Scientists develop a new computational method to uncover gene regulation

Apr 13, 2010

(PhysOrg.com) -- Researchers from Aalto University (Finland), European Molecular Biology Laboratory Heidelberg (Germany) and the University of Manchester (UK) have developed a new computational method to identify targets of regulator genes. The method is presented in the Early Edition of Proceedings of the National Academy of Sciences (PNAS).

The human contains instructions for making all the cells in our body. An individual cell's make up (e.g. muscle or blood) depends on how these instructions are read. This is controlled by gene regulatory mechanisms. Uncovering these mechanisms holds a key to greatly improving our understanding of biological systems.

One important is based on genes that actively promote or repress the activity of other genes. The new research addresses the problem of identifying the targets these regulator genes affect.

The new method is based on careful modelling of time series measurements of . It combines a simple biochemical model of the cell with probabilistic modelling to deal with incomplete and uncertain measurements.

Dr Rattray, a senior researcher from the University of Manchester, said: "Combining biochemical and probabilistic modelling techniques as done here holds great promise for the future. Many systems we are looking at now are too complex for purely physical models and connecting to experimental data in a principled manner is essential."

Dr Honkela, a senior research fellow from Aalto University, added: "A major contribution of our work is to show how data-driven machine learning techniques can be used to uncover physical models of cell regulation. This demonstrates how data-driven modelling can clearly benefit from the incorporation of physical modelling ideas."

Explore further: The origin of the language of life

More information: The original research article is available through PNAS early edition: A Honkela, C Girardot, EH Gustafson, Y Liu, EEM Furlong, ND Lawrence, M Rattray (2010), "Model-based method for transcription factor target identification with limited data." Proc Natl Acad Sci USA, www.pnas.org/cgi/doi/10.1073/pnas.0914285107

add to favorites email to friend print save as pdf

Related Stories

Learning the language of gene expression

Jan 19, 2007

Researchers have taken a major step towards understanding the language of gene regulation in the fruitfly Drosophila and they expect the technique to be rapidly applicable to understanding the effects of genome variation ...

Scientists achieve first rewire of genetic switches

Jan 25, 2010

Researchers in Manchester have successfully carried out the first rewire of genetic switches, creating what could be a vital tool for the development of new drugs and even future gene therapies.

Computers make sense of experiments on human disease

Nov 12, 2008

Increased use of computers to create predictive models of human disease is likely following a workshop organised by the European Science Foundation (ESF), which urged for a collaborative effort between specialists in the ...

Recommended for you

The origin of the language of life

Dec 19, 2014

The genetic code is the universal language of life. It describes how information is encoded in the genetic material and is the same for all organisms from simple bacteria to animals to humans. However, the ...

Quest to unravel mysteries of our gene network

Dec 18, 2014

There are roughly 27,000 genes in the human body, all but a relative few of them connected through an intricate and complex network that plays a dominant role in shaping our physiological structure and functions.

EU court clears stem cell patenting

Dec 18, 2014

A human egg used to produce stem cells but unable to develop into a viable embryo can be patented, the European Court of Justice ruled on Thursday.

User comments : 0

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.