Computational Modelling Group

Quantitative Biology

Quantitative Biology represents an interdisciplinary initiative under the umbrella of the Institute for Life Sciences. The remit is broad and targets applications of mathematical, computational and bioinformatics techniques to experimental biology and biomedicine, with a particular initial focus on Systems Biology and protein networks.

For queries about this topic, contact Richard Edwards.

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Projects

A spatially-explicit agent-based model of jaguar population dynamics

Jason Noble, Patrick Doncaster (Investigators), Angela Watkins

A single species spatially-explicit agent-based model has been developed that illustrates the role of simulation modelling, integrated with an adapted least-cost modelling approach and real-world geographical data, in exploring jaguar population dynamics.

Agent-based simulations of jaguar movements through conservation corridors

Jason Noble, Patrick Doncaster (Investigators), Angela Watkins

We present an agent-based model of jaguars (Panthera onca),
scaled for fragmented habitat in Belize where proposals already exist for creating a jaguar corridor. We use a least cost approach to simulate movement paths through alternative possible landscapes.

Integrating least-cost models with agent-based simulations: example hedgehog responses to fragmented landscapes

Jason Noble, Patrick Doncaster (Investigators), Angela Watkins

This study presents a novel analysis of an agent-based model of hedgehog movements integrated with a least-cost model of hedgehog dispersal and validated in landscapes with a varying degree of habitat fragmentation. A comparison of the fitness of individual agents reveals that incorporating a simple rule into
individual agents, to better mimic movement choices by real hedgehogs, dramatically affects the relationship between individual fitness and fragmentation.

Lagrangian modelling of ecosystem dynamics at the Bermuda Atlantic Time-series Study station

Tom Anderson, Seth Bullock (Investigators), Melissa Saeland

Focus in the marine ecosystem modelling community is starting to shift towards the use of Lagrangian, agent-based models as these are believed to produce more realistic results. The basic assumptions behind these models have not been thoroughly tested, and this project aims to undertake a detailed study of Lagrangian marine ecosystem models, before creating one to investigate the dynamics at the Bermuda Atlantic Time-series Study station (BATS).

Multiscale Modelling of Cellular Calcium Signalling

Hans Fangohr, Jonathan Essex (Investigators), Dan Mason

Calcium ions play a vitally important role in signal transduction and are key to many cellular processes including muscle contraction and cell apoptosis (cell death). This importance has made calcium an active area in biomedical science and mathematical modelling.

Sample tracking in whole-exome sequencing projects

Andrew Collins, Sarah Ennis (Investigators), Reuben Pengelly

Whole-exome sequencing is entering clinical use for genetic investigations, and it is therefore essential that robust quality control is utilised. As such we designed and validated a tool to allow for unambiguous tying of patient data to a patient, to identify, and thus prevent errors such as the switching of samples during processing.

Sensitivity of the critical depth to the choice of particle movement rules in Lagrangian models and the consequences for the predicted timing of the spring bloom

Tom Anderson (Investigator), Melissa Saeland

Individual-based (Lagrangian) models lend themselves to the study of the controls of the spring bloom in the ocean, due to their ability to represent both the turbulence and the phytoplankton motion. Here, we use a Lagrangian phytoplankton model to test some of the most prevalent hypotheses (e.g. critical depth and critical turbulence).

Tag based transcriptome analysis of gene expression in a promising green algae

Richard Edwards (Investigator), Andreas Johansson

We use SuperSAGE in combination with next-generation sequencing to compare differences in gene expression between selected mutants and the wild type of a green algae. The data in the form of millions of 26 bp tags representing short stretches of expressed genes, will be analysed to find patterns of variation in gene expression under different conditions.

The application of next-generation sequencing to unresolved familial disease

Andrew Collins, Sarah Ennis (Investigators), Jane Gibson, Reuben Pengelly

Next-generation sequencing (NGS) allows us to sequence individual patients cost-effectively, allowing us to enter a new era of genomic medicine. The level of genetic detail that we can access through these methods is unprecedented making it suitable for clinical molecular diagnostics.

People

Seth Bullock
Professor, Electronics and Computer Science (FPAS)
Andrew Collins
Professor, Medicine (FM)
Sarah Ennis
Professor, Medicine (FM)
Jonathan Essex
Professor, Chemistry (FNES)
Hans Fangohr
Professor, Engineering Sciences (FEE)
Patrick Doncaster
Reader, Biological Sciences (FNES)
Thomas Blumensath
Senior Lecturer, Institute of Sound & Vibration Research (FEE)
Robert Ewing
Senior Lecturer, Biological Sciences (FNES)
Christopher Bell
Lecturer, Biological Sciences (FNES)
Jane Gibson
Lecturer, Biological Sciences (FNES)
Tom Anderson
Principal Research Fellow, National Oceanography Centre (FNES)
Alistair Bailey
Research Fellow, Medicine (FM)
Petros Bogiatzis
Research Fellow, Ocean & Earth Science (FNES)
Jason Noble
Research Fellow, Electronics and Computer Science (FPAS)
Reuben Pengelly
Research Fellow, Medicine (FM)
Joseph Egan
Postgraduate Research Student, Mathematics (FSHS)
Graham Elliott
Postgraduate Research Student, Electronics and Computer Science (FPAS)
Andreas Johansson
Postgraduate Research Student, National Oceanography Centre (FNES)
Maximillian Phipps
Postgraduate Research Student, Chemistry (FNES)
Sonya Ridden
Postgraduate Research Student, Mathematics (FSHS)
Melissa Saeland
Postgraduate Research Student, National Oceanography Centre (FNES)
Angela Watkins
Postgraduate Research Student, Biological Sciences (FNES)
Ella Marley-Zagar
Enterprise staff, Medicine (FM)
Richard Edwards
Alumnus, University of New South Wales, Australia
Dan Mason
Alumnus, University of Southampton