Bioinformatics of Genome Regulation and Structure by V. G. Levitsky, A. V. Katokhin, O. A. Podkolodnaya, D. P.

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By V. G. Levitsky, A. V. Katokhin, O. A. Podkolodnaya, D. P. Furman (auth.), Nikolay Kolchanov, Ralf Hofestaedt (eds.)

Bioinformatics of Genome law and Structurecovers:

-regulatory genomic sequences: databases, wisdom bases, desktop research, modeling, and popularity;
-large-scale genome research and useful annotation;
-gene constitution detection and prediction;
-comparative and evolutionary genomics;
-computer research of genome polymorphism and evolution; laptop research and modeling of transcription, splicing, and translation; structural computational biology: structure-function association of genomic DNA, RNA, and proteins;
-gene networks, sign transduction pathways, and genetically managed metabolic pathways: ideas of association, operation, and evolution;
-data warehousing, wisdom discovery and information mining; and,
-analysis of uncomplicated styles of genome operation, association, and evolution.

The facts provided can be utilized whereas fixing a variety of difficulties, either simple and utilized, in a number of instructions of molecular biology, molecular genetics, biotechnology, pharmacogenetics, pharmacology, and adjoining fields of drugs, veterinary, and agrobiology.

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6, 297, blood, copia, Dm412 (mdg2), gypsy, HMSBeagle, mdgl, mdg3, roo (Bl04), tirant, and yoyo. Further, we will call insertion regions those sequences of host DNA that contain target sites and the flanking sequences. The LTR retrotransposons are classified into three groups according to the variation pattern of mononucleotide context and CPCP of the insertion regions. Each group displays its own profiles of local CPCP of dinucleotides located both in the target sites and outside. A set of these CPCP may determine choosing of the region as preferential for integration of a particular element.

In that way, functional description was determined for each tRNA-like sequence. Implementation of the method on personal computer showed that the computational time it requires is unsatisfactorily long. This problem becomes clear, if we remember its most time-consuming process-the Monte-Carlo simulations. The way out was found in using computational cluster for implementation of this algorithm. To provide higher portability among computer platforms, the program complex was written in C language using MPI interface for interprocess communications.

L. G. 4* 1Institute of Cytology & Genetics, Siberian Branch of the Russian Academy of Sciences, prosp. ru; 2 Ugra Research Institute of Information Technologies, ul. Mira ISI, Khanty-Mansyisk, 6280I I Russia; 3National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bldg. 38A, Bethesda, MD 20894, USA; 4Novosibirsk State University, ul. Pirogova 2, Novosibirsk, 630090 Russia Corresponding author * Abstract A new method for the recognition of type 2 promoters in the eukaryotic tRNA genes, which takes into consideration not only nucleotide distribution at individual box positions, but also the multiple interactions between the different parts of the A and B boxes, is proposed.

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