Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Bastien Cazaux"'
Publikováno v:
Genome Biology, Vol 24, Iss 1, Pp 1-23 (2023)
Abstract It has been over a decade since the first publication of a method dedicated entirely to mapping long-reads. The distinctive characteristics of long reads resulted in methods moving from the seed-and-extend framework used for short reads to a
Externí odkaz:
https://doaj.org/article/f296d9beff9147898bdc9aaddd7aa3fd
Publikováno v:
Algorithms for Molecular Biology, Vol 15, Iss 1, Pp 1-7 (2020)
Abstract Recent large-scale community sequencing efforts allow at an unprecedented level of detail the identification of genomic regions that show signatures of natural selection. Traditional methods for identifying such regions from individuals’ h
Externí odkaz:
https://doaj.org/article/0f0e5cf0df3c442d90170e0f5346acb9
Publikováno v:
Algorithms for Molecular Biology, Vol 14, Iss 1, Pp 1-15 (2019)
Abstract Background We study a preprocessing routine relevant in pan-genomic analyses: consider a set of aligned haplotype sequences of complete human chromosomes. Due to the enormous size of such data, one would like to represent this input set with
Externí odkaz:
https://doaj.org/article/f184131ea832445884b76629a936afa6
Autor:
Benedikt Kirsch-Gerweck, Leonard Bohnenkämper, Michel T Henrichs, Jarno N Alanko, Hideo Bannai, Bastien Cazaux, Pierre Peterlongo, Joachim Burger, Jens Stoye, Yoan Diekmann
Genomic regions under positive selection harbour variation linked for example to adaptation. Most tools for detecting positively selected variants have computational resource requirements rendering them impractical on population genomic datasets with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d59660f5ce90353d37a056eb34510874
https://pub.uni-bielefeld.de/record/2969065
https://pub.uni-bielefeld.de/record/2969065
Motivation Seeking probabilistic motifs in a sequence is a common task to annotate putative transcription factor binding sites (TFBS). Useful motif representations include Position Weight Matrices (PWMs), dinucleotidic PWMs (di-PWMs), and Hidden Mark
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b047c359d9ff8b53e79496d8817b84c5
https://doi.org/10.1101/2022.11.08.515647
https://doi.org/10.1101/2022.11.08.515647
Publikováno v:
Algorithmica
Algorithmica, 2022, ⟨10.1007/s00453-022-01007-w⟩
Algorithmica, 2022, ⟨10.1007/s00453-022-01007-w⟩
We study the problem of matching a string in a labeled graph. Previous research has shown that unless the Orthogonal Vectors Hypothesis (OVH) is false, one cannot solve this problem in strongly sub-quadratic time, nor index the graph in polynomial ti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2276b3ccb5ffb9f82edea68957f1009
https://hal.science/hal-03934245
https://hal.science/hal-03934245
It has been ten years since the first publication of a method dedicated entirely to mapping third-generation sequencing long-reads. The unprecedented characteristics of this new type of sequencing data created a shift, and methods moved on from the s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e281078e2ddd447d67ca3ef73b31f9f
https://doi.org/10.1101/2022.05.21.492932
https://doi.org/10.1101/2022.05.21.492932
Publikováno v:
Bioinformatics
Motivation Variant calling workflows that utilize a single reference sequence are the de facto standard elementary genomic analysis routine for resequencing projects. Various ways to enhance the reference with pangenomic information have been propose
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b58ff8a6851d1d1463c3ed1636fb9ee8
http://hdl.handle.net/10138/338304
http://hdl.handle.net/10138/338304
Publikováno v:
22nd International Workshop on Algorithms in Bioinformatics (WABI 2022)
22nd International Workshop on Algorithms in Bioinformatics (WABI 2022), Sep 2022, Postdam, Germany. ⟨10.1101/2021.11.04.467355v1⟩
WABI 2022-22nd International Workshop on Algorithms in Bioinformatics
WABI 2022-22nd International Workshop on Algorithms in Bioinformatics, Sep 2022, Postdam, Germany. pp.25:1-25:15, ⟨10.4230/LIPIcs.WABI.2022.25⟩
22nd International Workshop on Algorithms in Bioinformatics (WABI 2022), Sep 2022, Postdam, Germany. ⟨10.1101/2021.11.04.467355v1⟩
WABI 2022-22nd International Workshop on Algorithms in Bioinformatics
WABI 2022-22nd International Workshop on Algorithms in Bioinformatics, Sep 2022, Postdam, Germany. pp.25:1-25:15, ⟨10.4230/LIPIcs.WABI.2022.25⟩
Motivation. To keep up with the scale of genomic databases, several methods rely on local sensitive hashing methods to efficiently find potential matches within large genome collections. Existing solutions rely on Minhash or Hyperloglog fingerprints
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45b3e19ddae2fd221c552dc0cc4e84d2
https://doi.org/10.1101/2021.11.04.467355
https://doi.org/10.1101/2021.11.04.467355
Publikováno v:
27th International Symposium, SPIRE 2020, Orlando, FL, USA, October 13–15, 2020, Proceedings
27th International Symposium on String Processing and Information Retrieval (SPIRE)
27th International Symposium on String Processing and Information Retrieval (SPIRE), Oct 2020, Orlando, FL, United States. pp.277-290, ⟨10.1007/978-3-030-59212-7_20⟩
String Processing and Information Retrieval ISBN: 9783030592110
SPIRE
27th International Symposium on String Processing and Information Retrieval (SPIRE)
27th International Symposium on String Processing and Information Retrieval (SPIRE), Oct 2020, Orlando, FL, United States. pp.277-290, ⟨10.1007/978-3-030-59212-7_20⟩
String Processing and Information Retrieval ISBN: 9783030592110
SPIRE
The hierarchical overlap graph (HOG for short) is an overlap encoding graph that efficiently represents overlaps from a given set P of n strings. A previously known algorithm constructs the HOG in \(O(\vert \vert P \vert \vert + n^2)\) time and \(O(\
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b1caa6a3f7354c1225fedbd3cd4cc4e1
https://hal-lirmm.ccsd.cnrs.fr/lirmm-03014336/document
https://hal-lirmm.ccsd.cnrs.fr/lirmm-03014336/document