Michigan molecular interactions r2: from interacting proteins to pathways

Tarcea, V. Glenn; Weymouth, Terry E.; Ade, Alexander S.; Bookvich, Aaron V.; Gao, Jinfang; Mahavisno, Vasudeva; Wright, Zach; Chapman, Adriane; Jayapandian, Magesh; Özgür, Arzucan; Tian, Yuanyuan; Cavalcoli, James D.; Mirel, Barbara; Patel, Jignesh M.; Radev, Dragomir; Athey, Brian D.; States, David J.; Jagadish, H. V.

doi:10.1093/nar/gkn722

Cited by 81 publications

(60 citation statements)

References 33 publications

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“…The interaction data for the 24 proteins were provided by the Michigan molecular interactions (MiMI) database, providing data from different databases [18]. Only the interactions demonstrated by experimental data were considered when constructing the interactome.…”

Section: Functional Analysismentioning

confidence: 99%

Functional analysis of beef tenderness

Guillemin

Bonnet

Jurie

et al. 2011

Journal of Proteomics

111

116

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Section: Functional Analysismentioning

confidence: 99%

Functional analysis of beef tenderness

Guillemin

Bonnet

Jurie

et al. 2011

Journal of Proteomics

111

116

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“…The literature describes many tools for genomic and proteomic data analysis [4]. Scientists have to select appropriate tools among those for either the GO annotation [15,30,49,21,29,50], the prediction of secreted proteins [51,52,39,53], or the search of protein -protein interactions [54,55,36,56,37,57,58].…”

Section: Discussionmentioning

confidence: 99%

Protein Function Easily Investigated by Genomics Data Mining Using the ProteINSIDE Online Tool

Kaspric¹,

Reichstadt²,

Picard³

et al. 2015

Genomics Comput Biol

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Nowadays, genomic and proteomic studies produce vast amounts of data. To get the biological meaning of these data and to generate testable new hypothesis, scientists must use several tools often not designed for ruminant studies. Here we present ProteINSIDE: an online tool to analyse lists of protein or gene identifiers from well-annotated species (human, rat, and mouse) and ruminants (cow, sheep, and goat). The aims of ProteINSIDE modules are to gather biological information stores in well-updated public databases, to proceed to annotations according to the Gene Ontology consortium, to predict potentially secreted proteins, and to search for proteins interactions. ProteINSIDE provides results from several software and databases in a single query. From a list of identifiers, ProteINSIDE uses orthologs or homologs to extend analyses and biological information retrieval. As a tutorial, we presented how to launch, to recover, to view, and to interpret the results provided by the two types of analysis available with ProteINSIDE (basic and custom analyses). ProteINSIDE is freely available using an internet browser at www.proteinside.org. The results of this article are provided on the home page of ProteINSIDE website as the example of an analysis result.

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“…The GRN was constructed using two major interaction databases, including MiMI (Michigan Molecular Interactions) (Tarcea et al, 2009) and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING;Franceschini et al, 2013). Briefly, the list of genes was submitted online or through a related plug-in within Cytoscape software (Cline et al, 2007) and then interactions between genes were retrieved and displayed as an interactions network.…”

Section: Network Reconstruction and Analysismentioning

confidence: 99%