Literature DB >> 21893519

Integrated pathway-level analysis of transcriptomics and metabolomics data with IMPaLA.

Atanas Kamburov1, Rachel Cavill, Timothy M D Ebbels, Ralf Herwig, Hector C Keun.   

Abstract

SUMMARY: Pathway-level analysis is a powerful approach enabling interpretation of post-genomic data at a higher level than that of individual biomolecules. Yet, it is currently hard to integrate more than one type of omics data in such an approach. Here, we present a web tool 'IMPaLA' for the joint pathway analysis of transcriptomics or proteomics and metabolomics data. It performs over-representation or enrichment analysis with user-specified lists of metabolites and genes using over 3000 pre-annotated pathways from 11 databases. As a result, pathways can be identified that may be disregulated on the transcriptional level, the metabolic level or both. Evidence of pathway disregulation is combined, allowing for the identification of additional pathways with changed activity that would not be highlighted when analysis is applied to any of the functional levels alone. The tool has been implemented both as an interactive website and as a web service to allow a programming interface. AVAILABILITY: The web interface of IMPaLA is available at http://impala.molgen.mpg.de. A web services programming interface is provided at http://impala.molgen.mpg.de/wsdoc. CONTACT: kamburov@molgen.mpg.de; r.cavill@imperial.ac.uk; h.keun@imperial.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Entities:  

Mesh:

Year:  2011        PMID: 21893519     DOI: 10.1093/bioinformatics/btr499

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  129 in total

1.  Defining the Independence of the Liver Circadian Clock.

Authors:  Kevin B Koronowski; Kenichiro Kinouchi; Patrick-Simon Welz; Jacob G Smith; Valentina M Zinna; Jiejun Shi; Muntaha Samad; Siwei Chen; Christophe N Magnan; Jason M Kinchen; Wei Li; Pierre Baldi; Salvador Aznar Benitah; Paolo Sassone-Corsi
Journal:  Cell       Date:  2019-05-30       Impact factor: 41.582

2.  Metabolomics profiling reveals profound metabolic impairments in mice and patients with Sandhoff disease.

Authors:  Li Ou; Michael J Przybilla; Chester B Whitley
Journal:  Mol Genet Metab       Date:  2018-09-14       Impact factor: 4.797

3.  Large scale non-targeted metabolomic profiling of serum by ultra performance liquid chromatography-mass spectrometry (UPLC-MS).

Authors:  Corey D Broeckling; Adam L Heuberger; Jessica E Prenni
Journal:  J Vis Exp       Date:  2013-03-14       Impact factor: 1.355

4.  Analyzing LC/MS metabolic profiling data in the context of existing metabolic networks.

Authors:  Tianwei Yu; Yun Bai
Journal:  Curr Metabolomics       Date:  2013-01-01

5.  Pyranocoumarin Tissue Distribution, Plasma Metabolome and Prostate Transcriptome Impacts of Sub-Chronic Exposure to Korean Angelica Supplement in Mice.

Authors:  Jinhui Zhang; Li Li; Suni Tang; Yong Zhang; Maciej Markiewski; Chengguo Xing; Cheng Jiang; Junxuan Lü
Journal:  Am J Chin Med       Date:  2016       Impact factor: 4.667

6.  Human Spermatozoa Quantitative Proteomic Signature Classifies Normo- and Asthenozoospermia.

Authors:  Mayank Saraswat; Sakari Joenväärä; Tushar Jain; Anil Kumar Tomar; Ashima Sinha; Sarman Singh; Savita Yadav; Risto Renkonen
Journal:  Mol Cell Proteomics       Date:  2016-11-28       Impact factor: 5.911

7.  Non-oncogene Addiction to SIRT3 Plays a Critical Role in Lymphomagenesis.

Authors:  Meng Li; Ying-Ling Chiang; Costas A Lyssiotis; Matthew R Teater; Jun Young Hong; Hao Shen; Ling Wang; Jing Hu; Hui Jing; Zhengming Chen; Neeraj Jain; Cihangir Duy; Sucharita J Mistry; Leandro Cerchietti; Justin R Cross; Lewis C Cantley; Michael R Green; Hening Lin; Ari M Melnick
Journal:  Cancer Cell       Date:  2019-06-10       Impact factor: 31.743

8.  Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online.

Authors:  Erica M Forsberg; Tao Huan; Duane Rinehart; H Paul Benton; Benedikt Warth; Brian Hilmers; Gary Siuzdak
Journal:  Nat Protoc       Date:  2018-03-01       Impact factor: 13.491

Review 9.  Time is ripe: maturation of metabolomics in chronobiology.

Authors:  Seth D Rhoades; Arjun Sengupta; Aalim M Weljie
Journal:  Curr Opin Biotechnol       Date:  2016-10-01       Impact factor: 9.740

Review 10.  Prospects and challenges of multi-omics data integration in toxicology.

Authors:  Sebastian Canzler; Jana Schor; Wibke Busch; Kristin Schubert; Ulrike E Rolle-Kampczyk; Hervé Seitz; Hennicke Kamp; Martin von Bergen; Roland Buesen; Jörg Hackermüller
Journal:  Arch Toxicol       Date:  2020-02-08       Impact factor: 5.153

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.