BioMet Toolbox 2.0: genome-wide analysis of metabolism and omics data
Journal article, 2014

Analysis of large data sets using computational and mathematical tools have become a central part of biological sciences. Large amounts of data are being generated each year from different biological research fields leading to a constant development of software and algorithms aimed to deal with the increasing creation of information. The BioMet Toolbox 2.0 integrates a number of functionalities in a user-friendly environment enabling the user to work with biological data in a web interface. The unique and distinguishing feature of the BioMet Toolbox 2.0 is to provide a web user interface to tools for metabolic pathways and omics analysis developed under different platform-dependent environments enabling easy access to these computational tools.

Author

Manuel Garcia

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Subazini Thankaswamy

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Avlant Nilsson

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Leif Wigge

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Intawat Nookaew

Oak Ridge National Laboratory

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Jens B Nielsen

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Nucleic Acids Research

0305-1048 (ISSN) 1362-4962 (eISSN)

Vol. 42 W1 W175-W181

Industrial Systems Biology of Yeast and A. oryzae (INSYSBIO)

European Commission (FP7), 2010-01-01 -- 2014-12-31.

Subject Categories

Biological Systematics

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

Areas of Advance

Life Science Engineering (2010-2018)

DOI

10.1093/nar/gku371

More information

Latest update

12/4/2018