BIND—The Biomolecular Interaction Network Database

The Biomolecular Interaction Network Database (BIND; http://binddb.org) is a database designed to store full descriptions of interactions, molecular complexes and pathways. Development of the BIND 2.0 data model has led to the incorporation of virtually all components of molecular mechanisms including interactions between any two molecules composed of proteins, nucleic acids and small molecules. Chemical reactions, photochemical activation and conformational changes can also be described. Everything from small molecule biochemistry to signal transduction is abstracted in such a way that graph theory methods may be applied for data mining. The database can be used to study networks of interactions, to map pathways across taxonomic branches and to generate information for kinetic simulations. BIND anticipates the coming large influx of interaction information from high-throughput proteomics efforts including detailed information about post-translational modifications from mass spectrometry. Version 2.0 of the BIND data model is discussed as well as implementation, content and the open nature of the BIND project. The BIND data specification is available as ASN.1 and XML DTD.

Deficient generalized Fibonacci maximum path graphs /

"UILU-ENG 78 1739."

Generalized Ramsey numbers for stars /

"UIUCDCS-R-81-1050"--Cover.

On the ordering, enumeration and ranking of k-ary trees /

"UILU-ENG 77 1706."

Decomposition of graphs into trees /

"UILU-ENG 77 1715."

Weak congruence relations on graphs /

Vita.

Canonical simplification of finite objects, well quasi-ordered by tree embedding /

"UILU-ENG 79 1727."

On the complexity of edge labelings for trees /

"UILU-ENG 78 1740."

Parallel algorithms for network routing problems and recurrences /

"Grant no. US NSF MCS75-21758."

A tricolor cartograph,

"COO-1469-0102."

Average analysis of simple path algorithms /

"UILU-ENG 77 1759."

On random 3-2 trees /

"UIUCDCS-R-74-679"

Enumerations of ordered trees /

Errata slip inserted.

Extension of the Huffman tree construction algorithm /

Bibliography: p. 42-43.

Generating binary trees lexicographically /

Bibliography: p. 26.