Nielsen Group

Systems and synthetic biology

The Nielsen Group, led by Senior Group Leader Professor Lars Nielsen, uses systems biology – that is, systems science, modelling and simulation – to integrate data streams and generate knowledge. As applied systems biologists or biotechnologists, they do more than develop tools for better understanding (analysis); they use these tools to design products and processes for human benefit (synthesis). The science is moving from crude retrofitting of living systems with a single or few genes using genetic engineering, to purposeful reengineering of living systems using systems and synthetic biology.

Drawing on a common core of expertise in genome scale metabolic modelling and the full range of ‘omics technologies, the Group studies a diverse range of biological systems, including model and industrial microbes, animals cells, plants and increasingly complex ecosystems.

Partner with the Nielsen Group

Publications

Click here to view Nielsen group publications

We run the Queenlsand Node of Metabolomics Australia. The facility is available to the public.

Genome Databases

We have developed Biocyc databases and genome scale models for most of the organisms we work with.

Mouse GEM - SBML for mouse genome scale model

Quek L-E, Nielsen LK (2008) On the reconstruction of the Mus musculus genome-scale metabolic network model. Genome Informatics 21:89-100.

AraFlux - A Matlab Toolbox for performing flux analysis using AraGEM genome scale model

de Oliveira Dal'molin CG, Quek LE, Palfreyman RW, Brumbley SM, Nielsen LK (2010) AraGEM - a Genome-Scale Reconstruction of the Primary Metabolic Network in Arabidopsis thaliana. Plant Physiol. 152: 579–589. PMID: 20044452.

AraGEM COBRA - AraGEM SBML file for use with COBRA Toolbox in Matlab

Mammalian MFA - Matlab files for mammalian cell culture MFA using reduced Mouse GEM

Quek L-E, Dietmair S; Kr?mer JO, Nielsen LK (2010) Metabolic flux analysis in mammalian cell culture. Metabolic Engineering 12: 161-171. PMID: 19833223.

C4GEM - SBML models for maize, sorghum and sugarcane

de Oliveira Dal'molin CG, Quek LE, Palfreyman RW, Brumbley SM, Nielsen LK (2010) C4GEM - Genome-Scale Metabolic Model to study C4 plant metabolism. Plant Physiol. 154:1871-85. PMID: 20974891.

C4 Flux Toolbox - Matlab Flux Toolbox with maize example

de Oliveira Dal'molin CG, Quek LE, Palfreyman RW, Brumbley SM, Nielsen LK (2010) C4GEM - Genome-Scale Metabolic Model to study C4 plant metabolism. Plant Physiol. 154:1871-85. PMID: 20974891.

iCA1273 version 1.01 - E. coli W genome scale model

Archer CT, Kim JF, Jeong H, Park JH, Vickers CE, Lee SY, Nielsen LK (2011) The genome sequence of E. coli W (ATCC 9637): comparative genome analysis and an improved genome-scale reconstruction of E. coli. BMC Genomics 12:9. PMID: 21208457.

AlgaGEM - AlgaGEM SBML file for use with COBRA Toolbox in Matlab

Dal’Molin CGO, Quek LE, Palfreyman RW, Nielsen LK (2011) AlgaGEM - A genome-scale metabolic reconstruction of Algae based on Chlamydomonas reinhardtii genome. BMC Genomics 12(Supp 4): S5.http://www.biomedcentral.com/1471-2164/12/S4/S5.

Software

We make our software packages available.

Examples of Dirichlet Kernels (Bioinformatics submission)

The attached examples are for a submission in Bioinformatics only. Download: Dirichlet Kernel.zip

Fast-SNP

Saa PA, Nielsen LK (2016) Fast-SNP: a fast matrix pre-processing algorithm for efficient loopless flux optimization of metabolic models. Bioinformatics 32: 3807–3814.

Download: Fast_SNP_v10_10_16.zip

ll-ACHRB

Saa PA, Nielsen LK (2016) ll-ACHRB: a scalable algorithm for sampling the feasible solution space of metabolic networks. Bioinformatics 32: 2330–2337.

ll-ACHRB software ver 1.1 (introduces faster warm up using efficient loopless optimization): ll_ACHRB ver 1.1.zip

B-DMFA

Martínez VS, Buchsteiner M, Gray P, Nielsen LK, Quek LE (2015) Dynamic Metabolic Flux Analysis using B-splines to study the effects of temperature shift on CHO cell metabolism. Met Eng Comm 2: 46-57.

B-DMFA is available either as quadratic spline or generic order.

MultiGEM - multi-tissue GEM framework

Dal'molin CGDO, Quek LE, Saa PA, Nielsen LK (2015) A multi-tissue genome-scale metabolic modelling framework for the analysis of whole plant systems. Front. Plant Sci. 6:4. Online.

Download software from this site.

Supplementary Data for OpenFlux

Quek L-E, Wittmann C, Nielsen LK, Kroemer JO (2009) OpenFLUX: Efficient Modelling Software for 13C-Based Metabolic Flux Analysis. Microbial Cell Factories 8:25. PMID: 19409084.

Quek LE, Nielsen LK (2014) Steady-State 13C Fluxomics Using OpenFLUX. In: Krömer JO, Nielsen LK, Blank LM (eds) Metabolic Flux Analysis: Methods and Protocols. Series: Methods in Molecular Biology, vol. 1191. Chapter 13: 65-78. PMID: 25178793.

Registration (please register for use of OpenFlux)

C. glutamicum model (Excel file)

TCA model (Excel file)

Atom transitions (Excel file)

PathLogic

Fearnley LG, Nielsen LK (2012) PATHLOGIC-S: A scalable Boolean framework for modelling cellular signalling. PLoS ONE 7(8): e41977. PMID: 22879903.

Available from Sourceforge.

Martínez VS, Quek LE, Nielsen LK ( 2014) Network thermodynamic curation of human and yeast genome-scale metabolic models. Biophys J 107:493-503. PMID: 25028891.

Martinez VS, Nielsen LK (2014) NExT: Integration of Thermodynamic Constraints and Metabolomics Data into a Metabolic Network. In: Krömer JO, Nielsen LK, Blank LM (eds) Metabolic Flux Analysis: Methods and Protocols. Series: Methods in Molecular Biology, vol. 1191. Chapter 4: 209-224. PMID: 25178784.

Download software from this site.

Partner with the Nielsen Group

Professor Lars Nielsen

Senior Group Leader

Nielsen Group

Researchers

Dr Craig Barry

Postdoctoral Research Fellow

Nielsen Group

Ancient biology meets cutting-edge technology at AIBN

Published on: 28 July 2017

AIBN Researchers and US company LanzaTech have developed a computer model that harnesses ancient biology for carbon-capture biotechnology.
International deal brings new treatment for chemotherapy patients closer to the clinic

Published on: 6 December 2016

Patients at risk of life-threatening infections following chemotherapy could benefit from a new cell-based treatment developed from University of Queensland research.
UQ-Amyris collaboration seeks to accelerate development of Queensland ‘Biofutures Hub’

Published on: 7 June 2016

Leading American biotechnology company Amyris, Inc. and the Australian Institute for Bioengineering and Nanotechnology at The University of Queensland have signed a Memorandum of Understanding to support the development of a Queensland-based biotechnology industry using feedstock from local sugarcane.
AIBN picks up Research Week Awards

Published on: 16 September 2015

Two researchers from the Australian Institute for Bioengineering and Nanotechnology at The University of Queensland have won awards for their work during UQ’s annual Research Week.
Novo Nordisk Foundation (NNF) Nielsen

Published on: 6 February 2015

An international multi-million dollar grant will support a University of Queensland researcher’s attempts to crack a 90-year old mystery around the detailed biology of cancer cells.
Tall Poppy Award celebrates scientific excellence

Published on: 26 November 2014

University of Queensland synthetic biologist Claudia Vickers has been recognised for scientific excellence with a 2014 Queensland Young Tall Poppy Science Award.
Student Challenge Success for AIBN

Published on: 28 July 2014

Researchers at the Australian Institute for Bioengineering and Nanotechnology (AIBN) were awarded first prize in the Dow Sustainability Innovation Student Challenge Award (SISCA).
Future jet fuels could come from lemons

Published on: 9 October 2013

An Australian Institute for Bioengineering and Nanotechnology researcher hopes to use a chemical found in lemons and other citrus fruits to make clean, renewable jet fuel.
From a petrochemical to a biochemical economy

Published on: 30 September 2013