Computational Molecular Biology: an Integration of Experimental Molecular and Genome Biology with Computational Technology  

Yan Zhang1 , Jack Min2
1. College of bioinformatics science and technology, Harbin Medical University, China
2. Center for Applied Chemical Biology, Department of Biological Sciences, Youngstown State University, Youngstown, Ohio 44555, USA
Author    Correspondence author
Computational Molecular Biology, 2011, Vol. 1, No. 1   doi: 10.5376/2011.cmb.01.0001
Received: 09 Feb., 2011    Accepted: 15 Mar., 2011    Published: 04 Apr., 2011
© 2011 BioPublisher Publishing Platform
This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:

Zhang and Min, 2011, Computational Molecular Biology: an Integration of Experimental Molecular and Genome Biology with Computational Technology, Computational Molecular Biology, Vol.1, No.1 1-3 (doi: 10.5376/cmb.2011.01.0001)

Abstract

The emergence and development of computational technology and informatics innovates and complements the research approaches used in the classical molecular biology. Massively parallel signature sequencing approaches, especially genome-wide approaches, become the mainstream experimental approaches, which have generated a large number of biological data. Computational molecular biology is an integration of experimental molecular and genome biology with computational technology. The newly launching journal, Computational Molecular Biology (ISSN 1927-5587) provides a platform for the community in computational molecular and genome biology to disseminate new discoveries in this interdisciplinary field to meet new challenges including raw molecular data generation, data analysis, comparative and evolutionary genomics, and applications of biotechnology by applying the power of computational technology.

Keywords
Computational molecular biology; Systems biology; Genome and genomics; Experimental molecular and genome biology; Computational technology
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