In this current minireview, the cradle of the “5-steps rule” or “5-step rules”, along with its essence and advances, has been recalled. Born in 2011, its impacts on molecular biology a re both substantial and rapid, fully indicating the “5-steps rule” is no double a remarkable and profound milestone in molecular biology.
Keywords5-Steps RuleCradleGlobal and Local MetricsMulti-Label SystemWeb-Server
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
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.
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
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
Butt, A.H. and Khan, Y.D. (2019) Prediction of S-Sulfenylation Sites Using Statistical Moments Based Features via Chou’s 5-Step Rule. International Journal of Peptide Research and Therapeutics.
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.
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
Dutta, A., Dalmia, 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
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
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
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
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
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, 189, 169-180. https://doi.org/10.1016/j.chemolab.2019.05.003
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
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
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
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
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 Medicinal Chemistry, 19, 2301-2317. https://doi.org/10.2174/1568026619666191016155543
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
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
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
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, 193, Article ID: 103811. https://doi.org/10.1016/j.chemolab.2019.103811
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
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
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.
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.
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
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
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
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
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
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
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
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. https://doi.org/10.1109/JBHI.2019.2958042
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
Chou, K.C. (2019) Two Kinds of Metrics for Computational Biology. Genomics. https://www.sciencedirect.com/science/article/pii/S0888754319304604?via%3Dihub
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
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
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
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
Chou, K.C. (2019) Artificial Intelligence (AI) Tools Constructed via the 5-Steps Rule for Predicting Post-Translational Modifications. Trends in Artificial Intelligence (TIA), 3, 60-74. https://doi.org/10.36959/643/304
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.
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
Chou, K.C. (2019) The Cradle of Gordon Life Science Institute and Its Development and Driving Force. Int J Biol Genetics, 1, 1-28.
Chou, K.C. (2019) Showcase to Illustrate How the Web-Server iDNA6mA-PseKNC Is Working. Journal of Pathology Research Reviews & Reports, 1, 1-15.
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.
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
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.
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.
Chou, K.C. (2020) Showcase to Illustrate How the webserver pLoc_bal-mEuk Is Working. Biomedical Journal of Scientific & Technical Research.
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. ijSci, 9, 27-34. https://doi.org/10.18483/ijSci.2248
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.
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.
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. J Gent & Genome, 4.
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.
Chou, K.C. (2020) Showcase to Illustrate How the Web-Server iRNA-Methyl Is Working. J Mol Genet, 3, 1-7.
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.
Chou, K.C. (2020) Showcase to Illustrate How the Web-Server iSNO-AAPair Is Working. J Gent & Genome, 4.
Chou, K.C. (2020) The pLoc_bal-mHum Is a Powerful Web-Serve for Predicting the Subcellular Localization of Human Proteins Purely Based on Their Sequence Information. Advances in Bioengineering and Biomedical Science Research, 3, 1-5.