A computer system to perform structure comparison using TOPS representations of protein structure

We describe the design and implementation of a fast topology–based method for protein structure comparison. The approach uses the TOPS topological representation of protein structure, aligning two structures using a common discovered pattern and generating measure of distance derived from an insert score. Heavy use is made of a constraint-based pattern matching algorithm for TOPS diagrams that we have designed and described elsewhere Gilbert et al. (1999). The comparison system is maintained at the European Bioinformatics Institute and is available over the Web via the at tops.ebi.ac.uk/tops. Users submit a structure description in Protein Data Bank (PDB) format and can compare it with structures in the entire PDB or a representative subset of protein domains, receiving the results by email

TinkerCell: Modular CAD Tool for Synthetic Biology

Synthetic biology brings together concepts and techniques from engineering and biology. In this field, computer-aided design (CAD) is necessary in order to bridge the gap between computational modeling and biological data. An application named TinkerCell has been created in order to serve as a CAD tool for synthetic biology. TinkerCell is a visual modeling tool that supports a hierarchy of biological parts. Each part in this hierarchy consists of a set of attributes that define the part, such as sequence or rate constants. Models that are constructed using these parts can be analyzed using various C and Python programs that are hosted by TinkerCell via an extensive C and Python API. TinkerCell supports the notion of a module, which are networks with interfaces. Such modules can be connected to each other, forming larger modular networks. Because TinkerCell associates parameters and equations in a model with their respective part, parts can be loaded from databases along with their parameters and rate equations. The modular network design can be used to exchange modules as well as test the concept of modularity in biological systems. The flexible modeling framework along with the C and Python API allows TinkerCell to serve as a host to numerous third-party algorithms. TinkerCell is a free and open-source project under the Berkeley Software Distribution license. Downloads, documentation, and tutorials are available at www.tinkercell.com.Comment: 23 pages, 20 figure

Development of novel software tools and methods for investigating the significance of overlapping transcription factor genomic interactions

Identifying overlapping DNA binding patterns of different transcription factors is a major objective of genomic studies, but existing methods to archive large numbers of datasets in a personalised database lack sophistication and utility. To address this need, various database systems were benchmarked and a tool BiSA (Binding Sites Analyser) was developed for archiving of genomic regions and easy identification of overlap with or proximity to other regions of interest. BiSA can also calculate statistical significance of overlapping regions and can also identify genes located near binding regions of interest or genomic features near a gene or locus of interest. BiSA was populated with >1000 datasets from previously published genomic studies describing transcription factor binding sites and histone modifications. Using BiSA, the relationships between binding sites for a range of transcription factors were analysed and a number of statistically significant relationships were identified. This included an extensive comparison of estrogen receptor alpha (ERα) and progesterone receptor (PR) in breast cancer cells, which revealed a statistically significant functional relationship at a subset of sites. In summary, the BiSA comprehensive knowledge base contains publicly available datasets describing transcription factor binding sites and epigenetic modification and provides an easy graphical interface to biologists for advanced analysis of genomic interactions

FONZIE: An optimized pipeline for minisatellite marker discovery and primer design from large sequence data sets

<p>Abstract</p> <p>Background</p> <p>Micro-and minisatellites are among the most powerful genetic markers known to date. They have been used as tools for a large number of applications ranging from gene mapping to phylogenetic studies and isolate typing. However, identifying micro-and minisatellite markers on large sequence data sets is often a laborious process.</p> <p>Results</p> <p>FONZIE was designed to successively 1) perform a search for markers via the external software Tandem Repeat Finder, 2) exclude user-defined specific genomic regions, 3) screen for the size and the percent matches of each relevant marker found by Tandem Repeat Finder, 4) evaluate marker specificity (i.e., occurrence of the marker as a single copy in the genome) using BLAST2.0, 5) design minisatellite primer pairs via the external software Primer3, and 6) check the specificity of each final PCR product by BLAST. A final file returns to users all the results required to amplify markers. A biological validation of the approach was performed using the whole genome sequence of the phytopathogenic fungus <it>Leptosphaeria maculans</it>, showing that more than 90% of the minisatellite primer pairs generated by the pipeline amplified a PCR product, 44.8% of which showed agarose-gel resolvable polymorphism between isolates. Segregation analyses confirmed that the polymorphic minisatellites corresponded to single-locus markers.</p> <p>Conclusion</p> <p>FONZIE is a stand-alone and user-friendly application developed to minimize tedious manual operations, reduce errors, and speed up the search for efficient minisatellite and microsatellite markers departing from whole-genome sequence data. This pipeline facilitates the integration of data and provides a set of specific primer sequences for PCR amplification of single-locus markers. FONZIE is freely downloadable at: <url>http://www.versailles-grignon.inra.fr/bioger/equipes/leptosphaeria_maculans/outils_d_analyses/fonzie</url></p