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ChemRecSys

ChemRecSys (Chemical Compounds Recommender System) is a system for recommending Chemical Compounds, integrating collaborative-filtering algorithms for implicit feedback (Alternating Least Squares (ALS) and Bayesian Personalized Ranking(BPR)), a content-based algorithm...
“BiOnt” a LASIGE paper @ ECIR 2020

“BiOnt” a LASIGE paper @ ECIR 2020

The academic paper “BiOnt: Deep Learning using Multiple Biomedical Ontologies for Relation Extraction”, co-authored by Diana Sousa and Francisco M. Couto (LASIGE researchers), was accepted at the 42nd European Conference on Information Retrieval (ECIR...

BiOnt

BiOnt is a system to perform relation extraction using a deep learning system. BiOnt, employs four types of biomedical ontologies, namely, the Gene Ontology, the Human Phenotype Ontology, the Human Disease Ontology, and the Chemical Entities of Biological Interest,...
5th LASIGE workshop (2020)

5th LASIGE workshop (2020)

Yesterday, February 13, LASIGE hosted its 5th annual workshop, featuring a variety of activities, and begun with four talks: Andreia Santos (psychologist at GAPSI, FCUL) – ” How to live together with rejection?” Marta Daniela Santos and Sílvio Mendes...
LASIGE’s paper published by Nature Publishing Group

LASIGE’s paper published by Nature Publishing Group

The paper “Identification of biological mechanisms underlying a multidimensional ASD phenotype using machine learning”, authored by Francisco M. Couto and Muhammad Asif (LASIGE integrated researchers), among others, was published at Translational...