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ProGeRF: proteome and genome repeat finder utilizing a fast parallel hash function.

Lopes Rda S, Moraes WJ, Rodrigues Tde S, Bartholomeu DC - Biomed Res Int (2015)

Bottom Line: ProGeRF is a web site for extracting repetitive regions from genome and proteome sequences.It was designed to be efficient, fast, and accurate and primarily user-friendly web tool allowing many ways to view and analyse the results.ProGeRF (Proteome and Genome Repeat Finder) is freely available as a stand-alone program, from which the users can download the source code, and as a web tool.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, Federal University of Mato Grosso, 78600-000 Barra do Garcas, MT, Brazil.

ABSTRACT
Repetitive element sequences are adjacent, repeating patterns, also called motifs, and can be of different lengths; repetitions can involve their exact or approximate copies. They have been widely used as molecular markers in population biology. Given the sizes of sequenced genomes, various bioinformatics tools have been developed for the extraction of repetitive elements from DNA sequences. However, currently available tools do not provide options for identifying repetitive elements in the genome or proteome, displaying a user-friendly web interface, and performing-exhaustive searches. ProGeRF is a web site for extracting repetitive regions from genome and proteome sequences. It was designed to be efficient, fast, and accurate and primarily user-friendly web tool allowing many ways to view and analyse the results. ProGeRF (Proteome and Genome Repeat Finder) is freely available as a stand-alone program, from which the users can download the source code, and as a web tool. It was developed using the hash table approach to extract perfect and imperfect repetitive regions in a (multi)FASTA file, while allowing a linear time complexity.

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Related in: MedlinePlus

Creating repetitive element hash table: Step  1: sliding window maps each motif of the sequence for a position in the repetitive element hash table and sets value 1 to mapped position, and add or remove the sliding window to single bucket; Step  2: check whether the current sliding window is a degeneration of some motif ever recorded in buckets of REHT; Step  3: for each existing degeneration in the buffer the function h() is applied and then converted into an integer k and, soon after, Step  1 is performed.
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Related In: Results  -  Collection


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fig3: Creating repetitive element hash table: Step  1: sliding window maps each motif of the sequence for a position in the repetitive element hash table and sets value 1 to mapped position, and add or remove the sliding window to single bucket; Step  2: check whether the current sliding window is a degeneration of some motif ever recorded in buckets of REHT; Step  3: for each existing degeneration in the buffer the function h() is applied and then converted into an integer k and, soon after, Step  1 is performed.

Mentions: Creating repetitive elements hash table (REHT), illustrated by Figure 3: for each sliding window Qp, where p = 1,2, 3,…, n − j + 1, do the following:


ProGeRF: proteome and genome repeat finder utilizing a fast parallel hash function.

Lopes Rda S, Moraes WJ, Rodrigues Tde S, Bartholomeu DC - Biomed Res Int (2015)

Creating repetitive element hash table: Step  1: sliding window maps each motif of the sequence for a position in the repetitive element hash table and sets value 1 to mapped position, and add or remove the sliding window to single bucket; Step  2: check whether the current sliding window is a degeneration of some motif ever recorded in buckets of REHT; Step  3: for each existing degeneration in the buffer the function h() is applied and then converted into an integer k and, soon after, Step  1 is performed.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4355816&req=5

fig3: Creating repetitive element hash table: Step  1: sliding window maps each motif of the sequence for a position in the repetitive element hash table and sets value 1 to mapped position, and add or remove the sliding window to single bucket; Step  2: check whether the current sliding window is a degeneration of some motif ever recorded in buckets of REHT; Step  3: for each existing degeneration in the buffer the function h() is applied and then converted into an integer k and, soon after, Step  1 is performed.
Mentions: Creating repetitive elements hash table (REHT), illustrated by Figure 3: for each sliding window Qp, where p = 1,2, 3,…, n − j + 1, do the following:

Bottom Line: ProGeRF is a web site for extracting repetitive regions from genome and proteome sequences.It was designed to be efficient, fast, and accurate and primarily user-friendly web tool allowing many ways to view and analyse the results.ProGeRF (Proteome and Genome Repeat Finder) is freely available as a stand-alone program, from which the users can download the source code, and as a web tool.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, Federal University of Mato Grosso, 78600-000 Barra do Garcas, MT, Brazil.

ABSTRACT
Repetitive element sequences are adjacent, repeating patterns, also called motifs, and can be of different lengths; repetitions can involve their exact or approximate copies. They have been widely used as molecular markers in population biology. Given the sizes of sequenced genomes, various bioinformatics tools have been developed for the extraction of repetitive elements from DNA sequences. However, currently available tools do not provide options for identifying repetitive elements in the genome or proteome, displaying a user-friendly web interface, and performing-exhaustive searches. ProGeRF is a web site for extracting repetitive regions from genome and proteome sequences. It was designed to be efficient, fast, and accurate and primarily user-friendly web tool allowing many ways to view and analyse the results. ProGeRF (Proteome and Genome Repeat Finder) is freely available as a stand-alone program, from which the users can download the source code, and as a web tool. It was developed using the hash table approach to extract perfect and imperfect repetitive regions in a (multi)FASTA file, while allowing a linear time complexity.

Show MeSH
Related in: MedlinePlus