Predicting co-complexed protein pairs using genomic and proteomic data integration - Test2 - elhamkhani - TriplyDB

Predicting co-complexed protein pairs using genomic and proteomic data integration

Predicting co-complexed protein pairs using genomic and proteomic data integration

http://www.wikidata.org/entity/Q24804004

about

The interactome: Predicting the protein-protein interactions in cells Protein-protein interactions in the mammalian brain Computational verification of protein-protein interactions by orthologous co-expression Motifs, themes and thematic maps of an integrated Saccharomyces cerevisiae interaction network A road map of yeast interactions AVID: an integrative framework for discovering functional relationships among proteins Simultaneous genome-wide inference of physical, genetic, regulatory, and functional pathway components Computational prediction of protein-protein interactions in Leishmania predicted proteomes An FPT approach for predicting protein localization from yeast genomic data Deciphering Protein–Protein Interactions. Part II. Computational Methods to Predict Protein and Domain Interaction Partners Survey of Natural Language Processing Techniques in Bioinformatics.Comparative analysis and assessment of M. tuberculosis H37Rv protein-protein interaction datasets Automating genomic data mining via a sequence-based matrix format and associative rule set Data integration: challenges for drug discovery.Evaluation of different biological data and computational classification methods for use in protein interaction prediction.A database and tool, IM Browser, for exploring and integrating emerging gene and protein interaction data for Drosophila.A novel biclustering approach to association rule mining for predicting HIV-1-human protein interactions.The development of a universal in silico predictor of protein-protein interactions.Predicting co-complexed protein pairs from heterogeneous data.Assessing the limits of genomic data integration for predicting protein networks.Application of machine learning in SNP discovery.Choosing negative examples for the prediction of protein-protein interactions.IntNetDB v1.0: an integrated protein-protein interaction network database generated by a probabilistic model.A domain-based approach to predict protein-protein interactions A high-accuracy consensus map of yeast protein complexes reveals modular nature of gene essentiality.A mixture of feature experts approach for protein-protein interaction prediction An evolutionary and structural characterization of mammalian protein complex organization.Questioning the ubiquity of neofunctionalization ComPhy: prokaryotic composite distance phylogenies inferred from whole-genome gene sets.Uncovering the rules for protein-protein interactions from yeast genomic data.Assessing reliability of protein-protein interactions by integrative analysis of data in model organisms.Large-scale prediction of protein-protein interactions from structures.A human functional protein interaction network and its application to cancer data analysis Bayesian inference for genomic data integration reduces misclassification rate in predicting protein-protein interactions.Semi-supervised multi-task learning for predicting interactions between HIV-1 and human proteins Recovering protein-protein and domain-domain interactions from aggregation of IP-MS proteomics of coregulator complexes Integration strategy is a key step in network-based analysis and dramatically affects network topological properties and inferring outcomes.Heterogeneous data integration by tree-augmented naïve Bayes for protein-protein interactions prediction.Challenges and rewards of interaction proteomics.A complex-based reconstruction of the Saccharomyces cerevisiae interactome

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Predicting co-complexed protein pairs using genomic and proteomic data integration

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2004 nî lūn-bûn

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2004 թուականի Ապրիլին հրատարակուած գիտական յօդուած

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2004 թվականի ապրիլին հրատարակված գիտական հոդված

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2004年の論文

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Predicting co-complexed protein pairs using genomic and proteomic data integration

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Predicting co-complexed protein pairs using genomic and proteomic data integration

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Predicting co-complexed protein pairs using genomic and proteomic data integration

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Predicting co-complexed protein pairs using genomic and proteomic data integration

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Predicting co-complexed protein pairs using genomic and proteomic data integration

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Predicting co-complexed protein pairs using genomic and proteomic data integration

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Predicting co-complexed protein pairs using genomic and proteomic data integration

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BMC Bioinformatics

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Predicting co-complexed protein pairs using genomic and proteomic data integration

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Lan V Zhang

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Oliver D King

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Sharyl L Wong

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An automated method for finding molecular complexes in large protein interaction networks

Functional organization of the yeast proteome by systematic analysis of protein complexes

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs

Crystallographic analysis of the recognition of a nuclear localization signal by the nuclear import factor karyopherin alpha

A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae

Transcriptional regulatory networks in Saccharomyces cerevisiae

A comprehensive two-hybrid analysis to explore the yeast protein interactome

Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry

Toward a protein-protein interaction map of the budding yeast: A comprehensive system to examine two-hybrid interactions in all possible combinations between the yeast proteins

A large nucleolar U3 ribonucleoprotein required for 18S ribosomal RNA biogenesis.

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