The IUBMB enzyme nomenclature decision tree

Abstract only availableThis project attempts to map the decisions involved in categorizing an enzyme using the International Union of Biochemistry and Molecular Biology (IUBMB) enzyme nomenclature. The recommendations of the Nomenclature Committee of IUBMB on the nomenclature and classification of enzyme-catalyzed reactions is complex and archaic, with rules that almost always have an exception. The IUBMB enzyme nomenclature was devised in 1961 by the first Enzyme Commission. It is a system of categorizing enzymes based on the biochemical reactions they catalyze. The system categorizes an enzyme into one of six main classes (oxidoreductases, transferases, hydrolases, lyases, isomerases, and ligases), a subclass, and a subsubclass based on the element of the biochemical reaction equation, such as the biochemical acceptor and donor. This research project looks at the IUBMB enzyme nomenclature with the purpose of defining a decision tree that would closely represent its taxonomy. The tree would be used in the programming of an automatic enzyme classifier, which when given the biochemical equation that an enzyme catalyzes, categorizes the enzyme in its final subsubclass. Techniques, such as the statistical analysis of chemical equation topologies and compound distribution, have been used to avoid the necessity of programming the underlying principals of chemistry, such as how to distinguish if a reaction is an oxidation-reduction reaction. This project is ongoing.National Library of Medicine Training Gran

Bioinformatics models in drug abuse and Neuro-AIDS: Using and developing databases

The magnitude of the problems of drug abuse and Neuro-AIDS warrants the development of novel approaches for testing hypotheses in diagnosis and treatment ranging from cell culture models to developing databases. In this study, cultured neurons were treated with/without HIV-TAT, ENV, or cocaine in a 2x2x2 expression study design. RNA was purified, labeled, and expression data were produced and analyzed using ANOVA. Thus, we identified 35 genes that were significantly expressed across treatment conditions. A diagram is presented showing examples of molecular relationships involving a significantly expressed gene in the current study (SOX2). Also, we use this information to discuss examples of gene expression interactions as a means to portray significance and complexity of gene expression studies in Drug Abuse and Neuro-AIDS. Furthermore, we discuss here that critical interactions remain undetected, which may be unravelled by developing robust database systems containing large datasets and gleaned information from collaborating scientists . Hence, we are developing a public domain database we named The Agora database , that will served as a shared infrastructure to query, deposit, and review information related to drug abuse and dementias including Neuro-AIDS. A workflow of this database is also outlined in this paper

Putting semantics into the semantic web: How well can it capture biology

Could the Semantic Web work for computations of biological interest in the way it’s intended to work for movie reviews and commercial transactions? It would be wonderful if it could, so it’s worth looking to see if its infrastructure is adequate to the job. The technologies of the Semantic Web make several crucial assumptions. I examine those assumptions; argue that they create significant problems; and suggest some alternative ways of achieving the Semantic Web’s goals for biology. 1