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Joe Mellor

Publications and source records attributed to Joe Mellor.

3 recordsLinked to original sources

An equilibrium partitioning model connecting gene expression and cis-motif content.

Thermodynamic favorability of transcription factor (TF) binding to DNA is a significant factor in the control of gene expression. Theoretical and in vitro measures link the relative equilibrium energy of a particular DNA binding protein to the sequence variation among binding sites in a genome. Extending this principle, we investigate whether biological variation in expression levels of active proteins leads to regulation of different sets of genes, based on inferred affinities of sites upstream of those genes. The TF-concentration-dependent variation in the repertoire of genes regulated by a particular TF is expected to follow patterns of chemical partitioning over DNA sites having differing affinity, and we develop a new modeling approach to test this hypothesis. Based on computational TF binding site discovery and genome-wide expression data available in Saccharomyces cerevisiae, we explore motif content for sets of genes and conditions having varying concentrations of different transcription factors which turn those genes on or off. We find cases of significant correlation between the level of intragenomic motif sequence variation and modeled TF protein levels that actuates regulation of corresponding sets of genes, and discuss the observed TF motif variants for several yeast transcription factors, as well as the potential biological functions of genes that are regulated by differential response to these high and low concentrations of particular TFs. These findings suggest that motif sequences of transcription factor binding sites may often be linked with the expression state of corresponding DNA-binding proteins.

Amino Acid Motifs↗

The interaction map of yeast: terra incognita?

A systematic curation of the literature on Saccharomyces cerevisiae has yielded a comprehensive collection of experimentally observed interactions. This new resource augments current views of the topological structure of yeast's physical and genetic networks, but also reveals that existing studies cover only a fraction of the cell.

Computational Biology↗

VisANT: data-integrating visual framework for biological networks and modules.

VisANT is a web-based software framework for visualizing and analyzing many types of networks of biological interactions and associations. Networks are a useful computational tool for representing many types of biological data, such as biomolecular interactions, cellular pathways and functional modules. Given user-defined sets of interactions or groupings between genes or proteins, VisANT provides: (i) a visual interface for combining and annotating network data, (ii) supporting function and annotation data for different genomes from the Gene Ontology and KEGG databases and (iii) the statistical and analytical tools needed for extracting topological properties of the user-defined networks. Users can customize, modify, save and share network views with other users, and import basic network data representations from their own data sources, and from standard exchange formats such as PSI-MI and BioPAX. The software framework we employ also supports the development of more sophisticated visualization and analysis functions through its open API for Java-based plug-ins. VisANT is distributed freely via the web at http://visant.bu.edu and can also be downloaded for individual use.

Computer Graphics↗