The Genetics & Genomic Medicine Service at Brigham and Women’s Hospital provides care for individuals in need of genetic risk assessment, genetic testing, genetic diagnosis, genetic counseling, or management of genetic disease. We offer exome and genome sequencing as a clinical service to patients for diagnosis and clinical management. For more information, please visit our website.
The Division of Genetics has developed many useful software tools. Here are some of our more popular programs:
Mass Spectrometry Driven BLAST: a specialized BLAST based protocol developed for identification of proteins by sequence similarity searchers using peptide sequences prodcued by the interpretation of tandem mass spectra
Sunyaev Lab/Bork Group
This program may be used to predict the impact of an amino acid substitution on the structure and function of a protein using straightforward physical and comparative considerations.
Identification of polymorphic mouse SNPs with Restriction Fragment Length Polymorphism: This program extracts region specific SNPs from the NCBI mouse database that are informative between specified mouse strains AND can be assayed by detection of restriction fragment length polymorphisms.
This program evaluates the likelihood that a given genomic region is a cisregulatory module for an input set of transcription factors according to its degree of: (1) homotypic site clustering; (2) heterotypic site clustering; and (3) evolutionary conservation across multiple genomes.
Reference: Philippakis AA, He FS, Bulyk ML. Modulefinder: a tool for computational discovery of cis regulatory modules. Pac Symp Biocomput. 2005; 519-30.
This software performs automated motif searching using four different profile-based motif finders, including AlignACE, MDscan, BioProspector and MEME. We anticipated that using all four of these motif finders might allow the user to combine the strengths of their different algorithms.
Reference: Huber BR and Bulyk ML. Meta-analysis discovery of tissue-specific DNA sequence motifs from mammalian gene expression data. BMC Bioinformatics 2006 Apr 27; 7: 229.