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Content archived on 2024-06-20

In-Silico Prediction of gene function

Objective

The GENEFUN project aims at addressing two important issues. Improving existing sequence-similarity based function annotation tools, and developing and integrating methods that consider information on 3D structure as well as on physical and functional interactions between genes and proteins and the processes in which they are involved. 1- It will develop criteria for evaluating the reliability of the annotations currently available in databases. These criteria will be used to assign reliability scores to these annotations and will be incorporated into standard annotation pipelines, for future use. 2- Higher-level features will be incorporated into functional annotations by combining sequence and structure information in order to identify non-linear functional features (interaction sites) and by integrating different methods for inferring function from context-based information (domain architecture, protein-protein interaction, gene order etc.). To achieve these goals several European groups with a strong track record in various aspects of bioinformatics have teamed up with an experimental group from Canada, which is well known for its strength in structural and functional proteomics. The expected output of the project is: improved procedures for inferring function on the basis of sequence similarity, a set of procedures for predicting non-linear functional features from sequence and 3D structure, and benchmarked procedures for predicting context-based functional features. Major efforts will be devoted to protocols that optimally combine the results from several methods. These protocols will be made available to the scientific community via the Web, and the community will be introduced to them through open workshops and training sessions.

Fields of science (EuroSciVoc)

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Keywords

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Topic(s)

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Call for proposal

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FP6-2002-LIFESCIHEALTH
See other projects for this call

Funding Scheme

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STREP - Specific Targeted Research Project

Coordinator

UNIVERSITÉ LIBRE DE BRUXELLES
EU contribution
No data
Total cost

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Participants (10)

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