TY - GEN
T1 - Algorithms for regular tree grammar network search and their application to mining human-viral infection patterns
AU - Smoly, Ilan
AU - Carmel, Amir
AU - Shemer-Avni, Yonat
AU - Yeger-Lotem, Esti
AU - Ziv-Ukelson, Michal
N1 - Funding Information:
We thank the anonymous WABI referees for their many helpful comments.The work of Ilan Smoly, Amir Carmel and Michal Ziv-Ukelson was partially supported by the Frankel Center for Computer Science at Ben Gurion University of the Negev and by the Israel Science Foundation (ISF 179/14).
Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - Network querying is a powerful approach to mine molecular interaction networks. Most network querying tools support queries in the form of a template sub-network, in case of topology-constrained queries, or a set of colored vertices in case of topology-free queries. A third approach is grammar-based queries, which are more flexible and expressive as they allow the addition of logic rules to the query. Previous grammar-based querying tools defined queries via string grammars and identified paths in graphs. In this paper, we extend the scope of grammar-based queries to regular tree grammar (RTG), and the scope of the identified sub-graphs from paths to trees. We introduce a new problem and propose a novel algorithm to search a given graph for the k highest scoring sub-graphs matching a tree accepted by an RTG. Our algorithm is based on dynamic programming and combines an extension to k-best parsing optimization with color coding. We implement the new algorithm and exemplify its application to mining the human-viral interaction network. Our code is available at http://www.cs.bgu.ac.il/~smolyi/RTGnet/.
AB - Network querying is a powerful approach to mine molecular interaction networks. Most network querying tools support queries in the form of a template sub-network, in case of topology-constrained queries, or a set of colored vertices in case of topology-free queries. A third approach is grammar-based queries, which are more flexible and expressive as they allow the addition of logic rules to the query. Previous grammar-based querying tools defined queries via string grammars and identified paths in graphs. In this paper, we extend the scope of grammar-based queries to regular tree grammar (RTG), and the scope of the identified sub-graphs from paths to trees. We introduce a new problem and propose a novel algorithm to search a given graph for the k highest scoring sub-graphs matching a tree accepted by an RTG. Our algorithm is based on dynamic programming and combines an extension to k-best parsing optimization with color coding. We implement the new algorithm and exemplify its application to mining the human-viral interaction network. Our code is available at http://www.cs.bgu.ac.il/~smolyi/RTGnet/.
UR - http://www.scopus.com/inward/record.url?scp=84945960792&partnerID=8YFLogxK
U2 - 10.1007/978-3-662-48221-6_4
DO - 10.1007/978-3-662-48221-6_4
M3 - Conference contribution
AN - SCOPUS:84945960792
SN - 9783662482209
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 53
EP - 65
BT - Algorithms in Bioinformatics - 15th International Workshop, WABI 2015, Proceedings
A2 - Pop, Mihai
A2 - Touzet, Hélène
PB - Springer Verlag
T2 - 15th International Workshop on Algorithms in Bioinformatics, WABI 2015
Y2 - 10 September 2015 through 12 September 2015
ER -