Computational analysis in systems biology

Dnr:

SNIC 2017/1-89

Type:

SNAC Medium

Principal Investigator:

Jens Nielsen

Affiliation:

Chalmers tekniska högskola

Start Date:

2017-04-01

End Date:

2018-04-01

Primary Classification:

10602: Biokemi och molekylärbiologi

Secondary Classification:

20901: Bioprocessteknik

Tertiary Classification:

20902: Biokemikalier

Webpage:

http://www.sysbio.se/

Allocation

Abstract

Biological systems are very complex and large-scale data such as genome sequencing, transcriptome data and proteome data have been generated to gain insight into cellular processes. With the massive amount of data, advanced statistical, mathematical and computational methods, as well as large-scale data mining, are required to assist the interpretation of the data by holistic approaches, being fundamental in systems biology. The major projects in the group are related to analyzing large-scale data such as genome sequencing and re-sequencing, RNA sequencing and microarray data that generally demand a high performance computational facility. Moreover developing and applying computational techniques such as sequence alignment, genome assembly, gene finding, gene annotation and analysis, reconstruction and analyzing of biological networks, large-scale simulations are performed in our group. The details of our activity are listed below. - Metagenomics analysis of human gut microbiome associated with dieases - Metatranscriptomics of mouse microbiome in different parts of the GI tract - Metatranscriptomics of gastric cancer - Saccharomyces ceravisiae genome re-sequencing - RNA-sequencing of yeast in various growth conditions - RNA-sequencing of human muscle in relation to diabetes and biomarker discovery - RNA-sequencing of human liver in relation to liver cancer and biomarker discovery - RNA-sequencing of human adipose in relation to obesity and biomarker discovery - Human tissue specific genome scale metabolic models and simulations - Multi-species genome scale metabolic models and simulations - Simulation of genome-wide yeast metabolism - Microarray analysis from various experiments