About GeneBridge
The functions of many eukaryotic genes are still poorly understood. GeneBridge is a newly developed systems approach with two linked methods to impute gene function and bridge genes with biological processes. First, Gene-Module Association Determination (G-MAD) allows the annotation of gene function. Second, Module-Module Association Determination (M-MAD) allows predicting connectivity among modules. We applied the GeneBridge tools to large-scale multi-species expression compendia-1,700 datasets with over 300,000 samples from human, mouse, rat, fly, worm, and yeast-collected in this study. Unlike most existing bioinformatics tools, GeneBridge exploits both positive and negative gene/module-module associations. We constructed association networks, such as those bridging mitochondria and proteasome, mitochondria and histone demethylation, as well as ribosomes and lipid biosynthesis. The GeneBridge tools together with the expression compendia are available at systems-genetics.org, to facilitate the identification of connections linking genes, modules, phenotypes, and diseases.
How to cite:
Li H, Rukina D, David F, Li TY, Oh C-M, Gao AW, Katsyuba E, Bou Sleiman M, Komljenovic A, Huang Q, Williams RW, Robinson-Rechavi M, Schoonjans K, Morgenthaler S, Auwerx J. Identifying gene function and module connections by the integration of multi-species expression compendia. Genome research.
Team
The webtools and multi-layered systems approaches were developed, validated by Hao Li under the supervision of Prof. Johan Auwerx at EPFL. The website was created and implemented by Dr. David Fabrice from SV-IT/GECF at EPFL. We appreciate the help from the Stephan Morgenthaler lab at EPFL, Kristina Schoonjans lab at EPFL, Marc Robinson-Rechavi lab at UNIL, Robert W. Williams lab at University of Tennessee for the help in bioinformatics and biostatistics. We thank the lab members in Auwerx lab for the help in experimental validations and discussions. We are grateful to the research community for generating the valuable resource for systems biology research.Funding
This work was supported by grants from the Ecole Polytechnique Fédérale de Lausanne (EPFL), the European Research Council (ERC-AdG-787702), the Swiss National Science Foundation (SNSF 31003A_179435), the GRL grant of the National Research Foundation of Korea (NRF 2017K1A1A2013124), the AgingX program of the Swiss Initiative for Systems Biology (RTD 2013/153), and the National Institutes of Health (R01AG043930).
Contact us:
If you have any questions or comments when using the web tools, please feel free to contact us through admin.auwerx@epfl.ch.
About BXD methods
Overview
The webtools make use of the multilayered datasets from the BXD mouse population to expedite in silico gene function prediction through a series of integrative and complimentary systems analytical approaches.
How to cite
Please use the following citations when referring to our work:
Li H, Wang X, Rukina D, Huang Q, Lin T, Sorrentino V, Zhang H, Arends D, McDaid A, Luan P, Ziari N, Velázquez-Villegas LA, Gariani K, Kutalik Z, Schoonjans K, Radcliffe RA, Prins P, Morgenthaler S, Williams RW, Auwerx J, An integrated systems genetics and omics toolkit to probe gene function Cell Systems (2018) 6, 90-102. DOI: http://dx.doi.org/10.1016/j.cels.2017.10.016
Team
The webtools and multi-layered systems approaches were developed, validated, and implemented by Hao Li, a PhD student under the supervision of Prof. Johan Auwerx at EPFL. We appreciate the help from Robert W. Williams lab at University of Tennessee, Stephan Morgenthaler lab at EPFL, Kristina Schoonjans lab at EPFL, Zoltan Kutalik lab at CHUV for the help in genetics, bioinformatics and biostatistics. We thank the lab members in Auwerx lab for the help in data collection, experimental validations and discussions. We are grateful to the BXD community for generating the valuable resource for systems biology research.
Funding sources
This work was supported by grants from the Ecole Polytechnique Fédérale de Lausanne, the Swiss National Science Foundation (31003A-140780), the Velux Stiftung, the Kristian Gerhard Jebsen Foundation; the AgingX program of the Swiss Initiative for Systems Biology (51RTP0-151019), and the NIH (R01AG043930, R01AA016957).
Contact us
If you have any questions or comments when using the web tools, please feel free to contact us through admin.auwerx@epfl.ch