Orozco-Arias S. auteur aut IRD Jaimes P. A. auteur aut IRD Candamil M. S. auteur aut IRD Jimenez-Varon C. F. auteur aut IRD Tabares-Soto R. auteur aut IRD Isaza G. auteur aut IRD Guyot Romain auteur aut IRD text journalArticle eng text/pdf reformatted digital access Long terminal repeat (LTR) retrotransposons are mobile elements that constitute the major fraction of most plant genomes. The identification and annotation of these elements via bioinformatics approaches represent a major challenge in the era of massive plant genome sequencing. In addition to their involvement in genome size variation, LTR retrotransposons are also associated with the function and structure of different chromosomal regions and can alter the function of coding regions, among others. Several sequence databases of plant LTR retrotransposons are available for public access, such as PGSB and RepetDB, or restricted access such as Repbase. Although these databases are useful to identify LTR-RTs in new genomes by similarity, the elements of these databases are not fully classified to the lineage (also called family) level. Here, we present InpactorDB, a semi-curated dataset composed of 130,439 elements from 195 plant genomes (belonging to 108 plant species) classified to the lineage level. This dataset has been used to train two deep neural networks (i.e., one fully connected and one convolutional) for the rapid classification of these elements. In lineage-level classification approaches, we obtain up to 98% performance, indicated by the F1-score, precision and recall scores. specialized LTR retrotransposons machine learning deep neural networks bioinformatics plant genomes genomics InpactorDB 020 122 12 2 190 [17 p.] 2021 https://www.documentation.ird.fr/hor/fdi:010081058 10.3390/genes12020190 [F B010081058] https://www.documentation.ird.fr/hor/fdi:010081058 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers21-03/010081058.pdf IRD - Base Horizon / Pleins textes 2021-04-01 2024-11-08 fdi:010081058 fre