The Scientific World Journal

Application of Machine Learning Method in Genomics and Proteomics

Publishing date
30 Jan 2015
Submission deadline
12 Sep 2014

Lead Editor

1University of Electronic Science and Technology of China, Chengdu, China

2Hebei United University, Tangshan, China

3Virginia Tech, Blacksburg, USA

4University of Warsaw, Warszawa, Poland

Application of Machine Learning Method in Genomics and Proteomics


With the avalanche of genomic and proteomic data generated in the postgenomic age, it is highly desirable to develop automated methods for rapidly and effectively analyzing and predicting the structure, function, and other properties of DNA and protein. Researchers realize the importance of machine learning methods and feature selection algorithms for potential knowledge finding tasks in genomics and proteomics. Recent years have shown tremendous advances in the properties prediction of DNA fragments and protein sequences by various pattern recognition methods. These techniques provide economical and time-saving solutions for identifying the properties of DNA and protein. This special issue will focus on various aspects of the application of machine learning methods in genomics and proteomics bioinformatics. The recent developments on the prediction of protein subcellular localization, posttranslational modification sites, DNA-binding site, protein-protein interaction, nucleosome positioning, transcription factor binding site, exon/intron splice site, translation initiation site, and transcription start site will be included in the special issue.

Potential topics include, but are not limited to:

  • Protein folding
  • Protein subcellular localization
  • Protein posttranslational modification sites
  • Protein family
  • Binding sites in proteins
  • Mechanism of protein-protein interaction
  • Gene prediction and annotation
  • Transcription factor binding site
  • Exon/intron splice site, including alternative splice site
  • Translation initiation site and transcription start site
  • Noncoding RNA
  • Gene function and activity
  • Molecular mutation and evolution
  • Biomarker


  • Special Issue
  • - Volume 2015
  • - Article ID 914780
  • - Editorial

Application of Machine Learning Method in Genomics and Proteomics

Hao Lin | Wei Chen | ... | Dariusz Plewczynski
  • Special Issue
  • - Volume 2015
  • - Article ID 945927
  • - Review Article

Briefing in Application of Machine Learning Methods in Ion Channel Prediction

Hao Lin | Wei Chen
  • Special Issue
  • - Volume 2014
  • - Article ID 740506
  • - Research Article

Prediction of DNase I Hypersensitive Sites by Using Pseudo Nucleotide Compositions

Pengmian Feng | Ning Jiang | Nan Liu
  • Special Issue
  • - Volume 2014
  • - Article ID 464093
  • - Research Article

Protein Binding Site Prediction by Combining Hidden Markov Support Vector Machine and Profile-Based Propensities

Bin Liu | Bingquan Liu | ... | Xiaolong Wang
  • Special Issue
  • - Volume 2014
  • - Article ID 864135
  • - Research Article

acACS: Improving the Prediction Accuracy of Protein Subcellular Locations and Protein Classification by Incorporating the Average Chemical Shifts Composition

Guo-Liang Fan | Yan-Ling Liu | ... | Yan Zhao
  • Special Issue
  • - Volume 2014
  • - Article ID 978503
  • - Research Article

Prediction of Four Kinds of Simple Supersecondary Structures in Protein by Using Chemical Shifts

Feng Yonge
  • Special Issue
  • - Volume 2014
  • - Article ID 236717
  • - Research Article

An Empirical Study of Different Approaches for Protein Classification

Loris Nanni | Alessandra Lumini | Sheryl Brahnam
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Acceptance rate15%
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