Reiter [3] has developed a general theory of diagnosis based on first principles. His
algorithm computes all diagnoses which explain the differences between the predicted and …

In this paper, we empirically evaluate algorithms for learning four types of Bayesian network
(BN) classifiers - Naive-Bayes, tree augmented Naive-Bayes, BN augmented Naive-Bayes …

The Human Metabolome Database or HMDB ( https://hmdb.ca ) has been providing
comprehensive reference information about human metabolites and their associated biological, …

The book under review here, Building Large Knowledge-Based Systems: Representation and
Inference in the Cyc Project, describes progress so far in an attempt to build a system that …

Background Scientists have long been driven by the desire to describe, organize, classify,
and compare objects using taxonomies and/or ontologies. In contrast to biology, geology, and …

In the field of metabolomics, mass spectrometry (MS) is the method most commonly used for
identifying and annotating metabolites. As this typically involves matching a given MS …

This paper investigates the methods for learning predictive classifiers based on Bayesian
belief networks (BN) — primarily unrestricted Bayesian networks and Bayesian multi-nets. We …

Motivation: Identifying the destination or localization of proteins is key to understanding their
function and facilitating their purification. A number of existing computational prediction …

The Human Metabolome Database (HMDB) is currently the most complete and comprehensive
curated collection of human metabolite and human metabolism data in the world. It …

The Human Metabolome Database (HMDB) ( www.hmdb.ca ) is a resource dedicated to
providing scientists with the most current and comprehensive coverage of the human …