Name
Abstract | ||
|---|---|---|
In this paper we propose the use of answer set programming (ASP) to model protein interaction networks. We argue that this declarative formalism rivals the popular boolean networks in terms of ease of use, while at the same time being more expressive. As we demonstrate for the particularcase of a fission yeast network, all information present in a boolean network, as well as relevant background assumptions,can be expressed explicitly in an answer set program. Moreover, readily available answer set solvers can then be used to find the stable states of the network. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/BIBM.2009.9 | BIBM |
Keywords | Field | DocType |
answer set program,fission yeast network,declarative formalism rival,model protein interaction network,modeling protein interaction networks,relevant background assumption,boolean network,available answer set solvers,answer set programming,popular boolean network,information present,trajectory,boolean algebra,artificial intelligent,proteins,artificial intelligence,data mining,molecular biophysics,ease of use,programming,logic | Boolean network,Computer science,Stable states,Theoretical computer science,Stable model semantics,Artificial intelligence,Answer set programming,Protein Interaction Networks,Usability,Boolean algebra,Formalism (philosophy),Bioinformatics,Machine learning | Conference |
ISSN | Citations | PageRank |
2156-1125 | 11 | 0.67 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Timur Fayruzov | 1 | 65 | 4.02 |
| Martine De Cock | 2 | 1341 | 96.06 |
| Chris Cornelis | 3 | 2116 | 113.39 |
| Dirk Vermeir | 4 | 694 | 85.34 |