Name
Abstract | ||
|---|---|---|
Despite a lot of advances in biology and genomics, it is still difficult to utilise such valuable knowledge and information to understand and analyse large biological systems due to high computational complexity. In this paper we propose a modular method with which from several small network analyses we analyse a large network by integrating them. This method is based on the qualitative framework proposed by authors in which an analysis of gene networks is reduced to checking satisfiability of linear temporal logic formulae. The problem of linear temporal logic satisfiability checking needs exponential time in the size of a formula. Thus it is difficult to analyse large networks directly in this method since the size of a formula grows linearly to the size of a network. The modular method alleviates this computational difficulty. We show some experimental results and see how we benefit from the modular analysis method. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.2390/biecoll-jib-2013-216 | JOURNAL OF INTEGRATIVE BIOINFORMATICS |
Field | DocType | Volume |
Data mining,Large networks,Exponential function,Computer science,Satisfiability,Linear temporal logic,Theoretical computer science,Modular design,Bioinformatics,Gene regulatory network,Computational complexity theory | Journal | 10 |
Issue | ISSN | Citations |
2 | 1613-4516 | 6 |
PageRank | References | Authors |
0.51 | 11 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sohei Ito | 1 | 32 | 6.22 |
| Takuma Ichinose | 2 | 13 | 1.73 |
| Masaya Shimakawa | 3 | 41 | 7.54 |
| Naoko Izumi | 4 | 20 | 2.95 |
| Shigeki Hagihara | 5 | 78 | 12.33 |
| Naoki Yonezaki | 6 | 107 | 20.02 |