News release

New method to identify genes affecting health

Ref: 08/131

9 July 2008

A new tool which makes it possible to extract information about an individual's health from genotypes in a fraction of a second, has been developed by an academic at the University of Southampton.

In a paper entitled Boosting Haplotype Inference with Local Search, just published in Constraints: An International Journal, Professor Joao Marques-Silva, of the University's School of Electronics and Computer Science, describes with collaborators a new approach to the process of inferring haplotype information from genotype data.

A haplotype can be defined as a group of alleles of one or more genes on a single chromosome that are closely enough linked to be inherited usually as a unit and a genotype refers to the combination of alleles inherited from both parents.

According to Professor Marques-Silva, the current method of extracting haplotypes from genotype data is based on statistical approaches, which can take a long time to compute.

Professor Marques-Silva and collaborators approached this scenario by taking the Haplotype Inference by Pure Parsimony (HIPP), a solution that minimises the total number of distinct haplotypes used, and developed new algorithms which they applied to achieve faster results.

"Biologists have been using these statistical approaches for a long time and may not be open to change," he said. "However, these methods can take days, even months to terminate, whereas our approach produces an almost instant result."

Further research is being carried out currently by Professor Marques-Silva and collaborators to validate this new method and to prove that it could replace statistical methods in a number of settings.

"This is the biggest development that we have made in this field so far," said Professor Marques-Silva. "It remains to be seen whether biologists will use this instead of existing techniques."

Ends


Notes for editors

  1. The paper: Boosting Haplotype Inference with Local Search, published this month in Constraints: An International Journal can be accessed at: http://www.springerlink.com/content/100252/?k=Boosting+Haplotype

  2. For further information about Prof Marques-Silva's work, please visit: http://users.ecs.soton.ac.uk/jpms/

  3. With around 500 researchers, and 900 undergraduate students, the School of Electronics and Computer Science at Southampton is one of the world's largest and most successful integrated research groupings, covering Computer Science, Software Engineering, Electronics, and Electrical Engineering. ECS has unrivalled depth and breadth of expertise in world-leading research, new developments and their applications.

  4. The University of Southampton is a leading UK teaching and research institution with a global reputation for leading-edge research and scholarship.

    This is one of the country's top institutions for engineering, computer science and medicine, and home to a range of world-leading research centres, including the National Oceanography Centre, Southampton, the Institute of Sound and Vibration Research, the Optoelectronics Research Centre, the Centre for the Developmental Origins of Health and Disease, and the Mountbatten Centre for International Studies.

    We combine academic excellence with an innovative and entrepreneurial approach to research, supporting a culture that engages and challenges students and staff in their pursuit of learning.

    As one of the UK's top 10 research universities, we offer first-rate opportunities and facilities for study and research across a wide range of subjects in humanities, health, science and engineering. We have over 22,000 students, around 5000 staff, and an annual turnover in the region of £325 million.

  5. For further information contact:

    Professor Joao Marques-Silva, School of Electronics and Computer Science,
    Tel: 023 8059 3377, email: jpms@ecs.soton.ac.uk
    Joyce Lewis, Communications Manager, School of Electronics and Computer Science, University of Southampton Tel. 023 8059 5453; email jkl2@ecs.soton.ac.uk