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MutDB: annotating human variation with functionally relevant data.

Sean D Mooney¹, Russ B Altman

¹Department of Genetics, Stanford Medical Informatics, Stanford University, 251 Campus Drive, MSOB X-215 Stanford, CA 94305-5479, USA. sdm@stanford.edu

Bioinformatics (Oxford, England)

|September 27, 2003

Summary

This summary is machine-generated.

MutDB is a new resource that helps identify single nucleotide polymorphisms (SNPs) that may affect protein function. It provides annotations and interactive maps to predict the functional impact of these genetic variations.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Single nucleotide polymorphisms (SNPs) are common genetic variations.
Understanding the functional impact of SNPs is crucial for disease research.
Existing resources may lack comprehensive functional annotations for disease-associated SNPs.

Purpose of the Study:

To develop a comprehensive database, MutDB, for annotating and analyzing SNPs.
To aid researchers in predicting the functional consequences of SNPs on protein products.
To provide interactive tools for visualizing and ranking the potential impact of genetic variations.

Main Methods:

Integrated protein structure and comparative genomic annotations.
Curated data from UCSC Annotated Genome and human RefSeq gene set.
Developed interactive mutation maps at gene and protein levels.
Utilized multiple sequence alignments for conservation-based functional impact ranking.

Main Results:

MutDB contains annotations for 8000 disease-associated mutations and SNPs.
The resource offers interactive mutation maps for detailed analysis.
Functional consequences of SNPs can be ranked based on evolutionary conservation.

Conclusions:

MutDB serves as a valuable resource for identifying functionally significant SNPs.
The database aids in understanding the link between genetic variation and protein function.
MutDB facilitates research into the genetic basis of diseases.