DIP: the Database of Interacting Proteins

By Ioannis Xenarios, Danny W. Rice, Lukasz Salwínski, M. Baron, Edward M. Marcotte, David S. Eisenberg. 2000

1,190 citations recorded by the source corpus.

Subfields: Molecular Biology, Pharmacology

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Tony Pawson

Citations in the corpus

Predicting protein functions with message passing algorithms (2004, neutral): “, 2000) and D (Xenarios et al., 2000), respectively.”
Using graph theory to analyze biological networks (2011, methodology): “Some very well-known datasets that have been recently produced by employing the aforementioned techniques and that are widely used are the Tong [8], Krogan [9], DIP [10], MIPS [11], Gavin 2002 [5] and Gavin 2006 [12] datasets.”
Relating whole-genome expression data with protein-protein interactions. (2002, background): “…MIPS catalogs of physical and genetic interactions (Fellenberg et al. 2000), databases of interacting proteins (DIP and BIND) (Bader and Hogue 2000; Xenarios 2000), and a comprehensive collection of yeast two-hybrid experiments (Cagney et al. 2000; Ito et al. 2000; Schwikowski et al. 2000; Uetz et…”
The Proteomics Protocols Handbook (2005, background): “Efforts to minimize this effect by introducing an excess of DTT in the wick at the cathode appear to help extend the pH range for protein resolution (77).”
DIP: The Database of Interacting Proteins: 2001 update (2001, neutral): “The core of the DIP database structure is composed of three linked tables: one of protein information, one of protein–protein interactions and one describing details of experiments (2).”
The Transporter Classification Database (2013, neutral): “php), DIP (18), RefSeq (19), Entrez (20), Pfam (21), BioCyc (22), KEGG (23), PDB (24) and DrugBank.”
Discovering molecular pathways from protein interaction and gene expression data (2003, methodology): “Based on this assumption, our approach searches for sets of genes that have a similar expression profile, and a significant fraction of protein-protein interactions in the DIP binary interaction data set (Xenarios et al., 2000).”
The Physics of Communicability in Complex Networks (2011, methodology): “[79] studied two PPI networks from DIP database [89], one in which protein complexes are identified by experimental methods (YGS_PC) and another in which they are identified by the CMC algorithm (YCMC_PC).”
Accomplishments and challenges in literature data mining for biology (2002, background): “The forerunners of such databases include KEGG [1], DIP [2], BIND [3], among others.”
Mutation severity spectrum of rare alleles in the human genome is predictive of disease type (2019, methodology): “D) Distribution of protein interactions from four databases (BioGrid [59], IntAct [60], DIP [61] and HPRD [62]) integrated in PICKLE [63] for gene sets within three different mutation severity AvgAI score deciles (0, 0.”
DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions (2002, methodology): “The database is implemented as a relational database composed of four tables (6).”
A new approach to decoding life: systems biology. (2001, background): “For instance, the Database of Interacting Proteins (137), BIND (10), and MIPS (90a) contain searchable indices of known protein-protein interactions; TRANSFAC (133) and SCPD (142) catalog interactions between proteins and DNA (i.e., transcriptionfactor interactions), and databases of metabolic pathw”
PDP: protein domain parser (2003, methodology): “, 2001), for prediction of protein–protein interactions (Xenarios et al., 2000), and for prediction of protein structure and function (Russel, 1999), We have developed and benchmarked a program PDP (Protein Domain Parser) for automatic domain assignment, which is currently used for preparation of th”
Regularized Learning with Networks of Features (2008, methodology): “For the biomedical domain, databases such as KEGG and DIP list putative protein interactions [3, 4].”