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Life Sciences - Systems Biology and Bioinformatics | Quantitative Biology (Press)

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Quantitative Biology

Quantitative Biology

Editors-in-Chief: C. Tang; M.Q. Zhang

ISSN: 2095-4689 (print version)
ISSN: 2095-4697 (electronic version)

Journal no. 40484


Chao Tang, Ph.D.

Chair Professor, School of Physics
Director, Center for Quantitative Biology
School of life sciences, Peking University
Beijing 100871, China
Tel: +86-10-62759762
Fax: +86-10-62753190
E-mail: tangc@pku.edu.cn

Michael Q. Zhang, Ph.D.

P_A32851_michaelq zhang_128x150px
Director, Center for Systems Biology
Cecil H. and Ida Green Distinguished Chair Professor
Department of Molecular & Cell Biology
The University of Texas at Dallas
Guest Professor in both school of Information Science and Technology and Medical School of Tsinghua University
Richardson TX 75080, USA
Tel: 972-883-2523
Fax: 972-883-5710
E-mail: michael.zhang@utdallas.edu

Executive Editor-in-Chief 

Xuegong Zhang, Ph.D.

P_A69785_Xuegong Zhang 照片_128x150px
Professor of Pattern Recognition and Bioinformatics
Director, Bioinformatics Division, BNRist
Deputy Director, MOE Key Laboratory of Bioinformatics
Department of Automation, FIT 1-107, Tsinghua University
Beijing 100084, China
Phone: 86-10-62794919
Fax: 86-10-62786911
Email: zhangxg@tsinghua.edu.cn

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For authors and editors

  • Aims and Scope

    Aims and Scope


     Quantitative Biology is an interdisciplinary journal that focuses on original research that uses quantitative approaches and technologies to analyze and integrate biological systems, construct and model engineered life systems, and gain a deeper understanding of the life sciences.  It aims to provide a platform for not only the analysis but also the integration and construction of biological systems.  It is a quarterly journal seeking to provide an inter- and multi-disciplinary forum for a broad blend of peer-reviewed academic papers in order to promote rapid communication and exchange between scientists in the East and the West.

    The content of Quantitative Biology will mainly focus on the two broad and related areas:

    ·bioinformatics and computational biology,

    which focuses on dealing with information technologies and computational methodologies that can efficiently and accurately manipulate –omics data and transform molecular information into biological knowledge.

    ·systems and synthetic biology,

    which focuses on complex interactions in biological systems and the emergent functional properties, and on the design and construction of new biological functions and systems.

    Its goal is to reflect the significant advances made in quantitatively investigating and modeling both natural and engineered life systems at the molecular and higher levels.

    The journal particularly encourages original papers that link novel theory with cutting-edge experiments, especially in the newly emerging and multi-disciplinary areas of research. The journal also welcomes high-quality reviews and perspective articles. 

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