NEWS CARD-8 ED6060 FELICIANO DE ALMEIDA BELO ID
5529511
Computation helps understand cancer
By: Jasmin Fisher , Researcher at Microsoft Research Cambridge, Programming Principles & Tools group
Tags: Economic Growth, Europe 2020, Horizon 2020, innovation, Research
20 June 2012
The decade
of genomic revolution following the complete determination of the human DNA
sequence, has produced significant medical advances, and yet again, revealed
how complicated human biology is, and how much more remains to be understood.
Biology is an extraordinary complicated puzzle; we may know some of its pieces
but have no clue how they are assembled to orchestrate the symphony of life,
which renders the comprehension and analysis of living systems a major
challenge.
Computer
science can play a major role in helping solve this puzzle. Recent efforts to
create executable models of complex biological phenomena - an approach we call Executable
Biology - entail great promise for new scientific discoveries, shading new
light on the puzzle of life. At the same time, this new wave of the future
forces computer science to stretch far and beyond, and in ways never considered
before, in order to deal with the enormous complexity observed in biology.
Complex human diseases, such as cancer, arise from the interaction between many different genes and the environment and are the main causes of death in Europe. In contrast to the successful identification of genes underlying rare monogenic diseases, studying the genetic basis of common complex diseases has been more challenging.
Complex human diseases, such as cancer, arise from the interaction between many different genes and the environment and are the main causes of death in Europe. In contrast to the successful identification of genes underlying rare monogenic diseases, studying the genetic basis of common complex diseases has been more challenging.
Evidence
is mounting to suggest that the genetic background of the patient has a
profound impact on a wide variety of complex disease in humans, but so far, the
genetic mechanisms are mostly unknown. The nematode worm Caenorhabditis elegans
is an important model for the identification of genes underlying complex
diseases in humans. Indeed some key genetic processes in C. elegans have
been implicated in human cancers and the simplicity of the C. elegans
worm allows easy and detailed study of those processes.
My work at
Microsoft Research Cambridge focuses on the usage of computer-based techniques
originally developed for engineering computerized systems, to model and analyze
the crosstalk between cancer signalling pathways during C. elegnas development.
We work in a consortium with five other research groups from the UK,
Netherlands and Switzerland, (EU FP7 consortium called PANACEA) and we aim to gain a better understanding of the
mechanisms underlying complex human disease, in particular cancer. In this
joint effort, we analyze large experimental data set through executable
modeling of cell differentiation and cell death (apoptosis), which are
fundamental in cancer development. Our modeling work has already provided
several new biological insights, and we hope that this line of work will
further help generate a broader description of disease states, and pave the way
for novel drug targets and therapies for human cancers.
This information is very important for
human being life.
