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|Title:||CoNekT : an open-source framework for comparative genomic and transcriptomic network analyses||Authors:||Proost, Sebastian
|Issue Date:||2018||Source:||Proost, S., & Mutwil, M. (2018). CoNekT: an open-source framework for comparative genomic and transcriptomic network analyses. Nucleic Acids Research, 46(W1), W133-W140. doi:10.1093/nar/gky336||Series/Report no.:||Nucleic Acids Research||Abstract:||The recent accumulation of gene expression data in the form of RNA sequencing creates unprecedented opportunities to study gene regulation and function. Furthermore, comparative analysis of the expression data from multiple species can elucidate which functional gene modules are conserved across species, allowing the study of the evolution of these modules. However, performing such comparative analyses on raw data is not feasible for many biologists. Here, we present CoNekT (Co-expression Network Toolkit), an open source web server, that contains user-friendly tools and interactive visualizations for comparative analyses of gene expression data and co-expression networks. These tools allow analysis and cross-species comparison of (i) gene expression profiles; (ii) co-expression networks; (iii) co-expressed clusters involved in specific biological processes; (iv) tissue-specific gene expression; and (v) expression profiles of gene families. To demonstrate these features, we constructed CoNekT-Plants for green alga, seed plants and flowering plants (Picea abies, Chlamydomonas reinhardtii, Vitis vinifera, Arabidopsis thaliana, Oryza sativa, Zea mays and Solanum lycopersicum) and thus provide a web-tool with the broadest available collection of plant phyla. CoNekT-Plants is freely available from http://conekt.plant.tools, while the CoNekT source code and documentation can be found at https://github.molgen.mpg.de/proost/CoNekT/.||URI:||https://hdl.handle.net/10356/88144
|ISSN:||0305-1048||DOI:||http://dx.doi.org/10.1093/nar/gky336||Rights:||© The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact firstname.lastname@example.org.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SBS Journal Articles|
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