[1]
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Chou, K.C. (2011) Some Remarks on Protein Attribute Prediction and Pseudo Amino Acid Composition (50th Anniversary Year Review, 5-Steps Rule). Journal of Theoretical Biology, 273, 236-247.
https://doi.org/10.1016/j.jtbi.2010.12.024
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[2]
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Butt, A.H. and Khan, Y.D. (2018) Prediction of S-Sulfenylation Sites Using Statistical Moments Based Features via Chou’s 5-Step Rule. International Journal of Peptide Research and Therapeutics.
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[3]
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Awais, M., Hussain, W., Khan, Y.D., Rasool, N., Khan, S.A. and Chou, K.C. (2019) iPhosH-PseAAC: Identify Phosphohistidine Sites in Proteins by Blending Statistical Moments and Position Relative Features According to the Chou’s 5-Step Rule and General Pseudo Amino Acid Composition. IEEE/ACM Transactions on Computational Biology and Bioinformatics. https://www.ncbi.nlm.nih.gov/pubmed/31144645
https://doi.org/10.1109/TCBB.2019.2919025
|
[4]
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Barukab, O., Khan, Y.D., Khan, S.A. and Chou, K.C. (2019) iSulfoTyr-PseAAC: Identify Tyrosine Sulfation Sites by Incorporating Statistical Moments via Chou’s 5-Steps Rule and Pseudo Components. Current Genomics, 20, 306-320. http://www.eurekaselect.com/174277/article
|
[5]
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Butt, A.H. and Khan, Y.D. (2018) Prediction of S-Sulfenylation Sites Using Statistical Moments Based Features via Chou’s 5-Step Rule. International Journal of Peptide Research and Therapeutics.
|
[6]
|
Du, X., Diao, Y., Liu, H. and Li, S. (2019) MsDBP: Exploring DNA-Binding Proteins by Integrating Multi-Scale Sequence Information via Chou’s 5-Steps Rule. Journal of Proteome Research, 18, 3119-3132.
https://doi.org/10.1021/acs.jproteome.9b00226
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[7]
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Chen, Y. and Fan, X. (2019) Use Chou’s 5-Steps Rule to Reveal Active Compound and Mechanism of Shuangsheng Pingfei San on Idiopathic Pulmonary Fibrosis. Current Molecular Medicine, 20, 220-230.
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[8]
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Dutta, A., Dalmia, A., R, A., Singh, K.K. and Anand, A. (2019) Using the Chou’s 5-Steps Rule to Predict Splice Junctions with Interpretable Bidirectional Long Short-Term Memory Networks. Computers in Biology and Medicine, 116, Article ID: 103558. https://doi.org/10.1016/j.compbiomed.2019.103558
|
[9]
|
Ehsan, A., Mahmood, M.K., Khan, Y.D., Barukab, O.M., Khan, S.A. and Chou, K.C. (2019) iHyd-PseAAC (EPSV): Identify Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant Feature via Chou’s 5-Step Rule and General Pseudo Amino Acid Composition. Current Genomics, 20, 124-133.
https://doi.org/10.2174/1389202920666190325162307
|
[10]
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Hussain, W., Khan, S.D., Rasool, N., Khan, S.A. and Chou, K.C. (2019) SPalmitoylC-PseAAC: A Sequence-Based Model Developed via Chou’s 5-Steps Rule and General PseAAC for Identifying S-Palmitoylation Sites in Proteins. Analytical Biochemistry, 568, 14-23. https://doi.org/10.1016/j.ab.2018.12.019
|
[11]
|
Hussain, W., Khan, Y.D., Rasool, N., Khan, S.A. and Chou, K.C. (2019) SPrenylC-PseAAC: A Sequence-Based Model Developed via Chou’s 5-Steps Rule and General PseAAC for Identifying S-Prenylation Sites in Proteins. Journal of Theoretical Biology, 468, 1-11. https://doi.org/10.1016/j.jtbi.2019.02.007
|
[12]
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Khan, S., Khan, M., Iqbal, N., Hussain, T., Khan, S.A. and Chou, K.C. (2019) A Two-Level Computation Model Based on Deep Learning Algorithm for Identification of piRNA and Their Functions via Chou’s 5-Steps Rule. International Journal of Peptide Research and Therapeutics.
https://link.springer.com/article/10.1007%2Fs10989-019-09887-3
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[13]
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Khan, Z.U., Ali, F., Khan, I.A., Hussain, Y. and Pi, D. (2019) iRSpot-SPI: Deep Learning-Based Recombination Spots Prediction by Incorporating Secondary Sequence Information Coupled with Physio-Chemical Properties via Chou’s 5-Step Rule and Pseudo Components. Chemometrics and Intelligent Laboratory Systems (CHEMOLAB), 189, 169-180. https://doi.org/10.1016/j.chemolab.2019.05.003
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[14]
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Lan, J., Liu, J., Liao, C., Merkler, D.J., Han, Q. and Li, J. (2019) A Study for Therapeutic Treatment against Parkinson’s Disease via Chou’s 5-Steps Rule. Current Topics in Medicinal Chemistry, 19, 2318-2333.
http://www.eurekaselect.com/175887/article
|
[15]
|
Le, N.Q.K. (2019) iN6-methylat (5-Step): Identifying DNA N(6)-methyladenine Sites in Rice Genome Using Continuous Bag of Nucleobases via Chou’s 5-Step Rule. Molecular Genetics and Genomics: MGG, 294, 1173-1182. https://doi.org/10.1007/s00438-019-01570-y
|
[16]
|
Le, N.Q.K., Yapp, E.K.Y., Ho, Q.T., Nagasundaram, N., Ou, Y.Y. and Yeh, H.Y. (2019) iEnhancer-5Step: Identifying Enhancers Using Hidden Information of DNA Sequences via Chou’s 5-Step Rule and Word Embedding. Analytical Biochemistry, 571, 53-61. https://doi.org/10.1016/j.ab.2019.02.017
|
[17]
|
Le, N.Q.K., Yapp, E.K.Y., Ou, Y.Y. and Yeh, H.Y. (2019) iMotor-CNN: Identifying Molecular Functions of Cytoskeleton Motor Proteins Using 2D Convolutional Neural Network via Chou’s 5-Step Rule. Analytical Biochemistry, 575, 17-26. https://doi.org/10.1016/j.ab.2019.03.017
|
[18]
|
Liang, R., Xie, J., Zhang, C., Zhang, M., Huang, H., Huo, H., Cao, X. and Niu, B. (2019) Identifying Cancer Targets Based on Machine Learning Methods via Chou’s 5-Steps Rule and General Pseudo Components. Current Topics in Medical Chemistry, 19, 2301-2317. https://doi.org/10.2174/1568026619666191016155543
|
[19]
|
Liang, Y. and Zhang, S. (2019) Identifying DNase I Hypersensitive Sites Using Multi-Features Fusion and F-Score Features Selection via Chou’s 5-Steps Rule. Biophysical Chemistry, 253, Article ID: 106227.
https://doi.org/10.1016/j.bpc.2019.106227
|
[20]
|
Liu, Z., Dong, W., Jiang, W. and He, Z. (2019) csDMA: An Improved Bioinformatics Tool for Identifying DNA 6 mA Modifications via Chou’s 5-Step Rule. Scientific Reports, 9, Article No. 13109.
https://doi.org/10.1038/s41598-019-49430-4
|
[21]
|
Malebary, S.J., Rehman, M.S.U. and Khan, Y.D. (2019) iCrotoK-PseAAC: Identify Lysine Crotonylation Sites by Blending Position Relative Statistical Features According to the Chou’s 5-Step Rule. PLoS ONE, 14, e0223993.
https://doi.org/10.1371/journal.pone.0223993
|
[22]
|
Nazari, I., Tahir, M., Tayari, H. and Chong, K.T. (2019) iN6-Methyl (5-Step): Identifying RNA N6-methyladenosine Sites Using Deep Learning Mode via Chou’s 5-Step Rules and Chou’s General PseKNC. Chemometrics and Intelligent Laboratory Systems (CHEMOLAB), 193, Article ID: 103811.
https://doi.org/10.1016/j.chemolab.2019.103811
|
[23]
|
Ning, Q., Ma, Z. and Zhao, X. (2019) dForml(KNN)-PseAAC: Detecting Formylation Sites from Protein Sequences Using K-Nearest Neighbor Algorithm via Chou’s 5-Step Rule and Pseudo Components. Journal of Theoretical Biology, 470, 43-49. https://doi.org/10.1016/j.jtbi.2019.03.011
|
[24]
|
Tahir, M., Tayara, H. and Chong, K.T. (2019) iDNA6mA (5-Step Rule): Identification of DNA N6-methyladenine Sites in the Rice Genome by Intelligent Computational Model via Chou’s 5-Step Rule. CHEMOLAB, 189, 96-101. https://doi.org/10.1016/j.chemolab.2019.04.007
|
[25]
|
Wiktorowicz, A., Wit, A., Dziewierz, A., Rzeszutko, L., Dudek, D. and Kleczynski, P. (2019) Calcium Pattern Assessment in Patients with Severe Aortic Stenosis via the Chou’s 5-Steps Rule. Current Pharmaceutical Design, 25, 3769-3775.
|
[26]
|
Yang, L., Lv, Y., Wang, S., Zhang, Q., Pan, Y., Su, D., Lu, Q. and Zuo, Y. (2019) Identifying FL11 Subtype by Characterizing Tumor Immune Microenvironment in Prostate Adenocarcinoma via Chou’s 5-Steps Rule. Genomics, 112, 1500-1515.
|
[27]
|
Charoenkwan, P., Schaduangrat, N., Nantasenamat, C., Piacham, T. and Shoombuatong, W. (2020) iQSP: A Sequence-Based Tool for the Prediction and Analysis of Quorum Sensing Peptides via Chou’s 5-Steps Rule and Informative Physicochemical Properties. International Journal of Molecular Sciences, 21, 75.
https://doi.org/10.3390/ijms21010075
|
[28]
|
Dobosz, R., Mucko, J. and Gawinecki, R. (2020) Using Chou’s 5-Step Rule to Evaluate the Stability of Tautomers: Susceptibility of 2-[(Phenylimino)-methyl]-cyclohexane-1,3-diones to Tautomerization Based on the Calculated Gibbs Free Energies. Energies, 13, 183. https://doi.org/10.3390/en13010183
|
[29]
|
Ju, Z. and Wang, S.Y. (2020) Prediction of Lysine Formylation Sites Using the Composition of k-Spaced Amino Acid Pairs via Chou’s 5-Steps Rule and General Pseudo Components. Genomics, 112, 859-866.
https://doi.org/10.1016/j.ygeno.2019.05.027
|
[30]
|
Kabir, M., Ahmad, S., Iqbal, M. and Hayat, M. (2020) iNR-2L: A Two-Level Sequence-Based Predictor Developed via Chou’s 5-Steps Rule and General PseAAC for Identifying Nuclear Receptors and Their Families. Genomics, 112, 276-285. https://doi.org/10.1016/j.ygeno.2019.02.006
|
[31]
|
Khan, Y.D., Amin, N., Hussain, W., Rasool, N., Khan, S.A. and Chou, K.C. (2020) iProtease-PseAAC(2L): A Two-Layer Predictor for Identifying Proteases and Their Types Using Chou’s 5-Step-Rule and General PseAAC. Analytical Biochemistry, 588, Article ID: 113477. https://doi.org/10.1016/j.ab.2019.113477
|
[32]
|
Akbar, S., Rahman, A.U. and Hayat, M. (2020) cACP: Classifying Anticancer Peptides Using Discriminative Intelligent Model via Chou’s 5-Step Rules and General Pseudo Components. Chemometrics and Intelligent Laboratory (CHEMOLAB), 196, Article ID: 103912. https://doi.org/10.1016/j.chemolab.2019.103912
|
[33]
|
Vishnoi, S., Garg, P. and Arora, P. (2020) Physicochemical n-Grams Tool: A Tool for Protein Physicochemical Descriptor Generation via Chou’s 5-Step Rule. Chemical Biology & Drug Design, 95, 79-86.
https://doi.org/10.1111/cbdd.13617
|
[34]
|
Vundavilli, H., Datta, A., Sima, C., Hua, J., Lopes, R. and Bittner, M. (2020) Using Chou’s 5-Steps Rule to Model Feedback in Lung Cancer. IEEE Journal of Biomedical and Health Informatics. (In Press)
https://doi.org/10.1109/JBHI.2019.2958042
|
[35]
|
Chou, K.C. (2019) Advance in Predicting Subcellular Localization of Multi-Label Proteins and Its Implication for Developing Multi-Target Drugs. Current Medicinal Chemistry, 26, 4918-4943.
http://www.eurekaselect.com/172010/article
https://doi.org/10.2174/0929867326666190507082559
|
[36]
|
Chou, K.C. (2019) Two Kinds of Metrics for Computational Biology. Genomics.
https://www.sciencedirect.com/science/article/pii/S0888754319304604?via%3Dihub
|
[37]
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Chou, K.C. (2019) Proposing Pseudo Amino Acid Components Is an Important Milestone for Proteome and Genome Analyses. International Journal for Peptide Research and Therapeutics.
https://link.springer.com/article/10.1007%2Fs10989-019-09910-7
|
[38]
|
Chou, K.C. (2019) An Insightful Recollection for Predicting Protein Subcellular Locations in Multi-Label Systems. Genomics. https://www.sciencedirect.com/science/article/pii/S0888754319304604?via%3Dihub
|
[39]
|
Chou, K.C. (2019) Progresses in Predicting Post-Translational Modification. International Journal of Peptide Research and Therapeutics.
https://link.springer.com/article/10.1007%2Fs10989-019-09893-5
|
[40]
|
Chou, K.C. (2019) An Insightful Recollection Since the Distorted Key Theory Was Born about 23 Years Ago. Genomics. https://www.sciencedirect.com/science/article/pii/S0888754319305543?via%3Dihub
|
[41]
|
Chou, K.C. (2019) Artificial Intelligence (AI) Tools Constructed via the 5-Steps Rule for Predicting Post-Translational Modifications. Trends in Artificial Intelligence, 3, 60-74. https://doi.org/10.36959/643/304
|
[42]
|
Liu, B. (2018) BioSeq-Analysis: A Platform for DNA, RNA, and Protein Sequence Analysis Based on Machine Learning Approaches. Briefings in Bioinformatics, 20, 1280-1294.
|
[43]
|
Liu, B., Gao, X. and Zhang, H. (2019) BioSeq-Analysis2.0: An Updated Platform for Analyzing DNA, RNA and Protein Sequences at Sequence Level and Residue Level Based on Machine Learning Approaches. Nucleic Acids Research, 47, e127. https://doi.org/10.1093/nar/gkz740
|
[44]
|
Chou, K.C. (2019) Showcase to Illustrate How the Web-Server iDNA6mA-PseKNC Is Working. Journal of Pathology Research Reviews & Reports, 1, 1-15.
|
[45]
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Chou, K.C. (2019) The pLoc_bal-mPlant Is a Powerful Artificial Intelligence Tool for Predicting the Subcellular Localization of Plant Proteins Purely Based on Their Sequence Information. International Journal of Nutrition Sciences, 4, 1037.
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[46]
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Chou, K.C., Cheng, X. and Xiao, X. (2019) pLoc_bal-mEuk: Predict Subcellular Localization of Eukaryotic Proteins by General PseAAC and Quasi-Balancing Training Dataset. Medicinal Chemistry, 15, 472-485.
https://doi.org/10.2174/1573406415666181218102517
|
[47]
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Chou, K.C. (2019) Showcase to Illustrate How the Web-Server iNitro-Tyr Is Working. Glo J of Com Sci and Infor Tec., 2, 1-16.
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[48]
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Chou, K.C. (2019) The pLoc_bal-mAnimal Is a Powerful Artificial Intelligence Tool for Predicting the Subcellular Localization of Animal Proteins Based on Their Sequence Information Alone. Scientific Journal of Biometrics & Biostatistics, 2, 1-13.
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[49]
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Chou, K.C. (2020) Showcase to Illustrate How the Webserver pLoc_bal-mEuk Is Working. Biomedical Journal of Scientific & Technical Research.
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[50]
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Chou, K.C. (2020) The pLoc_bal-mGneg Predictor Is a Powerful Web-Server for Identifying the Subcellular Localization of Gram-Negative Bacterial Proteins Based on Their Sequences Information Alone. International Journal of Sciences, 9, 27-34. https://doi.org/10.18483/ijSci.2248
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[51]
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Chou, K.C. (2020) How the Artificial Intelligence tool iRNA-2methyl Is Working for RNA 2’-Omethylation Sites. Journal of Medical Care Research and Review, 3, 348-366.
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[52]
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Chou, K.C. (2020) Showcase to Illustrate How the Web-Server iKcr-PseEns Is Working. Journal of Medical Care Research and Review, 3, 331-347.
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[53]
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Chou, K.C. (2020) The pLoc_bal-mVirus Is a Powerful Artificial Intelligence Tool for Predicting the Subcellular Localization of Virus Proteins According to Their Sequence Information Alone. Journal of Genetics and Genomics, 4.
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[54]
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Chou, K.C. (2019) How the Artificial Intelligence Tool iSNO-PseAAC Is Working in Predicting the Cysteine S-Nitrosylation Sites in Proteins. Journal of Stem Cell Research and Medicine, 4, 1-9.
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[55]
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Chou, K.C. (2020) Showcase to Illustrate How the Web-Server iRNA-Methyl Is Working. Journal of Molecular Genetics, 3, 1-7.
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[56]
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Chou, K.C. (2020) How the Artificial Intelligence Tool iRNA-PseU Is Working in Predicting the RNA Pseudouridine Sites. Biomedical Journal of Scientific & Technical Research.
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