Richard D. Hull

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A novel method for computing chemical similarity from chemical substructure descriptors is described. This new method, called LaSSI, uses the singular value decomposition (SVD) of a chemical descriptor-molecule matrix to create a low-dimensional representation of the original descriptor space. Ranking molecules by similarity to a probe molecule in the(More)
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(More)
Similarity searches based on chemical descriptors have proven extremely useful in aiding large-scale drug screening. Here we present results of similarity searching using Latent Semantic Structure Indexing (LaSSI). LaSSI uses a singular value decomposition on chemical descriptors to project molecules into a k-dimensional descriptor space, where k is the(More)
In this study we use a novel similarity search technique called latent semantic structure indexing (LaSSI) with joint chemical probes as queries to mine the MDL drug data report database. LaSSI is based on latent semantic indexing developed for searching textual databases. We use atom pair and topological torsion descriptors in our calculations. The results(More)
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(More)