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Network integration of heterogeneous data
The document discusses the integration of heterogeneous data in biological research, emphasizing methodologies like phylogenetic profiling, gene expression analysis, and interaction networks. It highlights various resources and databases such as STRING, Biogrid, and Netphorest for data mining and analysis of gene and protein interactions. Additionally, it addresses challenges like data quality, context localization, and the need for computational validation methods in signaling networks.
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Network integration of heterogeneous data
- 1. Network integration ofheterogeneous data Lars Juhl Jensen EMBL Heidelberg
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- 41. BioGRID General Repositoryfor Interaction Datasets
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- 43. MINT Molecular InteractionsDatabase
- 44. DIP Database ofInteracting Proteins
- 45. BIND Biomolecular InteractionNetwork Database
- 46. HPRD Human ProteinReference Database
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- 51. NLP Natural LanguageProcessing
- 52. Gene andprotein names Cue words for entity recognition Verbs for relation extraction [ nxexpr T he expression of [ nxgene the cytochrome genes [ nxpg CYC1 and CYC7 ]]] is controlled by [ nxpg HAP1 ]
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- 54. SGD Saccharomyces GenomeDatabase
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- 56. OMIM Online MendelianInheritance in Man
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- 63. MIPS Munich Informationcenter for Protein Sequences
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- 69. PID NCI-Nature PathwayInteraction Database
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- 81. calibrate vs. goldstandard
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- 85. P = 1-(1-P1 ) . (1-P 2 ) . (1-P 3 ) …
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- 149. Acknowledgments STRING &STITCH Christian von Mering Michael Kuhn Manuel Stark Samuel Chaffron Philippe Julien Tobias Doerks Jan Korbel Berend Snel Martijn Huynen Peer Bork Literature mining Evangelos Pafilis Jasmin Saric Rossitza Ouzounova Sean O’Donoghue Isabel Rojas NetworKIN & NetPhorest Rune Linding Martin Lee Miller Gerard Ostheimer Francesca Diella Karen Colwill Jing Jin Pavel Metalnikov Vivian Nguyen Adrian Pasculescu Jin Gyoon Park Leona D. Samson Nikolaj Blom Rob Russell Peer Bork Søren Brunak Michael Yaffe Tony Pawson
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