Title
MANIA: A GENE NETWORK REVERSE ALGORITHM FOR COMPOUNDS MODE-OF-ACTION AND GENES INTERACTIONS INFERENCE
Abstract
Understanding the complexity of the cellular machinery represents a grand challenge in molecular biology. To contribute to the deconvolution of this complexity, a novel inference algorithm based on linear ordinary differential equations is proposed, based solely on high-throughput gene expression data. The algorithm can infer (i) gene-gene interactions from steady state expression profiles and (ii) mode-of-action of the components that can trigger changes in the system. Results demonstrate that the proposed algorithm can identify both information with high performances, thus overcoming the limitation of current algorithms that can infer reliably only one.
Year
DOI
Venue
2009
10.1142/S0219525910002451
ADVANCES IN COMPLEX SYSTEMS
Keywords
Field
DocType
Gene network,gene expression,reverse engineering,ordinary differential equations (ODE),compound mode-of-action
Gene,Ordinary differential equation,Inference,Reverse engineering,Deconvolution,Algorithm,Artificial intelligence,Gene regulatory network,Mode of action,Mathematics,Machine learning
Conference
Volume
Issue
ISSN
13
1
0219-5259
Citations 
PageRank 
References 
0
0.34
5
Authors
5
Name
Order
Citations
PageRank
Darong Lai1102.57
Hongtao Lu273593.14
Mario Lauria362895.12
DIGEO DI BERNARDO400.34
Christine Nardini5659.00