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 NS  Vol.12 No.9 , September 2020
The Significant and Profound Impacts of Chou’s 5-Steps Rule
Abstract: In this short review paper, the significant and profound impacts of the 5-steps rule have been briefly recalled with crystal clear convincingness.

The “5-Steps Rule” or “5-Step Rules” was originally proposed by Kuo-Chen Chou in 2011 [1], named by many scientists as “Chou’s 5-steps rule” or “Chou’s 5-step rules”.

According to this rule, to develop a practically more useful statistical prediction method or predictor for genome or proteome analysis, one should observe the following five guidelines. 1) Construct or select a valid benchmark dataset to train and test the predictor. 2) Formulate the biological sequence samples with an effective mathematical expression that can truly reflect their intrinsic correlation with the target to be predicted. 3) Introduce or develop a powerful algorithm (or engine) to operate the prediction. 4) Properly perform cross-validation tests to objectively evaluate the anticipated accuracy of the predictor. 5) Establish a user-friendly webserver for the predictor that is accessible to the public. Ever since then, the 5-steps rule has been used by many scientists in developing various predictors for proteome or genome analyses.

Papers presented for developing a new sequence-analyzing method or statistical predictor by observing the guidelines of Chou’s 5-strp rules have the following notable merits: 1) crystal clear in logic development, 2) completely transparent in operation, 3) easily to repeat the reported results by other investigators, 4) with high potential in stimulating other sequence-analyzing methods, and 5) very convenient to be used by the majority of experimental scientists.

Therefore, the impacts of the 5-step rules are both significantly and profoundly (see, e.g., [2-49].

Moreover, the Chou’s 5-steps rule has been further extended to materials science for developing powerful method of detecting perovskite materials with higher Curie temperature as well [50].

Cite this paper: Chou, K. (2020) The Significant and Profound Impacts of Chou’s 5-Steps Rule. Natural Science, 12, 633-637. doi: 10.4236/ns.2020.129048.
References

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[20]   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.
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[21]   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.
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[22]   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.
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[27]   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.
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[29]   Akmal, M.A., Hussain, W., Rasool, N., Khan, Y.D., Khan, S.A. and Chou, K.C. (2020) Using Chou’s 5-Steps Rule to Predict O-Linked Serine Glycosylation Sites by Blending Position Relative Features and Statistical Moment. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 1-12.
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[30]   Bouziane, H. and Chouarfia, A. (2020) Use of Chou’s 5-Steps Rule to Predict the Subcellular Localization of Gram-Negative and Gram-Positive Bacterial Proteins by Multi-Label Learning Based on Gene Ontology Annotation and Profile Alignment. Journal of Integrative Bioinformatics.
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[31]   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

[32]   Charoenkwan, P., Schaduangrat, N., Nantasenamat, C., Piacham, T. and Shoombuatong, W. (2020) Correction: Shoombuatong, W., et al. 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.
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[33]   Chen, Y. and Fan, X. (2020) Use of Chou’s 5-Steps Rule to Reveal Active Compound and Mechanism of Shuangshen Pingfei San on Idiopathic Pulmonary Fibrosis. Current Molecular Medicine, 20, 220-230.
https://doi.org/10.2174/1566524019666191011160543

[34]   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.
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[36]   Dutta, A., Dalmia, A., R, A., Singh, K.K. and Anand, A. (2020) 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

[37]   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

[38]   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.
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[39]   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.
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[40]   Lin, W., Xiao, X., Qiu, W. and Chou, K.C. (2020) Use Chou’s 5-Steps Rule to Predict Remote Homology Proteins by Merging Grey Incidence Analysis and Domain Similarity Analysis. Natural Science, 12, 181-198.
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[41]   Lu, W., Song, Z., Ding, Y., Wu, H., Cao, Y., Zhang, Y.L., et al. (2020) Use Chou’s 5-Step Rule to Predict DNA- Binding Proteins with Evolutionary Information. BioMed Research International, 2020, Article ID: 6984045.
https://doi.org/10.1155/2020/6984045

[42]   Nguyen, D., Ho-Quang, T., Nguyen Quoc Khanh, L., Dinh-Phan, V. and Ou, Y.Y. (2020) Use Chou’s 5-Steps Rule with Different Word Embedding Types to Boost Performance of Electron Transport Protein Prediction Model. IEEE/ACM Transactions on Computational Biology and Bioinformatics.
https://doi.org/10.1109/TCBB.2020.3010975

[43]   Pandey, R.P., Kumar, S., Ahmad, S., Vibhuti, A., Raj, V.S., Verma, A.K., Sharma, P. and Leal, E. (2020) Use Chou’s 5-Steps Rule to Evaluate Protective Efficacy Induced by Antigenic Proteins of Mycobacterium tuberculosis Encapsulated in Chitosan Nanoparticles. Life Sciences, 256, Article ID: 117961.
https://doi.org/10.1016/j.lfs.2020.117961

[44]   Roy, T. and Bhattacharjee, P. (2020) A LabVIEW-Based Real-Time Modeling Approach via Chou’s 5-Steps Rule for Detection of Abnormalities in Cancer Cells. Gene Reports, Article ID: 100788.
https://doi.org/10.1016/j.genrep.2020.100788

[45]   Song, C. and Yang, B. (2020) Use Chou’s 5-Step Rule to Classify Protein Modification Sites with Neural Network. Scientific Programming, 2020, Article ID: 8894633.
https://doi.org/10.1155/2020/8894633

[46]   Song, C. and Yang, B. (2020) Use Chou’s 5-Step Rule to Classify Protein Modification Sites with Neural Network. Scientific Programming, 2020, Article ID: 8894633.
https://doi.org/10.1155/2020/8894633

[47]   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

[48]   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, 21, 2430-2438.
https://doi.org/10.1109/JBHI.2019.2958042

[49]   Yang, L., Lv, Y., Wang, S., Zhang, Q., Pan, Y., Su, D., Lu, Q. and Zuo, Y. (2020) Identifying FL11 Subtype by Characterizing Tumor Immune Microenvironment in Prostate Adenocarcinoma via Chou’s 5-Steps Rule. Genomics, 112, 1500-1515.
https://doi.org/10.1016/j.ygeno.2019.08.021

[50]   Zhai, X., Chen, M. and Lu, W. (2018) Accelerated Search for Perovskite Materials with Higher Curie Temperature Based on the Machine Learning Methods. Computational Materials Science, 151, 41-48.
https://doi.org/10.1016/j.commatsci.2018.04.031

 
 
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