Skip to main navigation Skip to search Skip to main content

Comparación de modelos novedosos de proximidad en quimioinformática

Translated title of the contribution: Comparison of novelproximity models in Chemoinformatics
  • Oscar Miguel Rivera Borroto*
  • , Yoandy Hernández Díaz
  • , José Manuel García De La Vega
  • , Ricardo Del Corazón Grau Ábalo
  • , Yovani Marrero Ponce
  • *Corresponding author for this work
  • Universidad Central Marta Abreu de Las Villas
  • Universidad Autónoma de Madrid

Research output: Contribution to journalArticlepeer-review

Abstract

This work comprises the computational implementation in the Java environment of 21 proximity models to be used in simulated experiments of similarity searching, nine out of which are novel in Chemoinformatics since they come from the psychology field, and other 12 are measures already established in the specialized literature. Afterwards, the similarity measures were compared and assessed at the "early retrieval" using nine data sets from medicinal chemistry, represented by machine learning-selected real descriptors, and one efficient matching algorithm. Results show that in average trends the new models perform superiorly with respect to the reference ones, and more than half of them are among the top-10 models.

Translated title of the contributionComparison of novelproximity models in Chemoinformatics
Original languageSpanish
Pages (from-to)272-277
Number of pages6
JournalAfinidad
Volume69
Issue number560
StatePublished - Oct 2012
Externally publishedYes

Fingerprint

Dive into the research topics of 'Comparison of novelproximity models in Chemoinformatics'. Together they form a unique fingerprint.

Cite this