Name
Abstract | ||
|---|---|---|
In this paper, we propose a methodology for making sense of large, multiple time-series data sets arising in expression analysis. Specifically, we present a mathematical model to release a reduced and coherent regulatory system given a putative regulatory network. We give two equivalent formulations of the problem and prove that the problem is NP-complete. For solving large scale instances we implemented an Ant Colony Optimization procedure. A computational analysis on randomly generated test instances validates the proposed algorithm and the computations on real data concerning Saccharomyces cerevisiae show the practicability of the proposed methodology. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.dam.2008.06.044 | Discrete Applied Mathematics |
Keywords | Field | DocType |
gene regulatory networks,reverse engineering,computational analysis,expression analysis,ant colony optimization procedure,gene regulatory network,coherent regulatory system,large scale instance,proposed algorithm,multiple time-series data,proposed methodology,putative regulatory network,ant colony optimization,mathematical programming,mathematical program,mathematical model | Ant colony optimization algorithms,Discrete mathematics,Data set,NP-complete,Computer science,Reverse engineering,Expression analysis,Algorithm,Theoretical computer science,Gene regulatory network,Computational analysis,Computation | Journal |
Volume | Issue | ISSN |
157 | 10 | Discrete Applied Mathematics |
Citations | PageRank | References |
4 | 0.47 | 20 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guglielmo Lulli | 1 | 205 | 18.82 |
| Martin Romauch | 2 | 72 | 5.42 |