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Diffusion kernel-based logistic regression models for protein function prediction.
Assigning functions to unknown proteins is one of the most important problems in proteomics. Several approaches have used protein-protein interaction data to predict protein functions. We previouslyExpand
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An integrated approach to the prediction of domain-domain interactions
TLDR
We combine protein interaction data sets from multiple species, molecular sequences, and gene ontology to construct a set of high-confidence domain-domain interactions using a Bayesian approach. Expand
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A critical assessment of Mus musculus gene function prediction using integrated genomic evidence
Background:Several years after sequencing the human genome and the mouse genome, much remains to be discovered about the functions of most human and mouse genes. Computational prediction of geneExpand
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CGI: a new approach for prioritizing genes by combining gene expression and protein-protein interaction data
TLDR
MOTIVATION Identifying candidate genes associated with a given phenotype or trait is an important problem in biological and biomedical studies. Expand
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Integrative analysis reveals the direct and indirect interactions between DNA copy number aberrations and gene expression changes
TLDR
MOTIVATION DNA copy number aberrations (CNAs) and gene expression (GE) changes provide valuable information for studying chromosomal instability and its consequences in cancer. Expand
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Adaptive landmark recommendations for travel planning: Personalizing and clustering landmarks using geo-tagged social media
TLDR
We propose an approach that adaptively recommends clusters of landmarks using geo-tagged social media based on their trip's spatial and temporal properties. Expand
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GIST at SemEval-2018 Task 12: A network transferring inference knowledge to Argument Reasoning Comprehension task
TLDR
This paper describes our GIST team system that participated in SemEval-2018 Argument Reasoning Comprehension task, outperforming all the systems more than 10%. Expand
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Predicting Drug-Target Interactions Using Drug-Drug Interactions
Computational methods for predicting drug-target interactions have become important in drug research because they can help to reduce the time, cost, and failure rates for developing new drugs.Expand
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DigSee: disease gene search engine with evidence sentences (version cancer)
TLDR
We search MEDLINE for evidence sentences describing that ‘genes’ are involved in the development of ‘cancer’ through ‘biological events’. Expand
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A Computational Approach to Identifying Gene-microRNA Modules in Cancer
TLDR
In this study, we propose a computational approach to constructing modules that represent the complex relationships between genes and miRNAs in cancer by integrating the expression data of genes andmiRNAs with gene-gene interaction data. Expand
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