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Advances in Computational Genomics

Call for Papers

Computational Genomics refers to the use of computational analysis to decipher biology from genome sequences and related data, including both DNA and RNA sequences and other “postgenomic”data. Next generation sequencing (NGS) technologies have been rapidly applied in biomedical and biological research since their advent only a few years ago and have produced an avalanche of genome sequences. Transforming genomic information into biological knowledge requires creative and innovative new computational methods for all aspects of genomics. With the current abundance of massive biological datasets, computational studies have become one of the most important avenues for biological discovery.

We invite investigators to contribute original research articles, as well as review articles, that will stimulate the continuing efforts in Computational Genomics for more efficient analysis of big genomics data. Emphasis of implementations on high performance computing systems, parallel algorithms, and knowledge extraction from genome-wide genomics data will be seen favorably. Advances in computational methods are welcome, though all submissions should include genome-scale analyses. Potential topics include, but are not limited to:

  • Functional genomics
  • Evolutionary genomics
  • Comparative genomics
  • Metagenomics
  • Epigenomics, noncoding RNA analysis, and DNA methylation analysis
  • Applications in NGS analysis

Before submission authors should carefully read over the journal’s Author Guidelines, which are located at Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at according to the following timetable:

Manuscript DueFriday, 6 June 2014
First Round of ReviewsFriday, 29 August 2014
Publication DateFriday, 24 October 2014

Lead Guest Editor

  • Leng Han, Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA

Guest Editors

  • Yan Guo, Department of Cancer Biology, Vanderbilt University, Vanderbilt Technologies for Advanced Genomics Analysis and Research Design (VANGARD), Vanderbilt Center for Quantitative Sciences, Nashville, TN, USA
  • Zhixi Su, School of Life Sciences, Fudan University, Shanghai, China
  • Siyuan Zheng, Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
  • Zhixiang Lu, Department of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, CA, USA