Detail publikace

LTRFIND: A Novel Algorithm for Human de novo LTR Retrotransposons Identification

Originální název

LTRFIND: A Novel Algorithm for Human de novo LTR Retrotransposons Identification

Anglický název

LTRFIND: A Novel Algorithm for Human de novo LTR Retrotransposons Identification

Jazyk

en

Originální abstrakt

Modern LTR retrotransposons identification is mainly based on similarity searching using databases of known retroviruses. Nowadays, when various human genomes are available, this approach is not fast enough. Unlike the other species, human LTR retrotransposons are inactive and modified so similarity searches can hardly find these strongly mutated or previously unknown retroelements. In this paper, we present a novel algorithm for de novo identification of human LTR retrotransposons. Considering features of the human genome, we designed heuristic algorithm based on identification of long terminal repeats. Employ of exact sting match seed technique brings a very efficient search with reasonable sensitivity.

Anglický abstrakt

Modern LTR retrotransposons identification is mainly based on similarity searching using databases of known retroviruses. Nowadays, when various human genomes are available, this approach is not fast enough. Unlike the other species, human LTR retrotransposons are inactive and modified so similarity searches can hardly find these strongly mutated or previously unknown retroelements. In this paper, we present a novel algorithm for de novo identification of human LTR retrotransposons. Considering features of the human genome, we designed heuristic algorithm based on identification of long terminal repeats. Employ of exact sting match seed technique brings a very efficient search with reasonable sensitivity.

BibTex


@inproceedings{BUT107299,
  author="Karel {Sedlář} and Ivo {Provazník}",
  title="LTRFIND: A Novel Algorithm for Human de novo LTR Retrotransposons Identification",
  annote="Modern LTR retrotransposons identification is mainly based on similarity searching using databases of known retroviruses. Nowadays, when various human genomes are available, this approach is not fast enough. Unlike the other species, human LTR retrotransposons are inactive and modified so similarity searches can hardly find these strongly mutated or previously unknown retroelements. In this paper, we present a novel algorithm for de novo identification of human LTR retrotransposons. Considering features of the human genome, we designed heuristic algorithm based on identification of long terminal repeats. Employ of exact sting match seed technique brings a very efficient search with reasonable sensitivity.",
  address="LITERA",
  booktitle="Proceedings of the 20th Conference STUDENT EEICT 2014",
  chapter="107299",
  howpublished="print",
  institution="LITERA",
  year="2014",
  month="april",
  pages="242--246",
  publisher="LITERA",
  type="conference paper"
}