nislow, C. (2007) · Nature Genetics · doi:10.1038/ng2117 · Cited by 829 · see citing works
Recent progress in protein subcellular location prediction
Chou, K., & Shen, H. (2007) · Analytical Biochemistry · doi:10.1016/j.ab.2007.07.006 · Cited by 769 · see citing works
Self-citationNucleosome organization in the Drosophila genome
Mavrich, T. N., Jiang, C., Ioshikhes, I. P., Li, X., Venters, B. J., Zanton, S. J., Tomsho, L. P., Qi, J., Glaser, R. L., Schuster, S. C., et al. (2008) · Nature · doi:10.1038/nature06929 · Cited by 719 · see citing works
Albert, I. U., Mavrich, T. N., Tomsho, L. P., Qi, J., Zanton, S. J., Schuster, S. C., & Pugh, B. F. (2007) · Nature · doi:10.1038/nature05632 · Cited by 694 · see citing works
A barrier nucleosome model for statistical positioning of nucleosomes throughout the yeast genomePreprint
Mavrich, T. N., Ioshikhes, I. P., Venters, B. J., Jiang, C., Tomsho, L. P., Qi, J., Schuster, S. C., Albert, I. U., & Pugh, B. F. (2008) · Genome Research · doi:10.1101/gr.078261.108 · Cited by 673 · see citing works
Chromatin organization marks exon-intron structure
Schwartz, S., Meshorer, E., & Ast, G. (2009) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.1659 · Cited by 638 · see citing works
iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide composition
Chen, W., Feng, P., Lin, H., & Chou, K. (2013) · Nucleic Acids Research · doi:10.1093/nar/gks1450 · Cited by 611 · see citing works
Self-citationValouev, A., Ichikawa, J. K., Tonthat, T., Stuart, J., Ranade, S., Peckham, H. E., Zeng, K., Malek, J. A., Costa, G. L., McKernan, K. J., et al. (2008) · Genome Research · doi:10.1101/gr.076463.108 · Cited by 580 · see citing works
Xiao, X., Wang, P., Lin, W., et al. (2013) · Analytical Biochemistry · doi:10.1016/j.ab.2013.01.019 · Cited by 550 · see citing works
Chou, K.-C., & Cai, Y.-D. (2002) · Journal of Biological Chemistry · doi:10.1074/jbc.m204161200 · Cited by 483 · see citing works
Self-citationPseudo Amino Acid Composition and its Applications in Bioinformatics, Proteomics and System Biology
Chou, K. (2009) · Current Proteomics · doi:10.2174/157016409789973707 · Cited by 478 · see citing works
Self-citationpropy: a tool to generate various modes of Chou’s PseAAC
Cao, D., Xu, Q., & Liang, Y. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt072 · Cited by 477 · see citing works
Poly(dA:dT) tracts: major determinants of nucleosome organization
Segal, E., & Widom, J. (2009) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2009.01.004 · Cited by 419 · see citing works
Some remarks on predicting multi-label attributes in molecular biosystems
Chou, K. (2013) · Molecular BioSystems · doi:10.1039/c3mb25555g · Cited by 413 · see citing works
Self-citationXu, Y., Ding, J., Wu, L., & Chou, K. (2013) · PLoS ONE · doi:10.1371/journal.pone.0055844 · Cited by 389 · see citing works
Self-citationHigh-resolution nucleosome mapping reveals transcription-dependent promoter packagingPreprint
Weiner, A., Hughes, A. L., Yassour, M., Rando, O. J., & Friedman, N. (2009) · Genome Research · doi:10.1101/gr.098509.109 · Cited by 381 · see citing works
High-throughput mapping of the chromatin structure of human promoters
Ozsolak, F., Song, J. S., Liu, X. S., & Fisher, D. E. (2007) · Nature Biotechnology · doi:10.1038/nbt1279 · Cited by 336 · see citing works
Chou, K., Wu, Z., & Xiao, X. (2011) · Molecular BioSystems · doi:10.1039/c1mb05420a · Cited by 334 · see citing works
Self-citationNucleosome positioning signals in genomic DNAPreprint
Peckham, H. E., Thurman, R. E., Fu, Y., Stamatoyannopoulos, J. A., Noble, W. S., Struhl, K., & Weng, Z. (2007) · Genome Research · doi:10.1101/gr.6101007 · Cited by 314 · see citing works
Bhasin, M., & Raghava, G. P. S. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh350 · Cited by 310 · see citing works
Du, P.-F., Wang, X., Xu, C., et al. (2012) · Analytical Biochemistry · doi:10.1016/j.ab.2012.03.015 · Cited by 308 · see citing works
Hajisharifi, Z., Piryaiee, M., Beigi, M. M., Behbahani, M., & Mohabatkar, H. (2013) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2013.08.037 · Cited by 294 · see citing works
Esmaeili, M., Mohabatkar, H., & Mohsenzadeh, S. (2009) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2009.11.016 · Cited by 271 · see citing works
Using subsite coupling to predict signal peptides
Chou, K.-C. (2001) · Protein Engineering, Design and Selection · doi:10.1093/protein/14.2.75 · Cited by 255 · see citing works
Self-citationChou, K., & Shen, H. (2006) · Journal of Proteome Research · doi:10.1021/pr060167c · Cited by 253 · see citing works
Self-citationLin, W., Fang, J., Xiao, X., et al. (2013) · Molecular BioSystems · doi:10.1039/c3mb25466f · Cited by 251 · see citing works
Chen, L., Zeng, W., Cai, Y., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0035254 · Cited by 225 · see citing works
Generic eukaryotic core promoter prediction using structural features of DNAPreprint
Abeel, T., Saeys, Y., Bonnet, É., Rouzé, P., & de Peer, Y. V. (2007) · Genome Research · doi:10.1101/gr.6991408 · Cited by 215 · see citing works
Mohabatkar, H., Beigi, M. M., & Esmaeili, A. (2011) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2011.04.017 · Cited by 214 · see citing works
Sahu, S. S., & Panda, G. (2010) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2010.09.002 · Cited by 207 · see citing works
Prediction of signal peptides using scaled window
Chou, K. (2001) · Peptides · doi:10.1016/s0196-9781(01)00540-x · Cited by 207 · see citing works
Self-citationiNuc-PhysChem: A Sequence-Based Predictor for Identifying Nucleosomes via Physicochemical Properties
Chen, W., Lin, H., Feng, P., Ding, C., Zuo, Y., & Chou, K. (2012) · PLoS ONE · doi:10.1371/journal.pone.0047843 · Cited by 201 · see citing works
Self-citationNucleosome DNA Sequence Pattern Revealed by Multiple Alignment of Experimentally Mapped Sequences
Ioshikhes, I. P., Bolshoy, A., Derenshteyn, K., et al. (1996) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0503 · Cited by 197 · see citing works
Genomic Sequence Is Highly Predictive of Local Nucleosome Depletion
Yuan, G., & Liu, J. S. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0040013 · Cited by 193 · see citing works
A Key Driving Force in Determination of Protein Structural Classes
Chou, K. (1999) · Biochemical and Biophysical Research Communications · doi:10.1006/bbrc.1999.1325 · Cited by 181 · see citing works
Self-citationMohabatkar, H., Beigi, M. M., Abdolahi, K., & Mohsenzadeh, S. (2012) · Medicinal Chemistry · doi:10.2174/157340613804488341 · Cited by 177 · see citing works
Nanni, L., Lumini, A., Gupta, D. K., & Garg, A. (2011) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2011.117 · Cited by 175 · see citing works
Nanni, L., & Lumini, A. (2008) · Amino Acids · doi:10.1007/s00726-007-0018-1 · Cited by 172 · see citing works
Berbenetz, N. M., Nislow, C., & Brown, G. W. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1001092 · Cited by 162 · see citing works
Definitions and Nomenclature of Nucleic Acid Structure Parameters
Dickerson, R. E. (1989) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.1989.10507726 · Cited by 157 · see citing works
Lin, S., & Lapointe, J. (2013) · Journal of Biomedical Science and Engineering · doi:10.4236/jbise.2013.64054 · Cited by 148 · see citing works
Chen, Y.-K., & Li, K.-B. (2012) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2012.10.033 · Cited by 147 · see citing works
Determining promoter location based on DNA structure first-principles calculations
Goñi, J. R., Pérez, A., Torrents, D., & Orozco, M. (2007) · Genome biology · doi:10.1186/gb-2007-8-12-r263 · Cited by 145 · see citing works
DNA physical properties determine nucleosome occupancy from yeast to fly
Mièle, V., Vaillant, C., d’Aubenton-Carafa, Y., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn262 · Cited by 137 · see citing works
Predicting Human Nucleosome Occupancy from Primary Sequence
Gupta, S., Dennis, J. H., Thurman, R. E., et al. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000134 · Cited by 134 · see citing works
Wan, S., Mak, M., & Kung, S. (2013) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2013.01.012 · Cited by 126 · see citing works
Liu, B., Wang, X., Zou, Q., Dong, Q., & Chen, Q. (2013) · Molecular Informatics · doi:10.1002/minf.201300084 · Cited by 118 · see citing works
Mei, S. (2012) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2012.06.028 · Cited by 113 · see citing works
Beigi, M. M., Behjati, M., & Mohabatkar, H. (2011) · Journal of Structural and Functional Genomics · doi:10.1007/s10969-011-9120-4 · Cited by 113 · see citing works
Predicting Membrane Protein Types by the LLDA Algorithm
Wang, T., Yang, J., Shen, H., & Chou, K. (2008) · Protein and Peptide Letters · doi:10.2174/092986608785849308 · Cited by 108 · see citing works
Self-citationPrediction of Golgi-resident protein types by using feature selection technique
Ding, H., Guo, S.-H., Deng, E.-Z., et al. (2013) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2013.03.005 · Cited by 101 · see citing works
Self-citationNucleosome Structural Features and Intrinsic Properties of the TATAAACGCC Repeat Sequence
Widlund, H. R., Kuduvalli, P. N., Bengtsson, M., et al. (1999) · Journal of Biological Chemistry · doi:10.1074/jbc.274.45.31847 · Cited by 81 · see citing works
The organization of nucleosomes around splice sites
Chen, W., Luo, L., & Zhang, L. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq007 · Cited by 74 · see citing works
Self-citationGupta, M. K., Niyogi, R., & Misra, M. (2013) · SAR and QSAR in environmental research · doi:10.1080/1062936x.2013.773378 · Cited by 67 · see citing works
Athey, B. D., Smith, M. F., Rankert, D. A., et al. (1990) · The Journal of Cell Biology · doi:10.1083/jcb.111.3.795 · Cited by 65 · see citing works
Yasuda, T., Sugasawa, K., Shimizu, Y., Iwai, S., Shiomi, T., & Hanaoka, F. (2004) · DNA repair · doi:10.1016/j.dnarep.2004.10.008 · Cited by 61 · see citing works
Prediction of replication origins by calculating DNA structural properties
Chen, W., Feng, P., & Lin, H. (2012) · FEBS Letters · doi:10.1016/j.febslet.2012.02.034 · Cited by 55 · see citing works
Self-citationDNAlive: a tool for the physical analysis of DNA at the genomic scale
Goni, J., Fenollosa, C., Pérez, A., et al. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn259 · Cited by 30 · see citing works
Analysis of nucleosome positioning determined by DNA helix curvature in the human genome
Liu, H., Duan, X., Yu, S., et al. (2011) · BMC Genomics · doi:10.1186/1471-2164-12-72 · Cited by 22 · see citing works
Xing, Y., Zhao, X., & Cai, L. (2011) · Genomics · doi:10.1016/j.ygeno.2011.07.008 · Cited by 22 · see citing works
Zhao, X., Pei, Z., Liu, J., et al. (2010) · Chromosome Research · doi:10.1007/s10577-010-9160-9 · Cited by 21 · see citing works
Fondufe‐Mittendorf, Y. N., Chen, L., Field, Y., & Moore, I. K. (2006) · Cited by 20 · see citing works
Role of 10–11bp periodicities of eukaryotic DNA sequence in nucleosome positioning
Liu, H., Lin, S., Cai, Z., & Sun, X. S. (2011) · Biosystems · doi:10.1016/j.biosystems.2011.05.016 · Cited by 8 · see citing works
An analysis and prediction of nucleosome positioning based on information content
Xing, Y., Liu, G., Zhao, X., et al. (2013) · Chromosome Research · doi:10.1007/s10577-013-9338-z · Cited by 8 · see citing works
Predicting Nucleosome Positions in Yeast: Using the Absolute Frequency
Zhang, Z., Zhang, Y., & Gutman, İ. (2012) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/073911012010525032 · Cited by 5 · see citing works
Computational analysis suggests a highly bendable, fragile structure for nucleosomal DNA
Nozaki, T., Yachie, N., Ogawa, R., Saito, R., & Tomita, M. (2011) · Gene · doi:10.1016/j.gene.2011.02.004 · Cited by 4 · see citing works
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Self-citation
- Authors
- Guo, S.-H., Deng, E.-Z., Xu, L.-Q., Ding, H., Lin, H., Chen, W., & Chou, K.-C.
- Affiliations
- University of Electronic Science and Technology of China (CN)
- 1 Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China, 2Gordon Life Science Institute, Belmont, Massachusetts, USA, 3Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China and 4Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia
- Corresponding author
- Lin, Hao
- Chen, Wei
- Chou, Kuo-Chen
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-02-06
- Volume
- 30
- Issue
- 11
- Pages
- 1522-1529
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2139166279
- Cited by
- 375
- References
- 80
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 17 · 2023: 8 · 2022: 12 · 2021: 20 · 2020: 20 · 2019: 32 · 2018: 53 · 2017: 33 · 2016: 57 · 2015: 65 · 2014: 51
- FWCI
- 28.14
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Bioinformatics (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
- Keywords
- nucleosome positioning, sequence-based prediction, Caenorhabditis elegans genome, Drosophila melanogaster genome, web server
- MeSH terms
- Animals, DNA, Drosophila melanogaster, Humans, Nucleosomes, Nucleotides, Software, Genome, Caenorhabditis elegans, Sequence Analysis, DNA, Genomics
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