Serbia’s PM believe Russia concerned by instability in BalkansWorld March 28, 3:40
About 3,000 troops to take part in missile force’s drills in central RussiaMilitary & Defense March 27, 20:55
Russian footballers must ‘force own game’ on Belgium in Sochi friendly match — coachSport March 27, 20:34
UN denies rumors of Staffan de Mistura’s resignationWorld March 27, 20:16
Prominent Russian lawyer vows to look into detention of journalists during Moscow ralliesRussian Politics & Diplomacy March 27, 20:05
Kremlin says world chess tournaments should go as planned despite FIDE’s presidential rowSport March 27, 19:32
Ukrainian politician says Kiev turns deaf ear to public pleas to end Donbass blockadeWorld March 27, 19:17
Serbia to get Russian MiG-29 fighter jets 'within weeks'Military & Defense March 27, 18:51
Putin wants Russian Guard to ensure security at FIFA World CupSport March 27, 18:35
MOSCOW, January 13. /TASS/. A team of scientists from Germany, the United States and Russia have developed an algorithm to automate the process of searching for genes and making it more efficient, the Moscow Institute of Physics and Technology said in a press release on Wednesday.
"The new development combines the advantages of the most advanced tools for working with genomic data", the institute said.
The algorithm proposed by the Russian scientists and their colleagues determines which regions in the DNA are genes and which are not. The algorithm determines the most probable division of a genome into coding and noncoding regions. The developed program has already been downloaded by more than 1500 different centers and laboratories. The example running time of BRAKER1 on a single processor is about 17.5 hours for training and the prediction of genes in a genome with a length of 120 megabases. In the future the algorithm may be able to function faster due to parallel processing.
Annotating genomes or determining which particular DNA molecules are used to synthesize RNA and proteins is one of the most important area of bioinformatics. Many studied do not need information about the entire DNA (which is around 2 meters long for a single human cell), but about its most informative part - genes. In the future, this data will help doctors to diagnose complex diseases such as heart disease, diabetes, and cancer.
The paper describing the algorithm was published recently in the journal Bioinformatic.