@article{fdi:010081058,
  title = {{I}npactor{DB} : a classified lineage-level plant {LTR} retrotransposon reference library for free-alignment methods based on machine learning},
  author = {{O}rozco-{A}rias, {S}. and {J}aimes, {P}. {A}. and {C}andamil, {M}. {S}. and {J}imenez-{V}aron, {C}. {F}. and {T}abares-{S}oto, {R}. and {I}saza, {G}. and {G}uyot, {R}omain},
  editor = {},
  language = {{ENG}},
  abstract = {{L}ong terminal repeat ({LTR}) retrotransposons are mobile elements that constitute the major fraction of most plant genomes. {T}he identification and annotation of these elements via bioinformatics approaches represent a major challenge in the era of massive plant genome sequencing. {I}n 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. {S}everal sequence databases of plant {LTR} retrotransposons are available for public access, such as {PGSB} and {R}epet{DB}, or restricted access such as {R}epbase. {A}lthough these databases are useful to identify {LTR}-{RT}s in new genomes by similarity, the elements of these databases are not fully classified to the lineage (also called family) level. {H}ere, we present {I}npactor{DB}, a semi-curated dataset composed of 130,439 elements from 195 plant genomes (belonging to 108 plant species) classified to the lineage level. {T}his 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. {I}n lineage-level classification approaches, we obtain up to 98% performance, indicated by the {F}1-score, precision and recall scores.},
  keywords = {{LTR} retrotransposons ; machine learning ; deep neural networks ; bioinformatics ; plant genomes ; genomics ; {I}npactor{DB}},
  booktitle = {},
  journal = {{G}enes},
  volume = {12},
  numero = {2},
  pages = {190 [17 p.]},
  year = {2021},
  DOI = {10.3390/genes12020190},
  URL = {https://www.documentation.ird.fr/hor/fdi:010081058},
}