| Added by | jacques.colinge |
|---|---|
| Group name | EquipeJC |
| Item Type | Journal Article |
| Title | Modular response analysis reformulated as a multilinear regression problem |
| Creator | Borg et al. |
| Author | Jean-Pierre Borg |
| Author | Jacques Colinge |
| Author | Patrice Ravel |
| Abstract | MOTIVATION: Modular response analysis (MRA) is a well-established method to infer biological networks from perturbation data. Classically, MRA requires the solution of a linear system, and results are sensitive to noise in the data and perturbation intensities. Due to noise propagation, applications to networks of 10 nodes or more are difficult. RESULTS: We propose a new formulation of MRA as a multilinear regression problem. This enables to integrate all the replicates and potential additional perturbations in a larger, over-determined and more stable system of equations. More relevant confidence intervals on network parameters can be obtained, and we show competitive performance for networks of size up to 1,000. Prior knowledge integration in the form of known null edges further improves these results. AVAILABILITY: The R code used to obtain the presented results is available from GitHub: https://github.com/J-P-Borg/BioInformatics. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
| Publication | Bioinformatics (Oxford, England) |
| Pages | btad166 |
| Date | 2023-04-06 |
| Journal Abbr | Bioinformatics |
| Language | eng |
| DOI | 10.1093/bioinformatics/btad166 |
| ISSN | 1367-4811 |
| Library Catalog | PubMed |
| Extra | PMID: 37021935 |
| Tags | corresponding, first, last, phd |
| Date Added | 2023/04/07 - 14:21:03 |
| Date Modified | 2024/09/08 - 16:56:57 |
| Notes and Attachments | PubMed entry (Attachment) |
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