Using functional domain composition and support vector machines for prediction of protein subcellular location
Open accessAbstract
Proteins are generally classified into the following 12 subcellular locations: 1) chloroplast, 2) cytoplasm, 3) cytoskeleton, 4) endoplasmic reticulum, 5) extracellular, 6) Golgi apparatus, 7) lysosome, 8) mitochondria, 9) nucleus, 10) peroxisome, 11) plasma membrane, and 12) vacuole. Because the function of a protein is closely correlated with its subcellular location, with the rapid increase in new protein sequences entering into databanks, it is vitally important for both basic research and pharmaceutical industry to establish a high throughput tool for predicting protein subcellular location. In this paper, a new concept, the so-called "functional domain composition" is introduced. Based on the novel concept, the representation for a protein can be defined as a vector in a high-dimensional space, where each of the clustered functional domains derived from the protein universe serves as a vector base. With such a novel representation for a protein, the support vector machine (SVM) algorithm is introduced for predicting protein subcellular location. High success rates are obtained by the self-consistency test, jackknife test, and independent dataset test, respectively. The current approach not only can play an important complementary role to the powerful covariant discriminant algorithm based on the pseudo amino acid composition representation (Chou, K. C. (2001) Proteins Struct. Funct. Genet. 43, 246-255; Correction (2001) Proteins Struct. Funct. Genet. 44, 60), but also may greatly stimulate the development of this area.
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The principles of SVM were introduced in Chou and Cai, and more details are provided in Cristianini.
“The principles of SVM were introduced in Chou and Cai [60,61], and more details are provided in Cristianini [62].”
From An Efficient Classifier for Alzheimer’s Disease Genes Identification (2018) · cites this paper as [60]
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Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669 · see citing works
Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421 · see citing works
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138 · see citing works
Cortes, C., & Vapnik, V. N. (1995) · Machine Learning · doi:10.1023/a:1022627411411 · Cited by 34,565 · see citing works
Wu, Y., & Vapnik, V. N. (1999) · Technometrics · doi:10.2307/1271368 · Cited by 27,236 · see citing works
Advances in kernel methods: support vector learning
Schölkopf, B., Burges, C. J. C., & Smola, A. J. (1999) · doi:10.5555/299094 · Cited by 5,809 · see citing works
The Nature of Statistical Learning Theory
Sain, S. R., & Vapnik, V. N. (1996) · Technometrics · doi:10.2307/1271324 · Cited by 4,097 · see citing works
The SWISS-PROT protein sequence data bank and its supplement TrEMBL
Bairoch, A., & Apweiler, R. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.1.31 · Cited by 3,594 · 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-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-citationMulti-class protein fold recognition using support vector machines and neural networks
Ding, C. H. Q., & Dubchak, I. L. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.4.349 · Cited by 845 · see citing works
Prediction of Protein Structure and the Principles of Protein Conformation
Fasman, G. D. (1989) · Springer eBooks · doi:10.1007/978-1-4613-1571-1 · Cited by 820 · see citing works
Mammone, A., Turchi, M., & Cristianini, N. (2009) · Wiley Interdisciplinary Reviews Computational Statistics · doi:10.1002/wics.49 · Cited by 711 · see citing works
Using neural networks for prediction of the subcellular location of proteins
Reinhardt, A. (1998) · Nucleic Acids Research · doi:10.1093/nar/26.9.2230 · Cited by 597 · see citing works
A duality theorem for non-linear programming
Wolfe, P. (1961) · Quarterly of Applied Mathematics · doi:10.1090/qam/135625 · Cited by 593 · see citing works
Hua, S., & Sun, Z. (2001) · Journal of Molecular Biology · doi:10.1006/jmbi.2001.4580 · Cited by 533 · see citing works
Predicting protein–protein interactions from primary structure
Bock, J. R., & Gough, D. A. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.5.455 · Cited by 531 · see citing works
The Folding Type of a Protein Is Relevant to the Amino Acid Composition
Nakashima, H., Nishikawa, K., & Ooi, T. (1986) · The Journal of Biochemistry · doi:10.1093/oxfordjournals.jbchem.a135454 · Cited by 460 · see citing works
A novel approach to predicting protein structural classes in a (20–1)‐D amino acid composition space
Chou, K. (1995) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340210406 · Cited by 428 · see citing works
Self-citationNakashima, H., & Nishikawa, K. (1994) · Journal of Molecular Biology · doi:10.1006/jmbi.1994.1267 · Cited by 419 · see citing works
Relation between amino acid composition and cellular location of proteins 1 1Edited by F. E. Cohen
Cedano, J. A., Aloy, P., Perez-Pons, J. A., & Querol, E. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0804 · Cited by 397 · see citing works
Protein subcellular location prediction
Chou, K., & Elrod, D. W. (1999) · Protein Engineering Design and Selection · doi:10.1093/protein/12.2.107 · Cited by 375 · see citing works
Self-citationPrediction of Protein Subcellular Locations by Incorporating Quasi-Sequence-Order Effect
Chou, K. (2000) · Biochemical and Biophysical Research Communications · doi:10.1006/bbrc.2000.3815 · Cited by 361 · see citing works
Self-citationAn Intriguing Controversy over Protein Structural Class Prediction
Zhou, G. (1998) · Journal of Protein Chemistry · doi:10.1023/a:1020713915365 · Cited by 344 · see citing works
(1894) · Journal of Education · doi:10.1177/002205749404000313 · Cited by 318 · see citing works
Prediction of protein structure and principles of protein conformation
Lu, P. (1990) · Cell · doi:10.1016/0092-8674(90)90466-r · Cited by 278 · see citing works
Some insights into protein structural class prediction
Zhou, G., & Assa‐Munt, N. (2001) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.1071 · Cited by 270 · see citing works
Venables, W. N., & Ripley, B. D. (1997) · Statisctics and computing/Statistics and computing · doi:10.1007/978-1-4757-2719-7_13 · Cited by 235 · see citing works
Chou, K., & Zhang, C. T. (1994) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(17)31748-9 · Cited by 212 · see citing works
Self-citationA 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-citationPrediction of Protein Structural Classes from Amino Acid Compositions
Chou, P. Y. (1989) · Springer eBooks · doi:10.1007/978-1-4613-1571-1_12 · Cited by 176 · see citing works
Prediction of Protein Structural Classes and Subcellular Locations
Chou, K. (2000) · Current Protein and Peptide Science · doi:10.2174/1389203003381379 · Cited by 155 · see citing works
Self-citationCai, Y., Liu, X., Xu, X.-B., & Chou, K. (2001) · Journal of Cellular Biochemistry · doi:10.1002/jcb.10030 · Cited by 111 · see citing works
Self-citationUsing Discriminant Function for Prediction of Subcellular Location of Prokaryotic Proteins
Chou, K., & Elrod, D. W. (1998) · Biochemical and Biophysical Research Communications · doi:10.1006/bbrc.1998.9498 · Cited by 90 · see citing works
Self-citationTertiary and quaternary conformational changes in aspartate transcarbamylase: a normal mode study
Thomas, A. M., Hinsen, K., Field, M. J., & Pérahia, D. (1999) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(19990101)34:1 · Cited by 64 · see citing works
Prediction of Protein Structural Classes by Modified Mahalanobis Discriminant Algorithm
Liu, W., & Chou, K. (1998) · Journal of Protein Chemistry · doi:10.1023/a:1022576400291 · Cited by 57 · see citing works
Self-citationSupport Vector Machines for Prediction of Protein Subcellular Location
Cai, Y., Liu, X., Xu, X.-B., & Chou, K. (2000) · Molecular Cell Biology Research Communications · doi:10.1006/mcbr.2001.0285 · Cited by 45 · see citing works
Self-citationIs it a paradox or misinterpretation?
Cai, Y. (2001) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.1045 · Cited by 42 · see citing works
Self-citationUsing Neural Networks for Prediction of Subcellular Location of Prokaryotic and Eukaryotic Proteins
Cai, Y., & Chou, K. (2000) · Molecular Cell Biology Research Communications · doi:10.1006/mcbr.2001.0269 · Cited by 36 · see citing works
Self-citationAlberti, S. (1998) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(19980401)31:1 · Cited by 29 · see citing works
The SBASE protein domain library, release 8.0: a collection of annotated protein sequence segments
Murvai, J. (2001) · Nucleic Acids Research · doi:10.1093/nar/29.1.58 · Cited by 19 · see citing works
Žižka, J., Dařena, F., & Svoboda, A. (2019) · CRC Press eBooks · doi:10.1201/9780429469275-10 · Cited by 7 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Chou, P. Y. (1980) Abstracts of Papers, Part I, Second Chemical Congress of the North American Continent, Las Vegas, May 1, 1980, Plenum Press, New York
Cited by
Sorted by citations
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-citationChou, K., & Shen, H. (2010) · PLoS ONE · doi:10.1371/journal.pone.0011335 · Cited by 1,166 · see citing works
Self-citationYu, C., Lin, C., & Hwang, J. (2004) · Protein Science · doi:10.1110/ps.03479604 · Cited by 917 · 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-citationiRSpot-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-citationLin, H., Deng, E.-Z., Ding, H., Chen, W., & Chou, K.-C. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1019 · Cited by 508 · 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-citationREVIEW : Recent advances in developing web-servers for predicting protein attributes
Chou, K., & Shen, H. (2009) · Natural Science · doi:10.4236/ns.2009.12011 · Cited by 463 · see citing works
Self-citationChou, K., & Shen, H. (2007) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2007.06.027 · Cited by 434 · see citing works
Self-citationiACP: a sequence-based tool for identifying anticancer peptides
Chen, W., Ding, H., Feng, P., Lin, H., & Chou, K. (2016) · Oncotarget · doi:10.18632/oncotarget.7815 · Cited by 434 · see citing works
Self-citationChou, K., & Shen, H. (2010) · PLoS ONE · doi:10.1371/journal.pone.0009931 · Cited by 395 · see citing works
Self-citationGuo, S.-H., Deng, E.-Z., Xu, L.-Q., Ding, H., Lin, H., Chen, W., & Chou, K.-C. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu083 · Cited by 375 · see citing works
Self-citationLiu, B., Fang, L., Long, R., Lan, X., & Chou, K. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv604 · Cited by 364 · see citing works
Self-citationRao, H., Zhu, F., Yang, G. B., Li, Z., & Chen, Y. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr284 · Cited by 359 · see citing works
Classification of Nuclear Receptors Based on Amino Acid Composition and Dipeptide Composition*
Bhasin, M., & Raghava, G. P. S. (2004) · Journal of Biological Chemistry · doi:10.1074/jbc.m401932200 · Cited by 551 · see citing works
iRNA-Methyl: Identifying N6-methyladenosine sites using pseudo nucleotide composition
Chen, W., Feng, P., Ding, H., Lin, H., & Chou, K. (2015) · Analytical Biochemistry · doi:10.1016/j.ab.2015.08.021 · Cited by 350 · see citing works
Self-citationChou, K., & Shen, H. (2010) · Natural Science · doi:10.4236/ns.2010.210136 · Cited by 348 · see citing works
Self-citationChou, K., Wu, Z., & Xiao, X. (2011) · Molecular BioSystems · doi:10.1039/c1mb05420a · Cited by 334 · see citing works
Self-citationHöglund, A., Dönnes, P., Blum, T., Adolph, H., & Kohlbacher, O. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl002 · Cited by 325 · see citing works
Chou, K., Wu, Z., & Xiao, X. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018258 · Cited by 319 · see citing works
Self-citationOn the pH‐optimum of activity and stability of proteins
Talley, K., & Alexov, E. G. (2010) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22786 · Cited by 316 · see citing works
YLoc—an interpretable web server for predicting subcellular localization
Briesemeister, S., hrer, J. ⁄. R. R. ⁄., & Kohlbacher, O. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq477 · Cited by 315 · see citing works
Zhou, X., Chen, C., Li, Z., & Zou, X. (2007) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2007.06.001 · Cited by 314 · see citing works
Liu, B., Xu, J., Lan, X., Xu, R., Zhou, J., Wang, X., & Chou, K. (2014) · PLoS ONE · doi:10.1371/journal.pone.0106691 · Cited by 306 · see citing works
Self-citationFeng, P., Yang, H. Q., Ding, H., Lin, H., Chen, W., & Chou, K. (2018) · Genomics · doi:10.1016/j.ygeno.2018.01.005 · Cited by 306 · see citing works
Self-citationBlum, T., Briesemeister, S., & Kohlbacher, O. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-274 · Cited by 305 · see citing works
Feng, P., Chen, W., Lin, H., & Chou, K. (2013) · Analytical Biochemistry · doi:10.1016/j.ab.2013.05.024 · Cited by 294 · see citing works
Self-citationSu, Z.-D., Huang, Y., Zhang, Z., Zhao, Y.-W., Wang, D., Chen, W., Chou, K., & Lin, H. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty508 · Cited by 294 · see citing works
Self-citationiRNA-PseU: Identifying RNA pseudouridine sites
Chen, W., Tang, H., Ye, J., Lin, H., & Chou, K.-C. (2016) · Molecular Therapy - Nucleic Acids · doi:10.1038/mtna.2016.37 · Cited by 291 · see citing works
Self-citationFeng, P., Ding, H., Yang, H. Q., Chen, W., Lin, H., & Chou, K. (2017) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2017.03.006 · Cited by 288 · see citing works
Self-citationPredicting Drug-Target Interaction Networks Based on Functional Groups and Biological Features
He, Z., Zhang, J., Shi, X., Hu, L., Kong, X., Cai, Y., & Chou, K. (2010) · PLoS ONE · doi:10.1371/journal.pone.0009603 · Cited by 287 · see citing works
Self-citationEzyPred: A top–down approach for predicting enzyme functional classes and subclasses
Shen, H., & Chou, K. (2007) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2007.09.098 · Cited by 269 · see citing works
Self-citationpRNAm-PC: Predicting N6-methyladenosine sites in RNA sequences via physical–chemical properties
Liu, Z., Xiao, X., Yu, D., Jia, J., Qiu, W., & Chou, K. (2015) · Analytical Biochemistry · doi:10.1016/j.ab.2015.12.017 · Cited by 257 · see citing works
Self-citationChen, W., Feng, P., Deng, E.-Z., Lin, H., & Chou, K. (2014) · Analytical Biochemistry · doi:10.1016/j.ab.2014.06.022 · 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-citationiDNA-Methyl: Identifying DNA methylation sites via pseudo trinucleotide composition
Liu, Z., Xiao, X., Qiu, W., & Chou, K. (2015) · Analytical Biochemistry · doi:10.1016/j.ab.2014.12.009 · Cited by 252 · see citing works
Self-citationDehzangi, A., Heffernan, R., Sharma, A. K., Lyons, J., Paliwal, K. K., & Sattar, A. (2014) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2014.09.029 · Cited by 240 · see citing works
Identification of Real MicroRNA Precursors with a Pseudo Structure Status Composition Approach
Liu, B., Fang, L., Liu, F., Wang, X., Chen, J., & Chou, K.-C. (2015) · PLOS ONE · doi:10.1371/journal.pone.0121501 · Cited by 238 · see citing works
Self-citationPrediction of protein subcellular locations using fuzzy k-NN method
Huang, Y., & Li, Y. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg366 · Cited by 238 · see citing works
2L-piRNA: A Two-Layer Ensemble Classifier for Identifying Piwi-Interacting RNAs and Their Function
Liu, B., Yang, F., & Chou, K. (2017) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2017.04.008 · Cited by 238 · see citing works
Self-citationQiu, W., Xiao, X., & Chou, K. (2014) · International Journal of Molecular Sciences · doi:10.3390/ijms15021746 · Cited by 236 · see citing works
Self-citationGarg, A., Bhasin, M., & Raghava, G. P. S. (2005) · Journal of Biological Chemistry · doi:10.1074/jbc.m411789200 · Cited by 232 · see citing works
iRNA-AI: identifying the adenosine to inosine editing sites in RNA sequences
Chen, W., Feng, P., Yang, H. Q., Ding, H., Lin, H., & Chou, K. (2016) · Oncotarget · doi:10.18632/oncotarget.13758 · Cited by 229 · see citing works
Self-citationDing, H., Deng, E.-Z., Yuan, L., Liu, L., Lin, H., Chen, W., & Chou, K. (2014) · BioMed Research International · doi:10.1155/2014/286419 · Cited by 225 · see citing works
Self-citationLarge‐scale plant protein subcellular location prediction
Chou, K., & Shen, H. (2006) · Journal of Cellular Biochemistry · doi:10.1002/jcb.21096 · Cited by 221 · see citing works
Self-citationArrangements in the modular evolution of proteins
Moore, A. D., Björklund, Å. K., Ekman, D. S., Bornberg‐Bauer, E., & Elofsson, A. (2008) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2008.05.008 · Cited by 219 · see citing works
Xiao, X., Min, J., Lin, W., Liu, Z., Cheng, X., & Chou, K. (2014) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2014.998710 · Cited by 218 · see citing works
Self-citationiEnhancer-EL: identifying enhancers and their strength with ensemble learning approach
Liu, B., Li, K., Huang, D.-S., & Chou, K. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty458 · Cited by 215 · see citing works
Self-citationXiao, X., Shao, S., Ding, Y., Huang, Z., & Chou, K. (2005) · Amino Acids · doi:10.1007/s00726-005-0225-6 · Cited by 210 · see citing works
Self-citationMachine learning techniques in disease forecasting: a case study on rice blast prediction
Kaundal, R., Kapoor, A. S., & Raghava, G. P. S. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-485 · Cited by 203 · see citing works
Using LogitBoost classifier to predict protein structural classes
Cai, Y., Feng, K., Lu, W., & Chou, K. (2005) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2005.05.034 · Cited by 202 · see citing works
Self-citationZeng, Y. H., Guo, Y., Xiao, R.-Q., Yang, L., Yu, L., & Li, M. (2009) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2009.03.028 · Cited by 201 · see citing works
Zhicheng, W., Xiao, X., & Chou, K. (2011) · Molecular BioSystems · doi:10.1039/c1mb05232b · Cited by 198 · see citing works
Self-citationQiu, W., Xiao, X., Lin, W., & Chou, K. (2014) · BioMed Research International · doi:10.1155/2014/947416 · Cited by 194 · see citing works
Self-citationSearching for hypothetical proteins: Theory and practice based upon original data and literature
Lübec, G., Afjehi‐Sadat, L., Yang, J., & John, J. P. P. (2005) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2005.10.001 · Cited by 193 · see citing works
Wang, M., Yang, J., Liu, G.-P., Xu, Z., & Chou, K.-C. (2004) · Protein Engineering Design and Selection · doi:10.1093/protein/gzh061 · Cited by 186 · see citing works
Self-citationChen, Y., & Li, Q. (2007) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2007.05.019 · Cited by 185 · see citing works
Shen, H., & Chou, K. (2005) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2005.06.087 · Cited by 180 · see citing works
Self-citationIdentifying Sigma70 Promoters with Novel Pseudo Nucleotide Composition
Lin, H., Liang, Z.-Y., Tang, H., & Chen, W. (2017) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2017.2666141 · Cited by 180 · see citing works
Wei, L., Chen, H., & Su, R. (2018) · Molecular Therapy Nucleic Acids · doi:10.1016/j.omtn.2018.07.004 · Cited by 179 · see citing works
Prediction of protein subcellular locations by GO–FunD–PseAA predictor
Chou, K., & Cai, Y. (2004) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2004.06.073 · Cited by 179 · see citing works
Self-citationNanni, 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
Fang, Y., Guo, Y., Feng, Y., & Li, M. (2007) · Amino Acids · doi:10.1007/s00726-007-0568-2 · Cited by 175 · see citing works
Fuzzy KNN for predicting membrane protein types from pseudo-amino acid composition
Shen, H., Yang, J., & Chou, K. (2005) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2005.08.016 · Cited by 174 · see citing works
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Chou, K., & Cai, Y. (2003) · Journal of Cellular Biochemistry · doi:10.1002/jcb.10719 · Cited by 173 · see citing works
Self-citationNanni, L., & Lumini, A. (2008) · Amino Acids · doi:10.1007/s00726-007-0018-1 · Cited by 172 · see citing works
Shen, H., & Chou, K. (2009) · Analytical Biochemistry · doi:10.1016/j.ab.2009.07.046 · Cited by 170 · see citing works
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Cheng, X., Xiao, X., & Chou, K. (2017) · Genomics · doi:10.1016/j.ygeno.2017.10.002 · Cited by 164 · see citing works
Self-citationChou, K., & Shen, H. (2008) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2008.08.125 · Cited by 162 · see citing works
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Self-citationMatsuda, S., Vert, J., Saigo, H., Ueda, N., Toh, H., & Akutsu, T. (2005) · Protein Science · doi:10.1110/ps.051597405 · Cited by 161 · see citing works
Zhang, T.-L., Ding, Y., & Chou, K. (2007) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2007.09.014 · Cited by 160 · see citing works
Self-citationCheng, X., Xiao, X., & Chou, K. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx711 · Cited by 159 · see citing works
Self-citationHayat, M., & Khan, A. (2010) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2010.11.017 · Cited by 157 · see citing works
Shen, Y., Tang, J., & Guo, F. (2018) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2018.11.012 · Cited by 156 · see citing works
Shen, H., & Chou, K. (2005) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2005.09.117 · Cited by 152 · see citing works
Self-citationPredicting Protein−Protein Interactions from Sequences in a Hybridization Space
Chou, K., & Cai, Y. (2005) · Journal of Proteome Research · doi:10.1021/pr050331g · Cited by 152 · see citing works
Self-citationPredicting ion channels and their types by the dipeptide mode of pseudo amino acid composition
Lin, H., & Ding, H. (2010) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2010.10.019 · Cited by 151 · see citing works
Chen, C., Zhou, X., Tian, Y., Zou, X., & Cai, P. (2006) · Analytical Biochemistry · doi:10.1016/j.ab.2006.07.022 · Cited by 151 · see citing works
Prediction of the subcellular location of apoptosis proteins
Chen, Y., & Li, Q. (2006) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2006.11.010 · Cited by 151 · see citing works
Shen, H., & Chou, K. (2006) · Biopolymers · doi:10.1002/bip.20640 · Cited by 150 · see citing works
Self-citationLow-frequency Fourier spectrum for predicting membrane protein types
Liu, H., Wang, M., & Chou, K. (2005) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2005.08.160 · Cited by 150 · see citing works
Self-citationUsing supervised fuzzy clustering to predict protein structural classes
Shen, H., Yang, J., Liu, X.-J., & Chou, K. (2005) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2005.06.128 · Cited by 150 · see citing works
Self-citationEuk-PLoc: an ensemble classifier for large-scale eukaryotic protein subcellular location prediction
Shen, H., Yang, J., & Chou, K.-C. (2007) · Amino Acids · doi:10.1007/s00726-006-0478-8 · Cited by 149 · see citing works
Self-citationShen, H., & Chou, K. (2007) · Protein Engineering Design and Selection · doi:10.1093/protein/gzl053 · Cited by 149 · see citing works
Self-citationiMiRNA-PseDPC: microRNA precursor identification with a pseudo distance-pair composition approach
Liu, B., Fang, L., Liu, F., Wang, X., & Chou, K. (2015) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2015.1014422 · Cited by 148 · see citing works
Self-citationSLLE for predicting membrane protein types
Wang, M., Yang, J., Xu, Z., & Chou, K. (2004) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2004.07.023 · Cited by 147 · see citing works
Self-citationYang, H. Q., Qiu, W., Liu, G., Guo, F., Chen, W., Chou, K., & Lin, H. (2018) · International Journal of Biological Sciences · doi:10.7150/ijbs.24616 · Cited by 142 · see citing works
Self-citationA Review on the Recent Developments of Sequence-based Protein Feature Extraction Methods
Zhang, J., & Liu, B. (2018) · Current Bioinformatics · doi:10.2174/1574893614666181212102749 · Cited by 140 · see citing works
Pan, Y., Zhang, Z., Guo, Z., Feng, G., Huang, Z., & He, L. (2003) · Journal of Protein Chemistry · doi:10.1023/a:1025350409648 · Cited by 140 · see citing works
SherLoc2: A High-Accuracy Hybrid Method for Predicting Subcellular Localization of Proteins
Briesemeister, S., Blum, T., Brady, S., Lam, Y. P., Kohlbacher, O., & Shatkay, H. (2009) · Journal of Proteome Research · doi:10.1021/pr900665y · Cited by 138 · see citing works
Huang, K., & Murphy, R. F. (2004) · BMC Bioinformatics · doi:10.1186/1471-2105-5-78 · Cited by 137 · see citing works
Gao, Y., Shao, S., Xiao, X., Ding, Y., Huang, Y., Huang, Z., & Chou, K. (2005) · Amino Acids · doi:10.1007/s00726-005-0206-9 · Cited by 136 · see citing works
Self-citationA new hybrid approach to predict subcellular localization of proteins by incorporating gene ontology
Chou, K., & Cai, Y. (2003) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2003.10.062 · Cited by 135 · see citing works
Self-citationZhang, S., Zhang, Y., Yang, H.-F., Zhao, C.-H., & Pan, Q. (2007) · Amino Acids · doi:10.1007/s00726-007-0010-9 · Cited by 135 · see citing works
- Authors
- Chou, K.-C., & Cai, Y.-D.
- Affiliations
- Chinese Academy of Sciences (CN)
- Corresponding author
- Cai, Yu-Dong
- ORCID
- Cai, Yu-Dong
- Venue
- Journal of Biological Chemistry
- Publisher
- Elsevier BV
- Published
- 2002-11
- Volume
- 277
- Issue
- 48
- Pages
- 45765-45769
- ISSN
- 0021-9258 (ISSN-L)
- OpenAlex
- W1992577925
- Cited by
- 483
- References
- 41
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 3 · 2022: 9 · 2021: 7 · 2020: 11 · 2019: 18 · 2018: 27 · 2017: 16 · 2016: 20 · 2015: 17 · 2014: 22 · 2013: 23 · 2012: 32
- FWCI
- 7.65
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Biological Chemistry (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 › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
- Keywords
- support vector machine, protein function prediction, protein sequence representation, pseudo amino acid composition, jackknife test, high-dimensional feature vectors
- MeSH terms
- Proteins, Subcellular Fractions
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