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PathRacer : Racing Profile HMM Paths on Assembly Graph. / Shlemov, Alexander; Korobeynikov, Anton.

6th International Conference on Algorithms for Computational Biology. ed. / Carlos Martín-Vide; Miguel A. Vega-Rodríguez; Ian Holmes. Springer Nature, 2019. p. 80-94 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11488 LNBI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Shlemov, A & Korobeynikov, A 2019, PathRacer: Racing Profile HMM Paths on Assembly Graph. in C Martín-Vide, MA Vega-Rodríguez & I Holmes (eds), 6th International Conference on Algorithms for Computational Biology. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11488 LNBI, Springer Nature, pp. 80-94, 6th International Conference on Algorithms for Computational Biology, AlCoB 2019, Berkeley, United States, 28/05/19. https://doi.org/10.1007/978-3-030-18174-1_6

APA

Shlemov, A., & Korobeynikov, A. (2019). PathRacer: Racing Profile HMM Paths on Assembly Graph. In C. Martín-Vide, M. A. Vega-Rodríguez, & I. Holmes (Eds.), 6th International Conference on Algorithms for Computational Biology (pp. 80-94). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11488 LNBI). Springer Nature. https://doi.org/10.1007/978-3-030-18174-1_6

Vancouver

Shlemov A, Korobeynikov A. PathRacer: Racing Profile HMM Paths on Assembly Graph. In Martín-Vide C, Vega-Rodríguez MA, Holmes I, editors, 6th International Conference on Algorithms for Computational Biology. Springer Nature. 2019. p. 80-94. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-18174-1_6

Author

Shlemov, Alexander ; Korobeynikov, Anton. / PathRacer : Racing Profile HMM Paths on Assembly Graph. 6th International Conference on Algorithms for Computational Biology. editor / Carlos Martín-Vide ; Miguel A. Vega-Rodríguez ; Ian Holmes. Springer Nature, 2019. pp. 80-94 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{9ee265fb536d45bb8ebabb3e286d42d1,
title = "PathRacer: Racing Profile HMM Paths on Assembly Graph",
abstract = "Recently large databases containing profile Hidden Markov Models (pHMMs) emerged. These pHMMs may represent the sequences of antibiotic resistance genes, or allelic variations amongst highly conserved housekeeping genes used for strain typing, etc. The typical application of such a database includes the alignment of contigs to pHMM hoping that the sequence of gene of interest is located within the single contig. Such a condition is often violated for metagenomes preventing the effective use of such databases. We present PathRacer—a novel standalone tool that aligns profile HMM directly to the assembly graph (performing the codon translation on fly for amino acid pHMMs). The tool provides the set of most probable paths traversed by a HMM through the whole assembly graph, regardless whether the sequence of interested is encoded on the single contig or scattered across the set of edges, therefore significantly improving the recovery of sequences of interest even from fragmented metagenome assemblies.",
keywords = "Graph alignment, Profile HMM, Set of most probable paths",
author = "Alexander Shlemov and Anton Korobeynikov",
year = "2019",
month = may,
day = "25",
doi = "10.1007/978-3-030-18174-1_6",
language = "English",
isbn = "9783030181734",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "80--94",
editor = "Carlos Mart{\'i}n-Vide and Vega-Rodr{\'i}guez, {Miguel A.} and Ian Holmes",
booktitle = "6th International Conference on Algorithms for Computational Biology",
address = "Germany",
note = "6th International Conference on Algorithms for Computational Biology, AlCoB 2019 ; Conference date: 28-05-2019 Through 30-05-2019",

}

RIS

TY - GEN

T1 - PathRacer

T2 - 6th International Conference on Algorithms for Computational Biology, AlCoB 2019

AU - Shlemov, Alexander

AU - Korobeynikov, Anton

PY - 2019/5/25

Y1 - 2019/5/25

N2 - Recently large databases containing profile Hidden Markov Models (pHMMs) emerged. These pHMMs may represent the sequences of antibiotic resistance genes, or allelic variations amongst highly conserved housekeeping genes used for strain typing, etc. The typical application of such a database includes the alignment of contigs to pHMM hoping that the sequence of gene of interest is located within the single contig. Such a condition is often violated for metagenomes preventing the effective use of such databases. We present PathRacer—a novel standalone tool that aligns profile HMM directly to the assembly graph (performing the codon translation on fly for amino acid pHMMs). The tool provides the set of most probable paths traversed by a HMM through the whole assembly graph, regardless whether the sequence of interested is encoded on the single contig or scattered across the set of edges, therefore significantly improving the recovery of sequences of interest even from fragmented metagenome assemblies.

AB - Recently large databases containing profile Hidden Markov Models (pHMMs) emerged. These pHMMs may represent the sequences of antibiotic resistance genes, or allelic variations amongst highly conserved housekeeping genes used for strain typing, etc. The typical application of such a database includes the alignment of contigs to pHMM hoping that the sequence of gene of interest is located within the single contig. Such a condition is often violated for metagenomes preventing the effective use of such databases. We present PathRacer—a novel standalone tool that aligns profile HMM directly to the assembly graph (performing the codon translation on fly for amino acid pHMMs). The tool provides the set of most probable paths traversed by a HMM through the whole assembly graph, regardless whether the sequence of interested is encoded on the single contig or scattered across the set of edges, therefore significantly improving the recovery of sequences of interest even from fragmented metagenome assemblies.

KW - Graph alignment

KW - Profile HMM

KW - Set of most probable paths

UR - http://www.scopus.com/inward/record.url?scp=85066111513&partnerID=8YFLogxK

UR - http://www.mendeley.com/research/pathracer-racing-profile-hmm-paths-assembly-graph

U2 - 10.1007/978-3-030-18174-1_6

DO - 10.1007/978-3-030-18174-1_6

M3 - Conference contribution

AN - SCOPUS:85066111513

SN - 9783030181734

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 80

EP - 94

BT - 6th International Conference on Algorithms for Computational Biology

A2 - Martín-Vide, Carlos

A2 - Vega-Rodríguez, Miguel A.

A2 - Holmes, Ian

PB - Springer Nature

Y2 - 28 May 2019 through 30 May 2019

ER -

ID: 42676722