TY - GEN
T1 - Completing SBGN-AF networks by logic-based hypothesis finding
AU - Yamamoto, Yoshitaka
AU - Rougny, Adrien
AU - Nabeshima, Hidetomo
AU - Inoue, Katsumi
AU - Moriya, Hisao
AU - Froidevaux, Christine
AU - Iwanuma, Koji
N1 - Copyright:
Copyright 2016 Elsevier B.V., All rights reserved.
PY - 2014
Y1 - 2014
N2 - This study considers formal methods for finding unknown interactions of incomplete molecular networks using microarray profiles. In systems biology, a challenging problem lies in the growing scale and complexity of molecular networks. Along with high-throughput experimental tools, it is not straightforward to reconstruct huge and complicated networks using observed data by hand. Thus, we address the completion problem of our target networks represented by a standard markup language, called SBGN (in particular, Activity Flow). Our proposed method is based on logic-based hypothesis finding techniques; given an input SBGN network and its profile data, missing interactions can be logically generated as hypotheses by the proposed method. In this paper, we also show empirical results that demonstrate how the proposed method works with a real network involved in the glucose repression of S. cerevisiae.
AB - This study considers formal methods for finding unknown interactions of incomplete molecular networks using microarray profiles. In systems biology, a challenging problem lies in the growing scale and complexity of molecular networks. Along with high-throughput experimental tools, it is not straightforward to reconstruct huge and complicated networks using observed data by hand. Thus, we address the completion problem of our target networks represented by a standard markup language, called SBGN (in particular, Activity Flow). Our proposed method is based on logic-based hypothesis finding techniques; given an input SBGN network and its profile data, missing interactions can be logically generated as hypotheses by the proposed method. In this paper, we also show empirical results that demonstrate how the proposed method works with a real network involved in the glucose repression of S. cerevisiae.
KW - SBGN
KW - completion
KW - glucose repression
KW - hypothesis finding
UR - http://www.scopus.com/inward/record.url?scp=84906334379&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84906334379&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-10398-3_14
DO - 10.1007/978-3-319-10398-3_14
M3 - Conference contribution
AN - SCOPUS:84906334379
SN - 9783319103976
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 165
EP - 179
BT - Formal Methods in Macro-Biology - First International Conference, FMMB 2014, Proceedings
A2 - Piazza, Carla
A2 - Fages, François
PB - Springer Verlag
T2 - 1st International Conference on Formal Methods in Macro-Biology, FMMB 2014
Y2 - 22 September 2014 through 24 September 2014
ER -