@inproceedings{1206bf129fe049a18087632994134210,
title = "Building Differential Co-expression Networks with Variable Selection and Regularization",
abstract = "This work introduces a technique for the inference of differential co-expression networks. The approach takes as input a matrix of differential expression profiles, where each entry corresponds to the Log Fold Change of a gene expression between control and stress conditions for a specific sample. It outputs a matrix of coefficients, where each non-zero entry represents a pairwise connection between genes. The proposed approach builds on Lasso, and is applied to differential expression profiles of rice between control and salt-stress conditions. A total of 25 genes were identified to respond to salt stress and as differentially expressed. About half of these genes (11) were reported with a statistically significant number of different GO annotations relevant to salt stress response.",
keywords = "Lasso-based inference, Network inference, Oryza sativa, Overlapping clustering, Rice, Salt-stress",
author = "Camila Riccio and Jorge Finke and Camilo Rocha",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 11th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2022 ; Conference date: 08-11-2022 Through 10-11-2022",
year = "2023",
doi = "10.1007/978-3-031-21127-0_23",
language = "English",
isbn = "9783031211263",
series = "Studies in Computational Intelligence",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "277--288",
editor = "Hocine Cherifi and Mantegna, {Rosario Nunzio} and Rocha, {Luis M.} and Chantal Cherifi and Salvatore Miccich{\`e}",
booktitle = "Complex Networks and Their Applications XI - Proceedings of The 11th International Conference on Complex Networks and Their Applications",
address = "Germany",
}