Scientists design search engine to identify functionally related genes -
Scientists at the Research Institute Virginia Tech Carilion genes build search engine functionally related
A border is deep within our cells.
Our bodies are as vast as the oceans and space, consisting of a dizzying number of different cell types. Exploration is fine, but the genes that make every cell and unique fabrics remained largely obscure.
that changes with the help of a team led by Gregorio Valdez, assistant professor at the Research Institute Virginia Tech Carilion.
Valdez and his team designed a search engine - called EvoCor -. which identifies genes that are functionally related
name, a portmanteau of "evolution" and "correlation" points to the idea that genes with a similar pattern of history and expression of evolution have evolved together to control a specific biological process.
project, describes in May in the journal Nucleic Acids Research , can help medical scientists find ways to treat diseases that often have a genetic component, such as cancer or disease Alzheimer
scientific types the name of a gene in a search box, and SIFT EvoCor quickly through the history of the evolution of all mapped genes -. human. and otherwise
EvoCor then compares the pattern of expression of all the genes to generate a list of candidate genes that work together with the query gene lead to a cellular process - to generate more energy for the cell to clearing cellular debris. The scientist can use this list to the next stage of research.
"This platform allows researchers to generate lists of candidate genes quickly and at no cost," said Valdez. "EvoCor should accelerate the discovery of complex molecular mechanisms that control key cellular processes, including those used to axon regeneration."
Most cellular functions - communication, division, death - the result of a gene tell a cell how it is supposed to behave.
Scientists study how a gene is expressed and functions to determine, for example, eye color. The issue becomes more complex when several genes with different functions are closely linked. Therein lies the problem. A researcher may start with a gene, but needs to know what other genes could play a role in influencing a particularly complex cellular function, such as the survival of neurons.
Once the other genes are known, the scientist can study strategically and their only function within the larger network of genes.
To identify candidate genes, scientists have relied on expensive and time-consuming biochemical approaches. EvoCor advantage of the wealth of publicly available genomic and gene expression data sets to generate a list of candidate genes.
"It is for the evolution," said James Dittmar, a Virginia Tech Carilion School fourth year medical student who is a member of Valdez laboratory and first author of the journal article. " We took advantage of almost 0 organizations with fully sequenced genomes to track and compare the history of the evolution of all human genes. "
combing through the 21,000 human genes already mapped 182 different genomes, and large sets of gene expression data all maintained by the National Institutes of Health is a huge task. EvoCor makes it much easier to manage.
"Scientists can now use EvoCor to take advantage of this huge amount of data available to the public to discover genes without prior knowledge of the network function," said Valdez.
When scientists understand each gene influencing a particular cell output, they will have more options for the development of therapies. In his own research, Valdez hopes to discover molecules that work to slow or stop the motor and cognitive disability caused by diseases and aging.
"We know of many genes that, when mutated, lead to disastrous results," Valdez said. "But these genes do not function alone. EvoCor identifies functional partners and these partners could be better targets for therapy."
EvoCor was developed in collaboration with Lauren McIver, Pawel Michalak, and Harold "Skip" Garner, all scientists of the Virginia Bioinformatics Institute at Virginia Tech.
Valdez and his team plan to change EvoCor further so it can make even more potent and specific predictions, which facilitates the way for researchers trekking the new frontier.
EmoticonEmoticon