Table of Contents Author Guidelines Submit a Manuscript
Computational and Mathematical Methods in Medicine
Volume 2013, Article ID 530696, 6 pages
http://dx.doi.org/10.1155/2013/530696
Research Article

Naïve Bayes Classifier with Feature Selection to Identify Phage Virion Proteins

1School of Public Health, Hebei United University, Tangshan 063000, China
2Key Laboratory for Neuroinformation of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
3Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China

Received 10 March 2013; Revised 16 April 2013; Accepted 28 April 2013

Academic Editor: Yanxin Huang

Copyright © 2013 Peng-Mian Feng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [39 citations]

The following is the list of published articles that have cited the current article.

  • Pengmian Feng, Wei Chen, and Hao Lin, “Prediction of CpG island methylation status by integrating DNA physiochemical properties,” Genomics, 2014. View at Publisher · View at Google Scholar
  • Bandana Kumari, Manish Kumar, Ravindra Kumar, and Sohni Jain, “Protein sub-nuclear localization prediction using SVM and Pfam domain information,” PLoS ONE, vol. 9, no. 6, 2014. View at Publisher · View at Google Scholar
  • Maqsood Hayat, and Nadeem Iqbal, “Discriminating Protein Structure Classes by Incorporating Pseudo Average Chemical Shift to Chou's General PseAAC and Support Vector Machine,” Computer Methods and Programs in Biomedicine, 2014. View at Publisher · View at Google Scholar
  • Sukanta Mondal, and Priyadarshini P. Pai, “Chou's pseudo amino acid composition improves sequence-based antifreeze protein prediction,” Journal of Theoretical Biology, 2014. View at Publisher · View at Google Scholar
  • L. C. B. Faria, A. S. L. Rocha, and R. Palazzo, “Transmission of intra-cellular genetic information: A system proposal,” Journal of Theoretical Biology, vol. 358, pp. 208–231, 2014. View at Publisher · View at Google Scholar
  • Ravindra Kumar, Abhishikha Srivastava, Bandana Kumari, and Manish Kumar, “Prediction of β-lactamase and its class by Chou’s pseudo-amino acid composition and support vector machine,” Journal of Theoretical Biology, 2014. View at Publisher · View at Google Scholar
  • Wei Chen, Peng-Mian Feng, Hao Lin, and Kuo-Chen Chou, “iSS-PseDNC: Identifying Splicing Sites Using Pseudo Dinucleotide Composition,” BioMed Research International, vol. 2014, pp. 1–12, 2014. View at Publisher · View at Google Scholar
  • Hui Ding, Peng-Mian Feng, Wei Chen, and Hao Lin, “Identification of bacteriophage virion proteins by the ANOVA feature selection and analysis,” Molecular Biosystems, vol. 10, no. 8, pp. 2229–2235, 2014. View at Publisher · View at Google Scholar
  • Pengmian Feng, Hao Lin, Wei Chen, and Yongchun Zuo, “Predicting the Types of J-Proteins Using Clustered Amino Acids,” BioMed Research International, vol. 2014, pp. 1–8, 2014. View at Publisher · View at Google Scholar
  • Bin Liu, Bingquan Liu, Fule Liu, and Xiaolong Wang, “Protein Binding Site Prediction by Combining Hidden Markov Support Vector Machine and Profile-Based Propensities,” The Scientific World Journal, vol. 2014, pp. 1–6, 2014. View at Publisher · View at Google Scholar
  • Lina Zhang, Chengjin Zhang, Rui Gao, and Runtao Yang, “An Ensemble Method to Distinguish Bacteriophage Virion from Non-Virion Proteins Based on Protein Sequence Characteristics,” International Journal Of Molecular Sciences, vol. 16, no. 9, pp. 21734–21758, 2015. View at Publisher · View at Google Scholar
  • Wei Chen, Hong Tran, Zhiyong Liang, Hao Lin, and Liqing Zhang, “Identification and analysis of the N6-methyladenosine in the Saccharomyces cerevisiae transcriptome,” Scientific Reports, vol. 5, 2015. View at Publisher · View at Google Scholar
  • Yong-E Feng, “Identify Secretory Protein of Malaria Parasite with Modified Quadratic Discriminant Algorithm and Amino Acid Composition,” Interdisciplinary Sciences: Computational Life Sciences, 2015. View at Publisher · View at Google Scholar
  • Karthikeyan, and Thangaraju, “Best first and greedy search based CFS- Naïve Bayes classification algorithms for hepatitis diagnosis,” Biosciences Biotechnology Research Asia, vol. 12, no. 1, pp. 983–990, 2015. View at Publisher · View at Google Scholar
  • Wuritu Yang, Jian Huang, Wei Chen, Hao Lin, Hui Ding, Hua Tang, and Peng-Mian Feng, “PHYPred: a tool for identifying bacteriophage enzymes and hydrolases,” Virologica Sinica, vol. 31, no. 4, pp. 350–352, 2016. View at Publisher · View at Google Scholar
  • Wei Chen, Hao Lin, and Pengmian Feng, “Identifying Antioxidant Proteins by Using Optimal Dipeptide Compositions,” Interdisciplinary Sciences: Computational Life Sciences, vol. 8, no. 2, pp. 186–191, 2016. View at Publisher · View at Google Scholar
  • Bin Liu, “iEnhancer-PsedeKNC: identification of enhancers and their subgroups based on Pseudo degenerate kmer nucleotide composition,” Neurocomputing, 2016. View at Publisher · View at Google Scholar
  • Hui Ding, Zhi-Yong Liang, Feng-Biao Guo, Jian Huang, Wei Chen, and Hao Lin, “Predicting bacteriophage proteins located in host cell with feature selection technique,” Computers In Biology And Medicine, vol. 71, pp. 156–161, 2016. View at Publisher · View at Google Scholar
  • Swakkhar Shatabda, Sanjay Saha, Alok Sharma, and Abdollah Dehzangi, “iPHLoc-ES: Identification of Bacteriophage Protein Locations using Evolutionary and Structural Features,” Journal of Theoretical Biology, 2017. View at Publisher · View at Google Scholar
  • Leyi Wei, Jijun Tang, and Quan Zou, “SkipCPP-Pred: an improved and promising sequence-based predictor for predicting cell-penetrating peptides,” BMC Genomics, vol. 18, no. S7, pp. 1–11, 2017. View at Publisher · View at Google Scholar
  • Jing-Hui Cheng, Hui Yang, Meng-Lu Liu, Wei Su, Peng-Mian Feng, Hui Ding, Wei Chen, and Hao Lin, “Prediction of bacteriophage proteins located in the host cell using hybrid features,” Chemometrics and Intelligent Laboratory Systems, vol. 180, pp. 64–69, 2018. View at Publisher · View at Google Scholar
  • Hui Yang, Hao Lv, Hui Ding, Wei Chen, and Hao Lin, “ iRNA-2OM: A Sequence-Based Predictor for Identifying 2′-O-Methylation Sites in Homo sapiens ,” Journal of Computational Biology, 2018. View at Publisher · View at Google Scholar
  • Jiu-Xin Tan, Fu-Ying Dao, Hao Lv, Peng-Mian Feng, and Hui Ding, “Identifying Phage Virion Proteins by Using Two-Step Feature Selection Methods,” Molecules, vol. 23, no. 8, pp. 2000, 2018. View at Publisher · View at Google Scholar
  • Wei Chen, Pengmian Feng, Hui Yang, Hui Ding, Hao Lin, and Kuo-Chen Chou, “iRNA-3typeA: Identifying Three Types of Modification at RNA’s Adenosine Sites,” Molecular Therapy - Nucleic Acids, vol. 11, pp. 468–474, 2018. View at Publisher · View at Google Scholar
  • Mohammad Reza Bakhtiarizadeh, Maryam Rahimi, Abdollah Mohammadi-Sangcheshmeh, Vahid Shariati J, and Seyed Alireza Salami, “PrESOgenesis: A two-layer multi-label predictor for identifying fertility-related proteins using support vector machine and pseudo amino acid composition approach,” Scientific Reports, vol. 8, no. 1, 2018. View at Publisher · View at Google Scholar
  • Yanyuan Pan, Hui Gao, Hao Lin, Zhen Liu, Lixia Tang, and Songtao Li, “Identification of Bacteriophage Virion Proteins Using Multinomial Naïve Bayes with g-Gap Feature Tree,” International Journal of Molecular Sciences, vol. 19, no. 6, pp. 1779, 2018. View at Publisher · View at Google Scholar
  • Ya-Wei Zhao, Ping Zou, Po Huang, Hao Lin, Hua Tang, Chun-Mei Zhang, and Rong Chen, “HBPred: A tool to identify growth hormone-binding proteins,” International Journal of Biological Sciences, vol. 14, no. 8, pp. 957–964, 2018. View at Publisher · View at Google Scholar
  • Hao Lin, Hui Yang, Wang-Ren Qiu, Guoqing Liu, Feng-Biao Guo, Wei Chen, and Kuo-Chen Chou, “IRSpot-Pse6NC: Identifying recombination spots in Saccharomyces cerevisiae by incorporating hexamer composition into general PseKNC,” International Journal of Biological Sciences, vol. 14, no. 8, pp. 883–891, 2018. View at Publisher · View at Google Scholar
  • Halil Bisgin, Tanmay Bera, Hongjian Ding, Howard G. Semey, Leihong Wu, Zhichao Liu, Amy E. Barnes, Darryl A. Langley, Monica Pava-Ripoll, Himansu J. Vyas, Weida Tong, and Joshua Xu, “Comparing SVM and ANN based Machine Learning Methods for Species Identification of Food Contaminating Beetles,” Scientific Reports, vol. 8, no. 1, 2018. View at Publisher · View at Google Scholar
  • Balachandran Manavalan, Tae H. Shin, and Gwang Lee, “PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine,” Frontiers in Microbiology, vol. 9, 2018. View at Publisher · View at Google Scholar
  • Waqar Hussain, Yaser Daanial Khan, Nouman Rasool, Sher Afzal Khan, and Kuo-Chen Chou, “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, 2018. View at Publisher · View at Google Scholar
  • Fu-Ying Dao, Hao Lv, Fang Wang, and Hui Ding, “Recent Advances on the Machine Learning Methods in Identifying DNA Replication Origins in Eukaryotic Genomics,” Frontiers in Genetics, vol. 9, 2018. View at Publisher · View at Google Scholar
  • Yaser Daanial Khan, Mehreen Jamil, Waqar Hussain, Nouman Rasool, Sher Afzal Khan, and Kuo-Chen Chou, “pSSbond-PseAAC: Prediction of disulfide bonding sites by integration of PseAAC and statistical moments,” Journal of Theoretical Biology, 2018. View at Publisher · View at Google Scholar
  • Maryam Mousivand, Maryam Hashemi, Kaveh Kavousi, Shohreh Ariaeenejad, Parinaz Moradi Dezfouli, and Ghasem Hosseini Salekdeh, “A computational method for prediction of xylanase enzymes activity in strains of Bacillus subtilis based on pseudo amino acid composition features,” PLoS ONE, vol. 13, no. 10, 2018. View at Publisher · View at Google Scholar
  • Xiao-Juan Zhu, Chao-Qin Feng, Hong-Yan Lai, Wei Chen, and Lin Hao, “Predicting protein structural classes for low-similarity sequences by evaluating different features,” Knowledge-Based Systems, 2018. View at Publisher · View at Google Scholar
  • Kaiyang Qu, Fei Guo, Xiangrong Liu, Yuan Lin, and Quan Zou, “Application of Machine Learning in Microbiology,” Frontiers in Microbiology, vol. 10, 2019. View at Publisher · View at Google Scholar
  • Xiaoqing Ru, Lihong Li, and Chunyu Wang, “Identification of Phage Viral Proteins With Hybrid Sequence Features,” Frontiers in Microbiology, vol. 10, 2019. View at Publisher · View at Google Scholar
  • Waqar Hussain, Yaser Daanial Khan, Nouman Rasool, Sher Afzal Khan, and Kuo-Chen Chou, “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, 2019. View at Publisher · View at Google Scholar
  • Pengmian Feng, Zhaochun Xu, Hui Yang, Hao Lv, Hui Ding, and Li Liu, “Identification of D Modification Sites by Integrating Heterogeneous Features in Saccharomyces cerevisiae,” Molecules, vol. 24, no. 3, pp. 380, 2019. View at Publisher · View at Google Scholar