Can We Replace Reads by Numeric Signatures? Lyndon Fingerprints as Representations of Sequencing Reads for Machine Learning

Autor: Paola Bonizzoni, Alessia Petescia, Rosalba Zizza, Rocco Zaccagnino, Raffaella Rizzi, Jens Stoye, Clelia De Felice, Yuri Pirola

Publikováno v: ORCID
BOA-Bicocca Open Archive
Publications at Bielefeld University
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Algorithms for Computational Biology
Algorithms for Computational Biology (AlCoB 2021)
Algorithms for Computational Biology ISBN: 9783030744311
AlCoB
PUB-Publications at Bielefeld University

Representations of biological sequences facilitating sequence comparison are crucial in several bioinformatics tasks. Recently, the Lyndon factorization has been proved to preserve common factors in overlapping reads, thus leading to the idea of usin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4458c18e31d61dc5ddf9e2736d550dc9

Numeric Lyndon-based feature embedding of sequencing reads for machine learning approaches

Autor: Bonizzoni, Paola, Costantini, Matteo, De Felice, Clelia, Petescia, Alessia, Pirola, Yuri, Previtali, Marco, Rizzi, Raffaela, Stoye, Jens, Zaccagnino, Rocco, Zizza, Rosalba

Publikováno v: arXiv.org e-Print Archive
Publications at Bielefeld University
Datacite

Feature embedding methods have been proposed in the literature to represent sequences as numeric vectors to be used in some bioinformatics investigations, such as family classification and protein structure prediction. Recent theoretical results show

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::439b2ffca16b6597bcc97329f0a0277a