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Head: Stephen Emmott
Computational modelling of biological systems is becoming increasingly
common as we try to understand biological phenomena in their full
complexity. In order to meet this challenge we need to establish the
methodologies and techniques that will enable us to gain a system-level
understanding of biological processes. The goal of the Computational
Biology Division is to enhance biological comprehension by using methods
and tools designed in Computer Science to model and analyze biological
systems.
Research Groups
Jasmin Fisher - Executable Biology
We are interested in the design and analysis of executable computer
algorithms that mimic biological phenomena. We call this approach
Executable Biology. These kinds of models hold great promise for new
discoveries in a wide variety of biological systems. Once an executable
model has been built of a particular system, it can be used to get a
global dynamic picture of how the system responds to various
perturbations. In addition, preliminary studies can be quickly performed
using executable models, saving valuable laboratory time and resources
for only the most promising avenues.
Our research is focused on two main directions: (1) the use of different
formalisms to create executable models of biological phenomena, aiming
to enhance biological comprehension, and (2) the development of tools
and design of algorithms that are specifically tailored for modelling
biological systems. We put a lot of emphasis on constructing
user-friendly tools (i.e., visual, flexible), in order to
facilitate the integration of such computational tools as mainstream
techniques in biological research.
Hillel Kugler - Systems Biology
Our research focuses on developing theory, languages and tools for
modelling, analyzing and understanding complex biological systems. We
use ideas and methods originally developed in computer science, mainly
in software and systems engineering (and in particular visual languages
and formal verification) to construct, simulate and analyze biological
models. Our goals include making these tools accessible to biologists,
improving upon the existing algorithms and techniques to handle large
and complex systems and investigating the use of the new tools
created specifically for biological systems and additional application
domains. The modelling work is done in close collaboration with
experimental biology labs, while theory, methodology and tool
development work is done in collaboration with researchers at Microsoft
and academic colleagues.
Andrew Phillips - Programming Biology
We are developing programming languages and tools for simulating and
analysing complex models of biological systems. One of our aims is to
develop a language in which large models of biological systems can be
programmed from simple components in a modular fashion. The ultimate
goal is to be able to program and test a biological system on a
computer, before implementing the final design inside a living organism.
The Microsoft Research - University of Trento Centre for Computational
and Systems Biology
Launched in February 2005,
the
Microsoft Research - University of Trento
Centre for Computational and Systems Biology is a joint venture between
Microsoft Research and the University of Trento, and is partly sponsored by the
Italian central and local governments.
At the Trento Centre, researchers are focusing on creating the next generation of computational tools that will enable biologists and others working in the life sciences to better understand and predict complex processes in biological systems, which could revolutionise our understanding of disease, and lead to new and faster insights into entirely novel therapies and better vaccines.
The Centre is also establishing close cooperation with experimental
scientists at both the domestic and international level to maintain a close
relationship with real biological data. Opened in December 2005 by Rick Rashid,
the Centre is a partnership between the University of Trento and Microsoft
Research with the external support of both the Italian Government and the Trentino Government.
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