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.
Readers of Quantitative Biology include biologists and information/mathematical/physical scientists and engineers, who can take the important findings presented in Quantitative Biology to the next level of discovery and bring new insights into and across multi-disciplines.
Quantitative Biology is offering FREE online access since its inception.
Quantitative Biology is administered by
·Higher Education Press
and in collaboration with
·Beijing National Research Center for Information Science and Technology, Tsinghua University
·Center for Synthetic & Systems Biology, TNList, Tsinghua University
·Center for Quantitative Biology, Peking University
- Journal Title
- Quantitative Biology
- Volume 1 / 2013 - Volume 6 / 2018
- Print ISSN
- Online ISSN
- Higher Education Press
- Additional Links
To view the rest of this content please follow the download PDF link above.