Latent Semantic Structure Indexing
Encyclopedia
Latent semantic structure indexing (LaSSI) is a technique for calculating chemical similarity derived from latent semantic analysis
(LSA).
LaSSI was developed at Merck & Co.
and patented in 2007 http://patft.uspto.gov/netacgi/nph-Parser?patentnumber=7219020 by Richard Hull, Eugene Fluder, Suresh Singh, Robert Sheridan, Robert Nachbar and Simon Kearsley.
to that matrix to derive latent features. What differs is that the occurrence matrix represents the frequency of two- and three-dimensional chemical descriptors (rather than natural language terms) found within a chemical database
of chemical structures. This process derives latent chemical structure concepts that can be used to calculate chemical similarities and structure–activity relationships for drug discovery
.
Latent semantic analysis
Latent semantic analysis is a technique in natural language processing, in particular in vectorial semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. LSA assumes that words that are close...
(LSA).
LaSSI was developed at Merck & Co.
Merck & Co.
Merck & Co., Inc. , also known as Merck Sharp & Dohme or MSD outside the United States and Canada, is one of the largest pharmaceutical companies in the world. The Merck headquarters is located in Whitehouse Station, New Jersey, an unincorporated area in Readington Township...
and patented in 2007 http://patft.uspto.gov/netacgi/nph-Parser?patentnumber=7219020 by Richard Hull, Eugene Fluder, Suresh Singh, Robert Sheridan, Robert Nachbar and Simon Kearsley.
Overview
LaSSI is similar to LSA in that it involves the construction of an occurrence matrix from a corpus of items and the application of singular value decompositionSingular value decomposition
In linear algebra, the singular value decomposition is a factorization of a real or complex matrix, with many useful applications in signal processing and statistics....
to that matrix to derive latent features. What differs is that the occurrence matrix represents the frequency of two- and three-dimensional chemical descriptors (rather than natural language terms) found within a chemical database
Chemical database
A chemical database is a database specifically designed to store chemical information. This information is about chemical and crystal structures, spectra, reactions and syntheses, and thermophysical data.- Chemical structures :...
of chemical structures. This process derives latent chemical structure concepts that can be used to calculate chemical similarities and structure–activity relationships for drug discovery
Drug discovery
In the fields of medicine, biotechnology and pharmacology, drug discovery is the process by which drugs are discovered or designed.In the past most drugs have been discovered either by identifying the active ingredient from traditional remedies or by serendipitous discovery...
.