Richard D Hull | PubMed Health

PubMedDate not supplied

CKB - the compound knowledge base: a text based chemical search system.

The Compound Knowledge Base (CKB) was developed as a means of locating structures and additional relevant information from a given known structural identifier. Any of Chemical Abstracts Service Registry Number, company code (code number the producing company refers to the chemical entity internally), generic name (trivial or class name), or trade name (name under which the compound is marketed) can be provided as a query. CKB will provide the remaining available information as well as the corresponding structure for any matching compound in the database. The interface to the Compound Knowledge Base is Internet/World Wide Web-based, using Netscape Navigator and the ChemDraw Pro Plugin, which allows Merck scientists quick and easy access to the database from their desktop. The design and implementation of the database and the search interface are herein detailed.

Journal Article↗

PubMedDate not supplied

Text Influenced Molecular Indexing (TIMI): a literature database mining approach that handles text and chemistry.

We present an application of a novel methodology called Text Influenced Molecular Indexing (TIMI) to mine the information in the scientific literature. TIMI is an extension of two existing methodologies: (1) Latent Semantic Structure Indexing (LaSSI), a method for calculating chemical similarity using two-dimensional topological descriptors, and (2) Latent Semantic Indexing (LSI), a method for generating correlations between textual terms. The singular value decomposition (SVD) of a feature/object matrix is the fundamental mathematical operation underlying LSI, LaSSI, and TIMI and is used in the identification of associations between textual and chemical descriptors. We present the results of our studies with a database containing 11,571 PubMed/MEDLINE abstracts which show the advantages of merging textual and chemical descriptors over using either text or chemistry alone. Our work demonstrates that searching text-only databases limits retrieved documents to those that explicitly mention compounds by name in the text. Similarly, searching chemistry-only databases can only retrieve those documents that have chemical structures in them. TIMI, however, enables search and retrieval of documents with textual, chemical, and/or text- and chemistry-based queries. Thus, the TIMI system offers a powerful new approach to uncovering the contextual scientific knowledge sought by the medical research community.

Algorithms↗