New Results
Exploiting general independence criteria for network inference
Petras Verbyla, Nina Desgranges, View ORCID ProfileSylvia Richardson, View ORCID ProfileLorenz Wernisch
doi: https://doi.org/10.1101/138669
Petras Verbyla
MRC Biostatistics Unit, Cambridge Biomedical Campus, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge CB2 0SR, UK
Nina Desgranges
MRC Biostatistics Unit, Cambridge Biomedical Campus, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge CB2 0SR, UK
Sylvia Richardson
MRC Biostatistics Unit, Cambridge Biomedical Campus, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge CB2 0SR, UK
Lorenz Wernisch
MRC Biostatistics Unit, Cambridge Biomedical Campus, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge CB2 0SR, UK
Article usage
Posted May 17, 2017.
Exploiting general independence criteria for network inference
Petras Verbyla, Nina Desgranges, Sylvia Richardson, Lorenz Wernisch
bioRxiv 138669; doi: https://doi.org/10.1101/138669
Subject Area
Subject Areas
- Biochemistry (11699)
- Bioengineering (8715)
- Bioinformatics (29119)
- Biophysics (14927)
- Cancer Biology (12047)
- Cell Biology (17347)
- Clinical Trials (138)
- Developmental Biology (9405)
- Ecology (14138)
- Epidemiology (2067)
- Evolutionary Biology (18261)
- Genetics (12216)
- Genomics (16760)
- Immunology (11839)
- Microbiology (27996)
- Molecular Biology (11549)
- Neuroscience (60781)
- Paleontology (450)
- Pathology (1864)
- Pharmacology and Toxicology (3228)
- Physiology (4937)
- Plant Biology (10382)
- Synthetic Biology (2876)
- Systems Biology (7332)
- Zoology (1642)