A resource-frugal probabilistic dictionary and applications in bioinformatics - Inria - Institut national de recherche en sciences et technologies du numérique
Journal Articles Discrete Applied Mathematics Year : 2020

A resource-frugal probabilistic dictionary and applications in bioinformatics

Abstract

Indexing massive data sets is extremely expensive for large scale problems. In many fields, huge amounts of data are currently generated, however extracting meaningful information from voluminous data sets, such as computing similarity between elements, is far from being trivial. It remains nonetheless a fundamental need. This work proposes a probabilistic data structure based on a minimal perfect hash function for indexing large sets of keys. Our structure out-compete the hash table for construction, query times and for memory usage, in the case of the indexation of a static set. To illustrate the impact of algorithms performances, we provide two applications based on similarity computation between collections of sequences, and for which this calculation is an expensive but required operation. In particular, we show a practical case in which other bioinformatics tools fail to scale up the tested data set or provide lower recall quality results.
Fichier principal
Vignette du fichier
short_read_connectors.pdf (323 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01322440 , version 1 (27-05-2016)

Identifiers

Cite

Camille Marchet, Lolita Lecompte, Antoine Limasset, Lucie Bittner, Pierre Peterlongo. A resource-frugal probabilistic dictionary and applications in bioinformatics. Discrete Applied Mathematics, 2020, 92-102 (Volume 274), ⟨10.1016/j.dam.2018.03.035⟩. ⟨hal-01322440⟩
572 View
322 Download

Altmetric

Share

More