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Fran Lewitter

Publications and source records attributed to Fran Lewitter.

6 recordsLinked to original sources

Visualizing networks.

An interrelated set of genes or proteins can be represented effectively as a network that describes physical interactions, regulatory relationships, or metabolic pathways. Visualizing a network can be a helpful method to extract biological meaning and to generate testable hypotheses about large-scale biological data. This chapter describes some potential rationales for visualizing networks of microarray and other data types, which can be integrated and filtered to show potentially significant relationships. It also presents a practical introduction to Osprey and Cytoscape, two software platforms that are powerful tools for visualizing, integrating, and manipulating networks.

Animals↗

Genome-wide map of nucleosome acetylation and methylation in yeast.

Eukaryotic genomes are packaged into nucleosomes whose position and chemical modification state can profoundly influence regulation of gene expression. We profiled nucleosome modifications across the yeast genome using chromatin immunoprecipitation coupled with DNA microarrays to produce high-resolution genome-wide maps of histone acetylation and methylation. These maps take into account changes in nucleosome occupancy at actively transcribed genes and, in doing so, revise previous assessments of the modifications associated with gene expression. Both acetylation and methylation of histones are associated with transcriptional activity, but the former occurs predominantly at the beginning of genes, whereas the latter can occur throughout transcribed regions. Most notably, specific methylation events are associated with the beginning, middle, and end of actively transcribed genes. These maps provide the foundation for further understanding the roles of chromatin in gene expression and genome maintenance.

Acetylation↗

Intragenic tandem repeats generate functional variability.

Tandemly repeated DNA sequences are highly dynamic components of genomes. Most repeats are in intergenic regions, but some are in coding sequences or pseudogenes. In humans, expansion of intragenic triplet repeats is associated with various diseases, including Huntington chorea and fragile X syndrome. The persistence of intragenic repeats in genomes suggests that there is a compensating benefit. Here we show that in the genome of Saccharomyces cerevisiae, most genes containing intragenic repeats encode cell-wall proteins. The repeats trigger frequent recombination events in the gene or between the gene and a pseudogene, causing expansion and contraction in the gene size. This size variation creates quantitative alterations in phenotypes (e.g., adhesion, flocculation or biofilm formation). We propose that variation in intragenic repeat number provides the functional diversity of cell surface antigens that, in fungi and other pathogens, allows rapid adaptation to the environment and elusion of the host immune system.

Antigens, Surface↗

siRNA Selection Server: an automated siRNA oligonucleotide prediction server.

The Whitehead siRNA (short interfering RNA) Selection Web Server (http://jura.wi.mit.edu/bioc/siRNA) automates the design of short oligonucleotides that can specifically 'knock down' expression of target genes. These short sequences are about 21 nt in length, and when synthesized as double stranded RNA and introduced into cell culture, can reduce or eliminate the function of the target gene. Depending on the length of a gene, there are potentially numerous combinations of possible 21mers. Some experimental evidence has already shown that not all 21mers in a gene have the same effectiveness at silencing gene function. Our tool incorporates published design rules and presents the scientist with information about uniqueness of the 21mers within the genome, thermodynamic stability of the double stranded RNA duplex, GC content, presence of SNPs and other features that may contribute to the effectiveness of a siRNA.

Algorithms↗

PathBLAST: a tool for alignment of protein interaction networks.

PathBLAST is a network alignment and search tool for comparing protein interaction networks across species to identify protein pathways and complexes that have been conserved by evolution. The basic method searches for high-scoring alignments between pairs of protein interaction paths, for which proteins of the first path are paired with putative orthologs occurring in the same order in the second path. This technique discriminates between true- and false-positive interactions and allows for functional annotation of protein interaction pathways based on similarity to the network of another, well-characterized species. PathBLAST is now available at http://www.pathblast.org/ as a web-based query. In this implementation, the user specifies a short protein interaction path for query against a target protein-protein interaction network selected from a network database. PathBLAST returns a ranked list of matching paths from the target network along with a graphical view of these paths and the overlap among them. Target protein-protein interaction networks are currently available for Helicobacter pylori, Saccharomyces cerevisiae, Caenorhabditis elegans and Drosophila melanogaster. Just as BLAST enables rapid comparison of protein sequences between genomes, tools such as PathBLAST are enabling comparative genomics at the network level.

Animals↗