Biomedical subjects

M Prüss

Publications and source records attributed to M Prüss.

4 recordsLinked to original sources

PubMed2001

The TRANSFAC system on gene expression regulation.

The TRANSFAC database on transcription factors and their DNA-binding sites and profiles (http://www.gene-regulation.de/) has been quantitatively extended and supplemented by a number of modules. These modules give information about pathologically relevant mutations in regulatory regions and transcription factor genes (PathoDB), scaffold/matrix attached regions (S/MARt DB), signal transduction (TRANSPATH) and gene expression sources (CYTOMER). Altogether, these distinct database modules constitute the TRANSFAC system. They are accompanied by a number of program routines for identifying potential transcription factor binding sites or for localizing individual components in the regulatory network of a cell.

Binding Sites↗

PubMed2000

TRANSFAC: an integrated system for gene expression regulation.

TRANSFAC is a database on transcription factors, their genomic binding sites and DNA-binding profiles (http://transfac.gbf.de/TRANSFAC/). Its content has been enhanced, in particular by information about training sequences used for the construction of nucleotide matrices as well as by data on plant sites and factors. Moreover, TRANSFAC has been extended by two new modules: PathoDB provides data on pathologically relevant mutations in regulatory regions and transcription factor genes, whereas S/MARt DB compiles features of scaffold/matrix attached regions (S/MARs) and the proteins binding to them. Additionally, the databases TRANSPATH, about signal transduction, and CYTOMER, about organs and cell types, have been extended and are increasingly integrated with the TRANSFAC data sources.

Database Management Systems↗

PubMed1999

Metabolic drug pointing and information processing.

Computer supported drug design is based on the biochemical information for the prediction of alternative bio-chemical pathways. Molecular information on genes, proteins, biochemical reactions, mutations, inborn errors and metabolic diseases are available via internet. Based on this information we developed an information retrieval and processing concept combining knowledge about metabolic diseases and biochemical effects.

Artificial Intelligence↗

PubMed1997

Genetic studies in Medzev, an isolate in south-eastern Slovakia. 2. Distribution of blood group genetic markers.

Phenotype and gene frequencies of three blood group, four serum protein and seven red cell enzyme polymorphisms were examined in 105 individuals from the population of Medzev, South-Eastern Slovakia. Locus and allele specific tests of homogeneity were calculated in order to obtain the pattern of variation. The results indicate considerable genetic differences between this population and another local population of this region (Chmelnica) as well as between the Medzev population and the total population of Slovakia. The possible reasons of the genetic heterogeneity within Slovakia are discussed.

Analysis of Variance↗