Basic category theory for computer scientists
Basic category theory for computer scientists
The POSTGRES next generation database management system
Communications of the ACM
Directed hypergraphs and applications
Discrete Applied Mathematics - Special issue: combinatorial structures and algorithms
Expresso and Chips: Creating a Next Generation Microarray Experiment Management System
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
ISPAN '02 Proceedings of the 2002 International Symposium on Parallel Architectures, Algorithms and Networks
MANTIS: system support for multimodAl NeTworks of in-situ sensors
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
Semantics of Multimodal Network Models
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Semantics of Multimodal Network Models
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Statement networks development environment REx
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part II
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A multimodal network (MMN) is a novel graph-theoretic formalism designed to capture the structure of biological networks and to represent relationships derived from multiple biological databases. MMNs generalize the standard notions of graphs and hypergraphs, which are the bases of current diagrammatic representations of biological phenomena and incorporate the concept of mode. Each vertex of an MMN is a biological entity, a biot, while each modal hyperedge is a typed relationship, where the type is given by the mode of the hyperedge. The current paper defines MMNs and concentrates on the structural aspects of MMNs. A companion paper develops MMNs as a representation of the semantics of biological networks and discusses applications of the MMNs in managing complex biological data. The MMN model has been implemented in a database system containing multiple kinds of biological networks.