Literature DB >> 29893885

EviNet: a web platform for network enrichment analysis with flexible definition of gene sets.

Ashwini Jeggari1, Zhanna Alekseenko1, Iurii Petrov2, José M Dias1, Johan Ericson1, Andrey Alexeyenko2,3.   

Abstract

The new web resource EviNet provides an easily run interface to network enrichment analysis for exploration of novel, experimentally defined gene sets. The major advantages of this analysis are (i) applicability to any genes found in the global network rather than only to those with pathway/ontology term annotations, (ii) ability to connect genes via different molecular mechanisms rather than within one high-throughput platform, and (iii) statistical power sufficient to detect enrichment of very small sets, down to individual genes. The users' gene sets are either defined prior to upload or derived interactively from an uploaded file by differential expression criteria. The pathways and networks used in the analysis can be chosen from the collection menu. The calculation is typically done within seconds or minutes and the stable URL is provided immediately. The results are presented in both visual (network graphs) and tabular formats using jQuery libraries. Uploaded data and analysis results are kept in separated project directories not accessible by other users. EviNet is available at https://www.evinet.org/.

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Year:  2018        PMID: 29893885      PMCID: PMC6030852          DOI: 10.1093/nar/gky485

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  56 in total

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Journal:  Genes Dev       Date:  2005-05-15       Impact factor: 11.361

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5.  Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Authors:  Aravind Subramanian; Pablo Tamayo; Vamsi K Mootha; Sayan Mukherjee; Benjamin L Ebert; Michael A Gillette; Amanda Paulovich; Scott L Pomeroy; Todd R Golub; Eric S Lander; Jill P Mesirov
Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-30       Impact factor: 11.205

6.  HTSeq--a Python framework to work with high-throughput sequencing data.

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Journal:  Bioinformatics       Date:  2014-09-25       Impact factor: 6.937

7.  ResponseNet2.0: Revealing signaling and regulatory pathways connecting your proteins and genes--now with human data.

Authors:  Omer Basha; Shoval Tirman; Amir Eluk; Esti Yeger-Lotem
Journal:  Nucleic Acids Res       Date:  2013-06-12       Impact factor: 16.971

8.  HTRIdb: an open-access database for experimentally verified human transcriptional regulation interactions.

Authors:  Luiz A Bovolenta; Marcio L Acencio; Ney Lemke
Journal:  BMC Genomics       Date:  2012-08-17       Impact factor: 3.969

9.  The Reactome pathway knowledgebase.

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Journal:  Nucleic Acids Res       Date:  2013-11-15       Impact factor: 16.971

10.  Short Chain Fatty Acids (SCFA) Reprogram Gene Expression in Human Malignant Epithelial and Lymphoid Cells.

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Journal:  PLoS One       Date:  2016-07-21       Impact factor: 3.240

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  7 in total

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Journal:  Brief Bioinform       Date:  2020-09-25       Impact factor: 11.622

2.  PlantGSAD: a comprehensive gene set annotation database for plant species.

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Journal:  Nucleic Acids Res       Date:  2022-01-07       Impact factor: 16.971

3.  Robust derivation of transplantable dopamine neurons from human pluripotent stem cells by timed retinoic acid delivery.

Authors:  José M Dias; Andrew F Adler; Mariya Kozhevnikova; Zhanna Alekseenko; Josina Anna van Lunteren; Sara Nolbrant; Ashwini Jeggari; Svitlana Vasylovska; Takashi Yoshitake; Jan Kehr; Marie Carlén; Andrey Alexeyenko; Malin Parmar; Johan Ericson
Journal:  Nat Commun       Date:  2022-06-01       Impact factor: 17.694

4.  Prediction of response to anti-cancer drugs becomes robust via network integration of molecular data.

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Journal:  Sci Rep       Date:  2019-02-20       Impact factor: 4.379

5.  Protein profiling and network enrichment analysis in individuals before and after the onset of rheumatoid arthritis.

Authors:  Mikael Brink; Anders Lundquist; Andrey Alexeyenko; Kristina Lejon; Solbritt Rantapää-Dahlqvist
Journal:  Arthritis Res Ther       Date:  2019-12-16       Impact factor: 5.156

6.  Venn-diaNet : venn diagram based network propagation analysis framework for comparing multiple biological experiments.

Authors:  Benjamin Hur; Dongwon Kang; Sangseon Lee; Ji Hwan Moon; Gung Lee; Sun Kim
Journal:  BMC Bioinformatics       Date:  2019-12-27       Impact factor: 3.169

7.  PyGNA: a unified framework for geneset network analysis.

Authors:  Viola Fanfani; Fabio Cassano; Giovanni Stracquadanio
Journal:  BMC Bioinformatics       Date:  2020-10-22       Impact factor: 3.169

  7 in total

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