Semantic similarity for automatic classification of chemical compounds.
With the increasing amount of data made available in the chemical field, there is a strong need for systems capable of comparing and classifying chemical compounds in an efficient and effective way. The best approaches existing today are based on the structure-activity relationship premise, which st...
Enregistré dans:
Auteurs principaux: | João D Ferreira, Francisco M Couto |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Public Library of Science (PLoS)
2010
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/96bb4f1feea84c7abc362d62a8be458e |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Semantic similarity in biomedical ontologies.
par: Catia Pesquita, et autres
Publié: (2009) -
Shape similarity, better than semantic membership, accounts for the structure of visual object representations in a population of monkey inferotemporal neurons.
par: Carlo Baldassi, et autres
Publié: (2013) -
Cross-over between discrete and continuous protein structure space: insights into automatic classification and networks of protein structures.
par: Alberto Pascual-García, et autres
Publié: (2009) -
Adventures in semantic publishing: exemplar semantic enhancements of a research article.
par: David Shotton, et autres
Publié: (2009) -
Machine learning approach for automatic recognition of tomato-pollinating bees based on their buzzing-sounds.
par: Alison Pereira Ribeiro, et autres
Publié: (2021)