Integration of biological networks and gene expression data using Cytoscape

Cline, Melissa; Smoot, Michael; Cerami, Ethan; Kuchinsky, Allan; Landys, Nerius; Workman, Christopher T.; Christmas, Rowan H.; Avila-Campilo, Iliana; Creech, Michael; Groß, Benjamin; Hanspers, Kristina; Isserlin, Ruth; Ryan, Katherine S.; Killcoyne, Sarah; Lotia, Samad; Maere, Steven; Morris, John H.; Ono, Keiichiro; Pavlovic, Vuk; Pico, Alexander R.; Vailaya, Aditya; Wang, Pengliang; Adler, Annette; Conklin, Bruce R.; Hood, Leroy; Kuiper, Martin; Sander, Chris; Schmulevich, Ilya; Schwikowski, Benno; Warner, Guy J.; Ideker, Trey; Bader, Gary D.

doi:10.1038/nprot.2007.324

Cited by 2,232 publications

(1,823 citation statements)

References 75 publications

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“…Resulting propagated scores were used as correction factors for each node and thus subtracted from the original propagated scores. For each NTR sample, proteins were ranked according to their smoothed, topology bias corrected scores, and the top 2% proteins for each sample were used for the identification of highly interconnected subnetworks using the Cytoscape (Cline et al , 2007) App MCODE (Bader & Hogue, 2003). …”

Section: Methodsmentioning

confidence: 99%

Landscape of nuclear transport receptor cargo specificity

Mackmull

Klaus

Heinze

et al. 2017

Molecular Systems Biology

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Nuclear transport receptors (NTRs) recognize localization signals of cargos to facilitate their passage across the central channel of nuclear pore complexes (NPCs). About 30 different NTRs constitute different transport pathways in humans and bind to a multitude of different cargos. The exact cargo spectrum of the majority of NTRs, their specificity and even the extent to which active nucleocytoplasmic transport contributes to protein localization remains understudied because of the transient nature of these interactions and the wide dynamic range of cargo concentrations. To systematically map cargo–NTR relationships in situ, we used proximity ligation coupled to mass spectrometry (BioID). We systematically fused the engineered biotin ligase BirA* to 16 NTRs. We estimate that a considerable fraction of the human proteome is subject to active nuclear transport. We quantified the specificity and redundancy in NTR interactions and identified transport pathways for cargos. We extended the BioID method by the direct identification of biotinylation sites. This approach enabled us to identify interaction interfaces and to discriminate direct versus piggyback transport mechanisms. Data are available via ProteomeXchange with identifier PXD007976.

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Section: Methodsmentioning

confidence: 99%

Landscape of nuclear transport receptor cargo specificity

Mackmull

Klaus

Heinze

et al. 2017

Molecular Systems Biology

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“…Cytoscape version 2.8.2 [47] along with its plugin Bingo version 2.44 [48] was used for GO classification. The AGI accession numbers for Arabidopsis were uploaded and ontology of GOSlim_Plants was chosen with other settings as default (significance level 0.05).…”

Section: Gene Ontology (Go) and Plant Ontology (Po) Analysesmentioning

confidence: 99%

“…3 -Functional classification of the identified phosphoproteins by gene ontology (GO) analysis. Cytoscape version 2.8.2 [47] along with its plugin Bingo version 2.44 [48] were used for the GO analysis. Over-represented GO terms were displayed graphically as yFiles hierarchical trees for three GO vocabularies: (A) cellular component, (B) biological process, and (C) molecular function.…”

Section: Functional Classification Of the Identified Phosphoproteinsmentioning

confidence: 99%

A large-scale protein phosphorylation analysis reveals novel phosphorylation motifs and phosphoregulatory networks in Arabidopsis

Wang

Bian

Cheng

et al. 2013

Journal of Proteomics

101

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“…All events extracted using the TEES software (Van Landeghem et al 2013) for these selected gene families were thereafter compiled and imported into Cytoscape (Cline et al 2007 interactions (defined a priori, i.e. 'examples of event triggers') between any two gene families that contain at least one homolog in Synechocystis 6803, accessing all literature for all species in PubMed abstracts and PubMed Central Open Access full-texts up to June 2012.…”

Section: Network Constructionmentioning

confidence: 99%

“…All events extracted using the TEES software (Van Landeghem et al 2013) for these selected gene families were thereafter compiled and imported into Cytoscape (Cline et al 2007). The thus created text-mining network was therefore composed of all machine- readable 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 interactions (defined a priori, i.e.…”

Section: Network Constructionmentioning

confidence: 99%

Finding novel relationships with integrated gene-gene association network analysis of Synechocystis sp. PCC 6803 using species-independent text-mining

Kreula

Kaewphan

Ginter

et al. 2017

Preprint

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The increasing move towards open access full-text scientific literature enhances our ability to utilize advanced text-mining methods to construct information-rich networks that no human will be able to grasp simply from 'reading the literature'. The utility of text-mining for well-studied species is obvious though the utility for less studied species, or those with no prior track-record at all, is not clear. Here we present a concept for how advanced textmining can be used to create information-rich networks even for less well studied species and apply it to generate an open-access gene-gene association network resource for Synechocystis sp. PCC 6803, a representative model organism for cyanobacteria and first case-study for the methodology. By merging the text-mining network with networks generated from species-specific experimental data, network integration was used to enhance the accuracy of predicting novel interactions that are biologically relevant. A rulebased algorithm was constructed in order to automate the search for novel candidate genes with a high degree of likely association to known target genes by (1) ignoring established relationships from the existing literature, as they are already 'known', and (2) demanding multiple independent evidences for every novel and potentially relevant relationship. Using selected case studies, we demonstrate the utility of the network resource and rule-based algorithm to (i) discover novel candidate associations between different genes or proteins in the network, and (ii) rapidly evaluate the potential role of ABSTRACTThe increasing move towards open access full-text scientific literature enhances our ability to utilize advanced text-mining methods to construct information-rich networks that no human will be able to grasp simply from 'reading the literature'. The utility of text-mining for well-studied species is obvious though the utility for less studied species, or those with no prior track-record at all, is not clear. Here we present a concept for how advanced text-mining can be used to create information-rich networks even for less well studied species and apply it to generate an openaccess gene-gene association network resource for Synechocystis sp. PCC 6803, a representative model organism for cyanobacteria and first case-study for the methodology. uy merging the textmining network with networks generated from species-specific experimental data, network integration was used to enhance the accuracy of predicting novel interactions that are biologically relevant. A rule-based algorithm was constructed in order to automate the search for novel candidate genes with a high degree of likely association to known target genes by (1) ignoring established relationships from the existing literature, as they are already 'known', and (2) demanding multiple independent evidences for every novel and potentially relevant relationship. Using selected case studies, we demonstrate the utility of the network resource and rule-based algorithm to (i) discover novel candidate ass...

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Integration of biological networks and gene expression data using Cytoscape

Cited by 2,232 publications

References 75 publications

Landscape of nuclear transport receptor cargo specificity

Landscape of nuclear transport receptor cargo specificity

A large-scale protein phosphorylation analysis reveals novel phosphorylation motifs and phosphoregulatory networks in Arabidopsis

Finding novel relationships with integrated gene-gene association network analysis of Synechocystis sp. PCC 6803 using species-independent text-mining

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