Improving gene regulatory network inference and assessment: The importance of using network structure
Por:
Escorcia-Rodriguez, Juan M., Gaytan-Nunez, Estefani, Hernandez-Benitez, Ericka M., Zorro-Aranda, Andrea, Tello-Palencia, Marco A., Freyre-Gonzalez, Julio A.
Publicada:
27 feb 2023
Resumen:
Gene regulatory networks are graph models representing cellular
transcription events. Networks are far from complete due to time and
resource consumption for experimental validation and curation of the
interactions. Previous assessments have shown the modest performance of
the available network inference methods based on gene expression data.
Here, we study several caveats on the inference of regulatory networks
and methods assessment through the quality of the input data and gold
standard, and the assessment approach with a focus on the global
structure of the network. We used synthetic and biological data for the
predictions and experimentally-validated biological networks as the gold
standard (ground truth). Standard performance metrics and graph
structural properties suggest that methods inferring co-expression
networks should no longer be assessed equally with those inferring
regulatory interactions. While methods inferring regulatory interactions
perform better in global regulatory network inference than
co-expression-based methods, the latter is better suited to infer
function-specific regulons and co-regulation networks. When merging
expression data, the size increase should outweigh the noise inclusion
and graph structure should be considered when integrating the
inferences. We conclude with guidelines to take advantage of inference
methods and their assessment based on the applications and available
expression datasets.
Filiaciones:
Escorcia-Rodriguez, Juan M.:
Univ Nacl Autonoma Mexico, Ctr Genom Sci, Program Syst Biol, Regulatory Syst Biol Res Grp, Cuernavaca, Mexico
Gaytan-Nunez, Estefani:
Univ Nacl Autonoma Mexico, Ctr Genom Sci, Program Syst Biol, Regulatory Syst Biol Res Grp, Cuernavaca, Mexico
Univ Nacl Autonoma Mexico, Ctr Genom Sci, Undergrad Program Genom Sci, Cuernavaca, Mexico
Hernandez-Benitez, Ericka M.:
Univ Nacl Autonoma Mexico, Ctr Genom Sci, Program Syst Biol, Regulatory Syst Biol Res Grp, Cuernavaca, Mexico
Univ Nacl Autonoma Mexico, Ctr Genom Sci, Undergrad Program Genom Sci, Cuernavaca, Mexico
Zorro-Aranda, Andrea:
Univ Nacl Autonoma Mexico, Ctr Genom Sci, Program Syst Biol, Regulatory Syst Biol Res Grp, Cuernavaca, Mexico
Univ Antioquia, Dept Chem Engn, Medellin, Colombia
Tello-Palencia, Marco A.:
Univ Nacl Autonoma Mexico, Ctr Genom Sci, Program Syst Biol, Regulatory Syst Biol Res Grp, Cuernavaca, Mexico
Univ Nacl Autonoma Mexico, Ctr Genom Sci, Undergrad Program Genom Sci, Cuernavaca, Mexico
Freyre-Gonzalez, Julio A.:
Univ Nacl Autonoma Mexico, Ctr Genom Sci, Program Syst Biol, Regulatory Syst Biol Res Grp, Cuernavaca, Mexico
gold, Green Accepted, Green Submitted, Gold, Green
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