We have developed a suite of computational tools that assist in
the design, implementation and analysis of UT Southwestern’s
research in the genetic causes of heart disease. Our software
and databases can be applied to all aspects of genomic analysis
to speed the discovery process. (i.e gene discovery, microarray
analysis, text data mining, pre-computed reagents, design of genotyping
and linkage experiments)
There were
two components to this educational event:
- An
online educational module
that gave an overview of our suite of computational tools.
-
A live, online conference
demonstrating two of our computational tools and a question
and answer session answering any questions someone may have
regarding our software and databases.
Online Educational Module
The
Bioinformatics Resources Educational Module is available online.
This is worth a look even if you were unable to attend the live,
online conference.
Live, Online WebEx™ Conference
As our first
attempt in this format, we felt the online conference was succesful.
There was good interaction between the speaker an the attendees
and the attendee respnses were positive. We will attempt to
build on this format for educational activities in the near
future.
The
live, online conference will demonstrated ELXR and eTBLAST,
two tools from our computational suite of tools.
ELXR
is one of our workhorse genomic analysis tools. It is both a
service and a pre-computed set of reagents that are valuable
to laboratory work. ELXR has pre-computed all the necessary
information to allow anyone who wants to study any gene or any
exon to no longer go through the painstaking effort of correctly
gathering the gene sequence, identifying the exon of interest,
and then designing primers to study it. Instead, by simply visiting
our website, anyone can access primer designs that have been
proven in over 6,000 experiments to work very well.
Additionally, one of our data mining codes is a text similarity
code called eTBLAST. This tool is similar to currently available
internet search engines that use keywords and phrases, but eTBLAST
can take as input natural text, from which it extracts keywords
and phrases, determines their relevance and compares them to
keywords and phrases previously extracted from all Medline biomedical
abstracts. It then groups all these results and employs a dynamic
programming algorithm to rank the top 200 returned results to
present the optimum order to the user via a web browser. We
found that many researchers use eTBLAST in a variety of ways
and so we offer it as a free academic service.
See the following for the materials
and examples presented during the conference.
