GeneDecks: paralog hunting and gene-set distillation with GeneCards annotation.

@article{Stelzer2009GeneDecksPH,
  title={GeneDecks: paralog hunting and gene-set distillation with GeneCards annotation.},
  author={Gil Stelzer and Aron Inger and Tsviya Olender and Tsippi Iny-Stein and Irina Dalah and Arye Harel and Marilyn Safran and Doron Lancet},
  journal={Omics : a journal of integrative biology},
  year={2009},
  volume={13 6},
  pages={
          477-87
        }
}
Sophisticated genomic navigation strongly benefits from a capacity to establish a similarity metric among genes. GeneDecks is a novel analysis tool that provides such a metric by highlighting shared descriptors between pairs of genes, based on the rich annotation within the GeneCards compendium of human genes. The current implementation addresses information about pathways, protein domains, Gene Ontology (GO) terms, mouse phenotypes, mRNA expression patterns, disorders, drug relationships, and… 

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References

SHOWING 1-10 OF 46 REFERENCES

In-silico human genomics with GeneCards

The evolution and architecture of this project is described, including examples of synergistic applications in diverse areas such as synthetic lethality in cancer, the annotation of genetic variations in disease, omics integration in a systems biology approach to kidney disease, and bioinformatics tools.

AutoFACT: An Automatic Functional Annotation and Classification Tool

This work presents AutoFACT, a fully automated and customizable annotation tool that assigns biologically informative functions to a sequence and determines the most informative functional description by combining multiple BLAST reports from several user-selected databases.

FunSimMat: a comprehensive functional similarity database

FunSimMat is described, a large new database that provides several different semantic similarity measures for GO terms and offers various precomputed functional similarity values for proteins contained in UniProtKB and for protein families in Pfam and SMART.

GOblet: a platform for Gene Ontology annotation of anonymous sequence data

GOblet is a comprehensive web server application providing the annotation of anonymous sequence data with Gene Ontology (GO) terms and provides an improved display of results with the aid of Java applets.

Human Gene-Centric Databases at the Weizmann Institute of Science: GeneCards, UDB, CroW 21 and HORDE

Recent enhancements and current research in the GeneCards project are described, including the addition of gene expression profiles and integrated gene locations and the contributions of specialized associated human gene-centric databases developed at the Weizmann Institute.

Characterization of protein-interaction networks in tumors

Cancer PINs representing differentially regulated genes are larger than those of randomly selected protein lists, indicating functional dependencies among protein lists that can be identified on the basis of transcriptomics experiments, but the prevalence of hub proteins was not increased in the presence of cancer.

Judging the quality of gene expression-based clustering methods using gene annotation.

It is concluded that enrichment of clusters for biological function is, in general, highest at rather low cluster numbers, and no method outperforms Euclidean distance for ratio-based measurements, or Pearson distance at the optimal choice of cluster number.

Gene Ontology: tool for the unification of biology

The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing.

Gene Ontology annotation quality analysis in model eukaryotes

The GO Annotation Quality (GAQ) score is reported, a quantitative measure of GO quality that includes breadth of GO annotation, the level of detail of annotation and the type of evidence used to make the annotation.