| Added by | jacques.colinge |
|---|---|
| Group name | EquipeJC |
| Item Type | Journal Article |
| Title | Application of modular response analysis to medium- to large-size biological systems |
| Creator | Mekedem et al. |
| Author | Meriem Mekedem |
| Author | Patrice Ravel |
| Author | Jacques Colinge |
| Abstract | The development of high-throughput genomic technologies associated with recent genetic perturbation techniques such as short hairpin RNA (shRNA), gene trapping, or gene editing (CRISPR/Cas9) has made it possible to obtain large perturbation data sets. These data sets are invaluable sources of information regarding the function of genes, and they offer unique opportunities to reverse engineer gene regulatory networks in specific cell types. Modular response analysis (MRA) is a well-accepted mathematical modeling method that is precisely aimed at such network inference tasks, but its use has been limited to rather small biological systems so far. In this study, we show that MRA can be employed on large systems with almost 1,000 network components. In particular, we show that MRA performance surpasses general-purpose mutual information-based algorithms. Part of these competitive results was obtained by the application of a novel heuristic that pruned MRA-inferred interactions a posteriori. We also exploited a block structure in MRA linear algebra to parallelize large system resolutions. |
| Publication | PLoS computational biology |
| Volume | 18 |
| Issue | 4 |
| Pages | e1009312 |
| Date | 2022-04 |
| Journal Abbr | PLoS Comput Biol |
| Language | eng |
| DOI | 10.1371/journal.pcbi.1009312 |
| ISSN | 1553-7358 |
| Library Catalog | PubMed |
| Extra | PMID: 35442961 PMCID: PMC9060349 |
| Tags | Algorithms, corresponding, Gene Editing, Gene Regulatory Networks, last, original, phd |
| Date Added | 2022/07/29 - 09:32:50 |
| Date Modified | 2022/07/29 - 09:33:07 |
| Notes and Attachments | PubMed entry (Attachment) Texte intégral (Attachment) |
Institut de Recherche en Cancérologie de
