Browsing Multidimensional Molecular Networks with the Generic Network Browser (N‐Browse)

Kao, Huey Ling; Gunsalus, Kristine C.

doi:10.1002/0471250953.bi0911s23

Cited by 29 publications

(23 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Approximately 40% of the interactions are novel, and the set excludes any lower confidence interactions from previous studies3. The WI8 physical interaction network can be visualized on our website (http://interactome.dfci.harvard.edu/C_elegans/) using N-Browse16 or VisAnt17.…”

Section: Resultsmentioning

confidence: 99%

Empirically controlled mapping of the Caenorhabditis elegans protein-protein interactome network

et al. 2008

View full text Add to dashboard Cite

Section: Resultsmentioning

confidence: 99%

Empirically controlled mapping of the Caenorhabditis elegans protein-protein interactome network

et al. 2008

View full text Add to dashboard Cite

“…These tools include: STRING (9), N-browse (31), IMP (32), FunctionalNet (33) and FunCoup (34). Each system draws from slightly different data sources and makes different decisions about how to score interactions, and we encourage readers to also evaluate these systems.…”

Section: Comparisons Of Genemania and Similar Toolsmentioning

confidence: 99%

GeneMANIA Prediction Server 2013 Update

Zuberi¹,

Franz²,

Rodriguez³

et al. 2013

Nucleic Acids Research

356

307

View full text Add to dashboard Cite

GeneMANIA (http://www.genemania.org) is a flexible user-friendly web interface for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query gene list, GeneMANIA extends the list with functionally similar genes that it identifies using available genomics and proteomics data. GeneMANIA also reports weights that indicate the predictive value of each selected data set for the query. GeneMANIA can also be used in a function prediction setting: given a query gene, GeneMANIA finds a small set of genes that are most likely to share function with that gene based on their interactions with it. Enriched Gene Ontology categories among this set can sometimes point to the function of the gene. Seven organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Homo sapiens, Rattus norvegicus and Saccharomyces cerevisiae), and hundreds of data sets have been collected from GEO, BioGRID, IRefIndex and I2D, as well as organism-specific functional genomics data sets. Users can customize their search by selecting specific data sets to query and by uploading their own data sets to analyze.

show abstract

“…The interactomes are visualized from the N-Browse viewer (http://www.arabidopsis.org/tools/nbrowse.jsp) [169] with manual modifications as indicated below ( A ) ABI5 interactome; ( B ) DREB2A interactome with addition of SRO1; ( C ) ANAC019 interactome; ( D ) WRKY40 interactome with addition of CHLH/ABAR; ( E ) Zat7 interactome; ( F ) MYB15 interactome; ( G ) ICE1 interactome.…”

Section: Figurementioning

confidence: 99%

Structure, Function and Networks of Transcription Factors Involved in Abiotic Stress Responses

Lindemose

O'Shea

Jensen

et al. 2013

IJMS

270

161

View full text Add to dashboard Cite

Transcription factors (TFs) are master regulators of abiotic stress responses in plants. This review focuses on TFs from seven major TF families, known to play functional roles in response to abiotic stresses, including drought, high salinity, high osmolarity, temperature extremes and the phytohormone ABA. Although ectopic expression of several TFs has improved abiotic stress tolerance in plants, fine-tuning of TF expression and protein levels remains a challenge to avoid crop yield loss. To further our understanding of TFs in abiotic stress responses, emerging gene regulatory networks based on TFs and their direct targets genes are presented. These revealed components shared between ABA-dependent and independent signaling as well as abiotic and biotic stress signaling. Protein structure analysis suggested that TFs hubs of large interactomes have extended regions with protein intrinsic disorder (ID), referring to their lack of fixed tertiary structures. ID is now an emerging topic in plant science. Furthermore, the importance of the ubiquitin-proteasome protein degradation systems and modification by sumoylation is also apparent from the interactomes. Therefore; TF interaction partners such as E3 ubiquitin ligases and TF regions with ID represent future targets for engineering improved abiotic stress tolerance in crops.

show abstract

Browsing Multidimensional Molecular Networks with the Generic Network Browser (N‐Browse)

Cited by 29 publications

References 1 publication

Empirically controlled mapping of the Caenorhabditis elegans protein-protein interactome network

Empirically controlled mapping of the Caenorhabditis elegans protein-protein interactome network

GeneMANIA Prediction Server 2013 Update

Structure, Function and Networks of Transcription Factors Involved in Abiotic Stress Responses

Contact Info

Product

Resources

About