Sequence-Based Machine Learning Methods in Computational Biology

Call for Papers With the development of high-throughput techniques, genomic and proteomic data were increased exponentially. In order to rapidly and effectively mine the biological functions from these data, it is highly desirable to develop computational methods. As excellent complements to experimental techniques, sequence-based computational methods have shown tremendous advances in decoding the genomic and proteomic data. However, the application of machine learning method in genomics and proteomics fell behind the data growth. Therefore, this special issue will focus on the aspects of application of machine learning method in genomics and proteomics. Potential topics include, but are not limited to: RNA posttranscriptional modification sites prediction Protein subcellular localization using machine learning method Analysis and prediction of DNA-binding sites in proteins Study and recognition mechanism of protein-protein interaction Prediction of functional…


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