G
Goar Frishman
Researcher at Technische Universität München
Publications - 22
Citations - 2907
Goar Frishman is an academic researcher from Technische Universität München. The author has contributed to research in topics: Annotation & Medicine. The author has an hindex of 13, co-authored 18 publications receiving 2562 citations.
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CORUM: the comprehensive resource of mammalian protein complexes—2009
Andreas Ruepp,Brigitte Waegele,Martin Lechner,Barbara Brauner,Irmtraud Dunger-Kaltenbach,Gisela Fobo,Goar Frishman,Corinna Montrone,H. Werner Mewes +8 more
TL;DR: A ‘Phylogenetic Conservation’ analysis tool was implemented that analyses the potential occurrence of orthologous protein complex subunits in mammals and other selected groups of organisms and allows one to predict the occurrence of protein complexes in different phylogenetic groups.
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The MIPS mammalian protein--protein interaction database
Philipp Pagel,Stefan Kovac,Matthias Oesterheld,Barbara Brauner,Irmtraud Dunger-Kaltenbach,Goar Frishman,Corinna Montrone,Pekka Mark,Volker Stümpflen,Hans-Werner Mewes,Andreas Ruepp,Dmitrij Frishman +11 more
TL;DR: The MIPS mammalian protein-protein interaction database (MPPI) is a new resource of high-quality experimental protein interaction data in mammals that is based on published experimental evidence that has been processed by human expert curators.
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PhenomiR: a knowledgebase for microRNA expression in diseases and biological processes
Andreas Ruepp,Andreas Kowarsch,Daniel Schmidl,Felix Buggenthin,Barbara Brauner,Irmtraud Dunger,Gisela Fobo,Goar Frishman,Corinna Montrone,Fabian J. Theis +9 more
TL;DR: Using the PhenomiR dataset, it is demonstrated that, depending on disease type, independent information from cell culture studies contrasts with conclusions drawn from patient studies.
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Negatome 2.0: a database of non-interacting proteins derived by literature mining, manual annotation and protein structure analysis
Philipp Blohm,Goar Frishman,Pawel Smialowski,Florian Goebels,Benedikt Wachinger,Andreas Ruepp,Dmitrij Frishman +6 more
TL;DR: The second version of Negatome, a database of proteins and protein domains that are unlikely to engage in physical interactions, is presented and it is shown that nearly a half of the text mining results with the highest confidence values correspond to NIP pairs.
Journal ArticleDOI
The Negatome database: a reference set of non-interacting protein pairs
Pawel Smialowski,Philipp Pagel,Philip Wong,Barbara Brauner,Irmtraud Dunger,Gisela Fobo,Goar Frishman,Corinna Montrone,Thomas Rattei,Dmitrij Frishman,Andreas Ruepp +10 more
TL;DR: The Negatome is much less biased toward functionally dissimilar proteins than the negative data derived by randomly selecting proteins from different cellular locations and can be used to evaluate protein and domain interactions from new experiments and improve the training of interaction prediction algorithms.