Alberto Paccanaro

发表

Markov Analysis of Protein Sequence Similarities

Chakra Chennubhotla, Alberto Paccanaro, 2003, WIRN.

A Recommender System Approach for Predicting Drug Side Effects

Alberto Paccanaro, Diego Galeano, A. Paccanaro, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Learning Distributed Representations by Mapping Concepts and Relations into a Linear Space

Geoffrey E. Hinton, Alberto Paccanaro, A. Paccanaro, 2000, ICML.

Drug cocktail selection for the treatment of chagas disease: A multi-objective approach

Luca Cernuzzi, Benjamín Barán, Miriam Rolon, 2017, 2017 XLIII Latin American Computer Conference (CLEI).

The Geometric Sparse Matrix Completion Model for Predicting Drug Side effects

Alberto Paccanaro, Diego Galeano, A. Paccanaro, 2019, bioRxiv.

A network medicine approach to quantify distance between hereditary disease modules on the interactome

Alfonso E. Romero, Alberto Paccanaro, Horacio Caniza, 2015, Scientific Reports.

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods

Giorgio Valentini, Alfonso E. Romero, Matteo Ré, 2014, Artif. Intell. Medicine.

Guiding Term Reduction Through a Neural Network: Some Prelimanary Results for the Group Theory

Alberto Paccanaro, 1995, RTA.

Mining the biomedical literature to predict shared drug targets in DrugBank

Alberto Paccanaro, Diego Galeano, Horacio Caniza, 2017, 2017 XLIII Latin American Computer Conference (CLEI).

Combining interactomes from multiple organisms: A case study on human-mouse

Alberto Paccanaro, Juan J. Caceres, 2016, 2016 XLII Latin American Computing Conference (CLEI).

Extracting distributed representations of concepts and relations from positive and negative propositions

Geoffrey E. Hinton, Alberto Paccanaro, A. Paccanaro, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Drug targets prediction using chemical similarity

Alberto Paccanaro, Diego Galeano, A. Paccanaro, 2016, 2016 XLII Latin American Computing Conference (CLEI).

Learning Distributed Representations of High-Arity Relational Data with Non-linear Relational Embedding

Alberto Paccanaro, A. Paccanaro, 2003, ICANN.

Learning Hierarchical Structures with Linear Relational Embedding

Geoffrey E. Hinton, Alberto Paccanaro, A. Paccanaro, 2001, NIPS.

Learning Distributed Representations of Concepts Using Linear Relational Embedding

Geoffrey E. Hinton, Alberto Paccanaro, A. Paccanaro, 2001, IEEE Trans. Knowl. Data Eng..

Improving GO semantic similarity measures by exploring the ontology beneath the terms and modelling uncertainty

Haixuan Yang, Tamás Nepusz, Alberto Paccanaro, 2012, Bioinform..

GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology

Giorgio Valentini, Alfonso E. Romero, Haixuan Yang, 2014, Bioinform..

SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale

Tamás Nepusz, Rajkumar Sasidharan, Alberto Paccanaro, 2010, BMC Bioinformatics.

Predicting interactions in protein networks by completing defective cliques

Mark Gerstein, Valery Trifonov, Haiyuan Yu, 2006, Bioinform..

Learning interpretable disease self-representations for drug repositioning pdf

Michael M. Bronstein, Ivan Laponogov, Fabrizio Frasca, 2019, ArXiv.

Integration of curated databases to identify genotype-phenotype associations

Mark Gerstein, Yang Liu, Jianrong Li, 2006, BMC Genomics.

OsWRKY22, a monocot WRKY gene, plays a role in the resistance response to blast.

Emmanuel Guiderdoni, Tamás Nepusz, Jean-Benoît Morel, 2012, Molecular plant pathology.

Statistical analysis of the genomic distribution and correlation of regulatory elements in the ENCODE regions.

Zhiping Weng, Yutao Fu, Mark B Gerstein, 2007, Genome research.

Spectral clustering of protein sequences

Alberto Paccanaro, James Casbon, Mansoor A. S. Saqi, 2006, Nucleic Acids Research.

Quantifying environmental adaptation of metabolic pathways in metagenomics

Jan O. Korbel, Peer Bork, Ivica Letunic, 2009, Proceedings of the National Academy of Sciences.

Computational Selection of Transcriptomics Experiments Improves Guilt-by-Association Analyses

Haixuan Yang, Alberto Paccanaro, Alessandra Devoto, 2012, PloS one.