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Gladstone scientists announce new version of
bioinformatics software program
A team of scientists at the J. David Gladstone
Institutes has unveiled a new version of GenMAPP, a widely used software program
designed to help biomedical scientists view and analyze genome-scale data sets
in the context of biological pathways.
GenMAPP 2.0, short for Gene Map Annotator and Pathway Profiler, marks the first
major revision of the program, which was developed and launched by Gladstone
scientists in 2002. With the program having been freely available at
www.GenMAPP.org to all researchers since its debut, it has now become a standard
means of depicting and sharing biological data and pathway information.
As GenMAPP developer Bruce Conklin, MD, points out, a single genomics experiment
can yield enough data to fill a large telephone book, and methods for organizing
and analyzing the data are desperately needed.
"Genomic experiments can easily overwhelm a scientist with data," explained
Conklin, an investigator at the Gladstone Institute of Cardiovascular Disease
and UCSF associate professor of medicine, molecular and cellular pharmacology. "GenMAPP
organizes the data by biological process, a scheme that most biologists
understand, and allows us to find new connections that we would not have seen
otherwise."
From its beginnings, GenMAPP has been designed for viewing and analyzing gene
expression data on biological pathways and other groupings of genes. GenMAPP 2.0
incorporates a variety of new features, many of them suggested by users,
including:
-- A flexible format that accepts many different gene ID systems from resources
for many species, including human, Drosophila (fruit fly), mouse, rat, zebrafish,
C. elegans (a microscopic roundworm), and S. cerevisiae (yeast).
-- Species-specific gene databases that show relationships between the various
gene ID systems in the database. For example, genes on the MAPP (GenMAPP files
that represent biological pathways or groupings of genes) may use a single
common ID type and the expression data sets may be annotated with a completely
different ID type, but GenMAPP provides an internal database that can connect
the two gene IDs.
-- Assistance in creating unique Gene Databases for any species, as well as
customization of existing Gene Databases.
-- The ability to export (as HTML) entire sets of MAPPs, including information
from the researcher's Expression Dataset, enabling convenient, interactive
display of data on web sites.
By viewing genes in the context of a known biological process, GenMAPP makes it
possible to make sense of data that might otherwise be difficult to interpret.
The most widespread alternative analytical method, hierarchical clustering,
groups genes without knowledge of the gene's function, but it can miss small
changes in expression. In fact, the two methods complement each other in
interpreting biological data.
GenMAPP was developed with grant support from the NIH. Any scientist can use it
to modify MAPPs to fit other hypotheses, to design new pathways, or to share the
data with others in the research community.
The GenMAPP site has logged over 10,000 registrations to download the program,
and GenMAPP has been cited as a resource in upwards of 50 publications to date.
"We have been very pleased with the widespread acceptance and use of GenMAPP,"
said Conklin. "This new version was created in response to comments from those
many users, and I am excited about what it will do for biomedical research here
and around the world."
The J. David Gladstone Institutes is an independent, nonprofit biomedical
research institution affiliated with UCSF. For further information, visit
http://www.gladstone.ucsf.edu.
Contact: John Watson
jwatson@gladstone.ucsf.edu
415-734-2019
University of California - San Francisco
http://www.ucsf.edu
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