Alberto Paccanaro

Global Functional Atlas of Escherichia coli Encompassing Previously Uncharacterized Proteins (2009)

Pingzhao Hu, Sarath Chandra Janga, Mohan Babu, Gareth Butland, Wenhong Yang, ...

One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic...

Inferring Protein-Protein Interactions Using Interaction Network Topologies (2008)

Alberto Paccanaro, Valery Trifonov, Haiyuan Yu, Mark Gerstein

[ ∗ these authors contributed equally to this work] Abstract — We describe two novel methods for predicting protein interactions, using only the topology of an observed protein interaction...

BIOINFORMATICS ORIGINAL PAPER Systems biology (2008)

Haiyuan Yu, Alberto Paccanaro, Valery Trifonov, Mark Gerstein

Vol. 22 no. 7 2006, pages 823–829 doi:10.1093/bioinformatics/btl014 Predicting interactions in protein networks by completing defective cliques

Project For Csc 2108 - Automated Verification (2007)

Prof Marsha, Prof Marsha Checkic, Cathy Jansen, Alberto Paccanaro

Some elementary concepts on Equational Theories and Term Rewriting Systems are introduced, followed by a brief review of the main ideas of the Knuth-Bendix Completion procedure. Then a formalization...

Statistical analysis of the genomic distribution and correlation of regulatory elements in the ENCODE regions (2007)

Zhang, Zhengdong D., Paccanaro, Alberto, Fu, Yutao, Weissman, Sherman, Weng, Zhiping, Chang, Joseph, ...

The comprehensive inventory of functional elements in 44 human genomic regions carried out by the ENCODE Project Consortium enables for the first time a global analysis of the genomic distribution of...

Integration of curated databases to identify genotype-phenotype associations (2006)

Goh, Chern-Sing, Gianoulis, Tara A, Liu, Yang, Li, Jianrong, Paccanaro, Alberto, Lussier, Yves A, ...

Abstract Background The ability to rapidly characterize an unknown microorganism is critical in both responding to infectious disease and biodefense. To do this, we need some way of anticipating an...

Clustering of Pseudomonas aeruginosatranscriptomes from planktonic cultures, developing and mature biofilms reveals distinct expression profiles (2006)

Waite, Richard D, Paccanaro, Alberto, Papakonstantinopoulou, Anastasia, Hurst, Jacob M, Saqi, Mansoor, Littler, Eddie, ...

Abstract Background Pseudomonas aeruginosa is a genetically complex bacterium which can adopt and switch between a free-living or biofilm lifestyle, a versatility that enables it to thrive in many...

Spectral clustering of protein sequences (2006)

Alberto Paccanaro, James A. Casbon

An important problem in genomics is automatically clustering homologous proteins when only sequence information is available. Most methods for clustering proteins are local, and are based on simply...

BioMed Central Open Access (2006)

Chern-sing Goh, Tara A Gianoulis, Yang Liu, Jianrong Li, Alberto Paccanaro, Yves A Lussier, ...

Integration of curated databases to identify genotype-phenotype

Predicting essential genes in fungal genomes (2006)

Seringhaus, Michael, Paccanaro, Alberto, Borneman, Anthony, Snyder, Michael, Gerstein, Mark

Essential genes are required for an organism's viability, and the ability to identify these genes in pathogens is crucial to directed drug development. Predicting essential genes through...

Predicting interactions in protein networks by completing defective cliques (2006)

Yu, Haiyuan, Paccanaro, Alberto, Trifonov, Valery, Gerstein, Mark

Datasets obtained by large-scale, high-throughput methods for detecting protein–protein interactions typically suffer from a relatively high level of noise. We describe a novel method for improving...

Spectral clustering of protein sequences (2006)

Paccanaro, Alberto, Casbon, James A., Saqi, Mansoor A. S.

An important problem in genomics is automatically clustering homologous proteins when only sequence information is available. Most methods for clustering proteins are local, and are based on simply...

Predicting essential genes in fungal genomes (2006)

Seringhaus, Michael, Paccanaro, Alberto, Borneman, Anthony, Snyder, Michael, Gerstein, Mark

Essential genes are required for an organism’s viability, and the ability to identify these genes in pathogens is crucial to directed drug development. Predicting essential genes through...

Assessing the limits of genomic data integration for predicting protein networks (2005)

Lu, Long J., Xia, Yu, Paccanaro, Alberto, Yu, Haiyuan, Gerstein, Mark

Genomic data integration—the process of statistically combining diverse sources of information from functional genomics experiments to make large-scale predictions—is becoming increasingly...

Learning hierarchical structures with linear relational embedding (2002)

Alberto Paccanaro, Geoffrey E. Hinton

We present Linear Relational Embedding (LRE), a new method of learning a distributed representation of concepts from data consisting of instances of relations between given concepts. Its final goal...

Learning hierarchical structures with linear relational embedding (2002)

Alberto Paccanaro, Geoffrey E. Hinton

We present Linear Relational Embedding (LRE), a new method of learning a distributed representation of concepts from data consisting of instances of relations between given concepts. Its final goal...

Learning hierarchical structures with linear relational embedding (2002)

Alberto Paccanaro, Geoffrey E. Hinton

alberto,hinton¡ We present Linear Relational Embedding (LRE), a new method of learning a distributed representation of concepts from data consisting of instances of relations between given concepts....

Learning distributed representations of concepts from relational data using linear relational embedding (2000)

Alberto Paccanaro

In this paper we discuss methods for generalizing over relational data. Our approach is to learn distributed representations for the concepts that coincide with their semantic features and then to...

Extracting distributed representations of concepts and relations from positive and negative propositions (2000)

Alberto Paccanaro, Geoffrey E. Hinton

Linear Relational Embedding (LRE) was introduced (Paccanaro and Hinton, 1999) as a means of extracting a distributed representation of concepts from relational data. The original formulation cannot...

Learning Distributed Representations of Concepts using Linear Relational Embedding (2000)

Alberto Paccanaro, Geoffrey E. Hinton

In this paper we introduce Linear Relational Embedding as a means of learning a distributed representation of concepts from data consisting of binary relations between concepts. The key idea is to...

Learning Distributed Representations of Concepts using Linear Relational Embedding (2000)

Alberto Paccanaro, Alberto Paccanaro, Geoffrey Hinton, Geoffrey Hinton

In this paper we introduce Linear Relational Embedding as a means of learning a distributed representation of concepts from data consisting of binary relations between concepts. The key idea is to...

Learning distributed representations of concepts from relational data using linear relational embedding (2000)

Alberto Paccanaro, Alberto Paccanaro, Geoffrey Hinton, Geoffrey Hinton

In this paper we introduce Linear Relational Embedding as a means of learning a distributed representation of concepts from data consisting of binary relations between concepts. The key idea is to...

Assessing the limits of genomic data integration for predicting protein networks

Lu, Long J., Xia, Yu, Paccanaro, Alberto, Yu, Haiyuan, Gerstein, Mark

Genomic data integration—the process of statistically combining diverse sources of information from functional genomics experiments to make large-scale predictions—is becoming increasingly...

Spectral clustering of protein sequences

Paccanaro, Alberto, Casbon, James A., Saqi, Mansoor A. S.

An important problem in genomics is automatically clustering homologous proteins when only sequence information is available. Most methods for clustering proteins are local, and are based on simply...

Assessing the limits of genomic data integration for predicting protein networks

Lu, Long J., Xia, Yu, Paccanaro, Alberto, Yu, Haiyuan, Gerstein, Mark

Genomic data integration—the process of statistically combining diverse sources of information from functional genomics experiments to make large-scale predictions—is becoming increasingly...

Spectral clustering of protein sequences

Paccanaro, Alberto, Casbon, James A., Saqi, Mansoor A. S.

An important problem in genomics is automatically clustering homologous proteins when only sequence information is available. Most methods for clustering proteins are local, and are based on simply...

Predicting essential genes in fungal genomes

Seringhaus, Michael, Paccanaro, Alberto, Borneman, Anthony, Snyder, Michael, Gerstein, Mark

Essential genes are required for an organism's viability, and the ability to identify these genes in pathogens is crucial to directed drug development. Predicting essential genes through...

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

Zhang, Zhengdong D., Paccanaro, Alberto, Fu, Yutao, Weissman, Sherman, Weng, Zhiping, Chang, Joseph, ...

The comprehensive inventory of functional elements in 44 human genomic regions carried out by the ENCODE Project Consortium enables for the first time a global analysis of the genomic distribution of...

Global Functional Atlas of Escherichia coli Encompassing Previously Uncharacterized Proteins

Hu, Pingzhao, Janga, Sarath Chandra, Babu, Mohan, Díaz-Mejía, J. Javier, Butland, Gareth, Yang, Wenhong, ...

One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic...

Quantifying environmental adaptation of metabolic pathways in metagenomics

Gianoulis, Tara A., Raes, Jeroen, Patel, Prianka V., Bjornson, Robert, Korbel, Jan O., Letunic, Ivica, ...

Recently, approaches have been developed to sample the genetic content of heterogeneous environments (metagenomics). However, by what means these sequences link distinct environmental conditions with...