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PathwAX: a web server for network crosstalk based pathway annotation
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Number of Authors: 3
2016 (English)In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 44, no W1, W105-W109 p.Article in journal (Refereed) Published
Abstract [en]

Pathway annotation of gene lists is often used to functionally analyse biomolecular data such as gene expression in order to establish which processes are activated in a given experiment. Databases such as KEGG or GO represent collections of how genes are known to be organized in pathways, and the challenge is to compare a given gene list with the known pathways such that all true relations are identified. Most tools apply statistical measures to the gene overlap between the gene list and pathway. It is however problematic to avoid false negatives and false positives when only using the gene overlap. The pathwAX web server (http://pathwAX.sbc.su.se/) applies a different approach which is based on network crosstalk. It uses the comprehensive network FunCoup to analyse network crosstalk between a query gene list and KEGG pathways. PathwAX runs the BinoX algorithm, which employs Monte-Carlo sampling of randomized networks and estimates a binomial distribution, for estimating the statistical significance of the crosstalk. This results in substantially higher accuracy than gene overlap methods. The system was optimized for speed and allows interactive web usage. We illustrate the usage and output of pathwAX.

Place, publisher, year, edition, pages
2016. Vol. 44, no W1, W105-W109 p.
National Category
Biological Sciences
Research subject
Biochemistry towards Bioinformatics
Identifiers
URN: urn:nbn:se:su:diva-133398DOI: 10.1093/nar/gkw356ISI: 000379786800018PubMedID: 27151197OAI: oai:DiVA.org:su-133398DiVA: diva2:958284
Available from: 2016-09-06 Created: 2016-09-06 Last updated: 2017-09-06Bibliographically approved
In thesis
1. Global functional association network inference and crosstalk analysis for pathway annotation
Open this publication in new window or tab >>Global functional association network inference and crosstalk analysis for pathway annotation
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Cell functions are steered by complex interactions of gene products, like forming a temporary or stable complex, altering gene expression or catalyzing a reaction. Mapping these interactions is the key in understanding biological processes and therefore is the focus of numerous experiments and studies. Small-scale experiments deliver high quality data but lack coverage whereas high-throughput techniques cover thousands of interactions but can be error-prone. Unfortunately all of these approaches can only focus on one type of interaction at the time. This makes experimental mapping of the genome-wide network a cost and time intensive procedure. However, to overcome these problems, different computational approaches have been suggested that integrate multiple data sets and/or different evidence types. This widens the stringent definition of an interaction and introduces a more general term - functional association. 

FunCoup is a database for genome-wide functional association networks of Homo sapiens and 16 model organisms. FunCoup distinguishes between five different functional associations: co-membership in a protein complex, physical interaction, participation in the same signaling cascade, participation in the same metabolic process and for prokaryotic species, co-occurrence in the same operon. For each class, FunCoup applies naive Bayesian integration of ten different evidence types of data, to predict novel interactions. It further uses orthologs to transfer interaction evidence between species. This considerably increases coverage, and allows inference of comprehensive networks even for not well studied organisms. 

BinoX is a novel method for pathway analysis and determining the relation between gene sets, using functional association networks. Traditionally, pathway annotation has been done using gene overlap only, but these methods only get a small part of the whole picture. Placing the gene sets in context of a network provides additional evidence for pathway analysis, revealing a global picture based on the whole genome.

PathwAX is a web server based on the BinoX algorithm. A user can input a gene set and get online network crosstalk based pathway annotation. PathwAX uses the FunCoup networks and 280 pre-defined pathways. Most runs take just a few seconds and the results are summarized in an interactive chart the user can manipulate to gain further insights of the gene set's pathway associations.

Place, publisher, year, edition, pages
Stockholm: Department of Biochemistry and Biophysics, Stockholm University, 2017
Keyword
biological networks, genome wide functional association networks, global gene association networks, gene networks, protein networks, functional association, functional coupling, network biology pathway analysis, pathway annotation, pathway enrichment, network-based enrichment, enrichment
National Category
Bioinformatics and Systems Biology
Research subject
Biochemistry towards Bioinformatics
Identifiers
urn:nbn:se:su:diva-146703 (URN)978-91-7649-950-4 (ISBN)978-91-7649-951-1 (ISBN)
Public defence
2017-10-20, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Stochkolm, 13:00 (English)
Opponent
Supervisors
Note

At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 2: Manuscript.

Available from: 2017-09-27 Created: 2017-09-06 Last updated: 2017-09-20Bibliographically approved

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