Characteristic enrichment of DNA repeats in different genomes

Using computer programs developed for this purpose, we searched for various repeated sequences including inverted, direct tandem, and homopurine–homopyrimidine mirror repeats in various prokaryotes, eukaryotes, and an archaebacterium. Comparison of observed frequencies with expectations revealed that in bacterial genomes and organelles the frequency of different repeats is either random or enriched for inverted and/or direct tandem repeats. By contrast, in all eukaryotic genomes studied, we observed an overrepresentation of all repeats, especially homopurine–homopyrimidine mirror repeats. Analysis of the genomic distribution of all abundant repeats showed that they are virtually excluded from coding sequences. Unexpectedly, the frequencies of abundant repeats normalized for their expectations were almost perfect exponential functions of their size, and for a given repeat this function was indistinguishable between different genomes.

A high-resolution annotated physical map of the human chromosome 13q12-13 region containing the breast cancer susceptibility locus BRCA2.

Various types of physical mapping data were assembled by developing a set of computer programs (Integrated Mapping Package) to derive a detailed, annotated map of a 4-Mb region of human chromosome 13 that includes the BRCA2 locus. The final assembly consists of a yeast artificial chromosome (YAC) contig with 42 members spanning the 13q12-13 region and aligned contigs of 399 cosmids established by cross-hybridization between the cosmids, which were selected from a chromosome 13-specific cosmid library using inter-Alu PCR probes from the YACs. The end sequences of 60 cosmids spaced nearly evenly across the map were used to generate sequence-tagged sites (STSs), which were mapped to the YACs by PCR. A contig framework was generated by STS content mapping, and the map was assembled on this scaffold. Additional annotation was provided by 72 expressed sequences and 10 genetic markers that were positioned on the map by hybridization to cosmids.

Quantitative modeling of stochastic systems in molecular biology by using stochastic Petri nets

An integrated understanding of molecular and developmental biology must consider the large number of molecular species involved and the low concentrations of many species in vivo. Quantitative stochastic models of molecular interaction networks can be expressed as stochastic Petri nets (SPNs), a mathematical formalism developed in computer science. Existing software can be used to define molecular interaction networks as SPNs and solve such models for the probability distributions of molecular species. This approach allows biologists to focus on the content of models and their interpretation, rather than their implementation. The standardized format of SPNs also facilitates the replication, extension, and transfer of models between researchers. A simple chemical system is presented to demonstrate the link between stochastic models of molecular interactions and SPNs. The approach is illustrated with examples of models of genetic and biochemical phenomena where the UltraSAN package is used to present results from numerical analysis and the outcome of simulations.