Network inference

January 31, 2025

  1. ebdbNet: Empirical Bayes estimation for dynamic Bayesian networks 🔗

  1. Monneret, G., Jaffrézic, F., Rau, A., Zerjal, T. and Nuel, G. (2017) Identification of marginal causal relationships in gene networks from observational and interventional expression data. PLoS One, 12(3): e0171142. 🔗 📄 🔢

  2. Monneret, G., Jaffrézic, F., Rau, A., Nuel, G. (2015) Estimation d’effets causaux dans les réseaux de régulation génique : vers la grande dimension. Revue d’intelligence artificielle, 29(2): 205-227. 📄 🔢

  3. Nuel, G., Rau, A., and Jaffrézic, F. (2013) Using pairwise ordering preferences to estimate causal effects in gene expression from a mixture of observational and intervention experiments.. Quality Technology and Quantitative Management, 11(1):23-37. 🔗 📄

  4. Rau, A., Jaffrézic, F., and Nuel, G. (2013) Joint estimation of causal effects from observational and intervention gene expression data. BMC Systems Biology, 8:51. 🔗 📄 🔢

  5. Gallopin, M. Rau, A., and Jaffrézic, F. (2013) A hierarchical Poisson log-normal model for network inference from RNA sequencing data. PLoS One, 8(10): e77503. 🔗 📄

  6. Rau, A., Jaffrézic, F., Foulley, J.-L., and Doerge, R. W. (2012) Reverse engineering gene regulatory networks using approximate Bayesian computation. Statistics and Computing, 22: 1257-1271. 🔗 📄 🔄

  7. Rau, A., Jaffrézic, F., Foulley, J.-L., and Doerge, R. W. (2010) An empirical Bayesian method for estimating biological networks from temporal microarray data. Statistical Applications in Genetics and Molecular Biology, 9(1): 9. 🔗 📄 💻

Posted on:
January 31, 2025
Length:
2 minute read, 227 words
Categories:
projects
Tags:
hugo-site
See Also:
RNA-seq co-expression
Multi-omic data integration
Applications in animal, plant, and human genomics