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P S Novichkov

Publications and source records attributed to P S Novichkov.

4 recordsLinked to original sources
PubMed2001

Pro-Frame: similarity-based gene recognition in eukaryotic DNA sequences with errors.

Performance of existing algorithms for similarity-based gene recognition in eukaryotes drops when the genomic DNA has been sequenced with errors. A modification of the spliced alignment algorithm allows for gene recognition in sequences with errors, in particular frameshifts. It tolerates up to 5% of sequencing errors without considerable drop of prediction reliability when a sufficiently close homologous protein is available (normalized evolutionary distance similarity score 50% or higher).

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PubMed2001

Gene recognition in eukaryotic DNA by comparison of genomic sequences.

MOTIVATION: Sequencing of complete eukaryotic genomes and large syntenic fragments of genomes makes it possible to apply genomic comparison for gene recognition. RESULTS: This paper describes a spliced alignment algorithm that aligns candidate exon chains of two homologous genomic sequence fragments from different species. The algorithm is implemented in Pro-Gen software. Unlike other algorithms, Pro-Gen does not assume conservation of the exon-intron structure. Amino acid sequences obtained by the formal translation of candidate exons are aligned instead of nucleotide sequences, which allows for distant comparisons. The algorithm was tested on a sample of human-mammal (mouse), human-vertebrate (Xenopus ) and human-invertebrate (Drosophila ) gene pairs. Surprisingly, the best results, 97-98% correlation between the actual and predicted genes, were obtained for more distant comparisons, whereas the correlation on the human-mouse sample was only 93%. The latter value increases to 95% if conservation of the exon-intron structure is assumed. This is caused by a large amount of sequence conservation in non-coding regions of the human and mouse genes probably due to regulatory elements. AVAILABILITY: Pro-Gen v. 3.0 is available to academic researchers free of charge at http://www.anchorgen.com/pro_gen/pro_gen.html.

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PubMed2000

Comparative analysis of regulatory patterns in bacterial genomes.

Recognition of transcription regulatory sites in bacterial genomes is a notoriously difficult problem. There are no algorithms capable of making reliable predictions even for well-studied sites such as the CRP (cyclic AMP receptor protein) box. However, availability of complete bacterial genomes makes it possible to make reliable predictions with bad rules. This comparative approach is based on the assumption that sets of co-regulated genes are conserved in related bacteria. Thus true sites occur upstream of orthologous genes, whereas false candidates are scattered at random. This means not only that knowledge about regulation in well-studied genomes can be transferred to newly sequenced ones, but also that new members of regulons can be found. This paper reviews several recent studies. In particular, a detailed analysis of catabolite repression in gamma-purple bacteria is presented.

Algorithms↗