Engqvist Lab

Assistant Professor
Martin Engqvist

Department of Biology and Biological Engineering,
Chalmers University of Technology,
Kemivägen 10, SE-412 96 Göteborg, Sweden

Phone: +46(0)31 772 8171
Fax: +46(0)31 772 3801
E-mail: martin.engqvist [at] chalmers.se
Office: Chemistry building, Room 2024

 

 


Our research focuses on bioinformatics and experimental high-throughput biochemical characterization of metabolic enzymes. We aim to understand how diverse protein sequences determine enzyme function.

Genome sequence data is growing at an explosive rate while experimental data relating to gene function is only growing slowly. The gap between what we know and what we do not know is increasing. The research community must greatly increase the body of experimental data to achieve accurate functional annotation of genes in current and future sequenced genomes, thereby unlocking their full value. A new generation of high-throughput experimental platforms are needed to provide this data.

Combining ideas and expertise from bioinformatics, biochemistry and directed evolution we operate a platform for high-throughput biochemical characterization of enzymes. It is a novel way of applying well-established methods towards a new purpose. We make use of these methods to densely sample sequence diversity in enzyme families. The resulting data is leveraged to gain insights into the sequence-function relationship in metabolic enzymes and forms a basis for improved functional gene annotation in sequenced genomes.


 
Hohmann Lab Larsson Lab Nielsen Lab Mijakovic Lab
Petranovic Lab Engqvist Lab    
   

Latest News

Jens Nielsen's research covered in GP (Göteborgs-Posten)

Leif Väremo’s thesis entitled “Systems Biology of Type 2 Diabetes in Skeletal Muscle” was selected as the best preclinical thesis by the Swedish Diabetes Association.

Jens Nielsen was appointed Honorary Professor at East China University of Science and Technology, Shanghai, China

Jens Nielsen was appointed as Adjunct Professor at Jiangnan University, Wuxi, China

Through sequencing 10 penicillia genome SysBio identified a large number of new secondary metabolite biosynthetic gene clusters were identified. The study was published in Nature Microbiology and featured in Cosmos Magazine.

Paper published in Nature Chemical Biology about engineering the yeast fatty acid synthase for production of short chain fatty acids by yeast was covered by more than 30 newspapers around the world



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