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Search: authors:"Charlotte Konikoff"

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myFX: a turn-key software for laboratory desktops to analyze spatial patterns of gene expression in Drosophila embryos

Summary: Spatial patterns of gene expression are of key importance in understanding developmental networks. Using in situ hybridization, many laboratories are generating images to describe these spatial patterns and to test biological hypotheses. To facilitate such analyses, we have developed biologist-centric software (myFX) that contains computational methods to automatically...

A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis

Chrisochoides 0 Christopher Osgood Charlotte Konikoff Stuart Newfeld Sudhir Kumar Shuiwang Ji 0 0 Department of Computer Science, Old Dominion University , Norfolk, VA 23529 , USA Background: Multicellular

Relationship between gene co-expression and sharing of transcription factor binding sites in Drosophila melanogaster

Motivation: In functional genomics, it is frequently useful to correlate expression levels of genes to identify transcription factor binding sites (TFBS) via the presence of common sequence motifs. The underlying assumption is that co-expressed genes are more likely to contain shared TFBS and, thus, TFBS can be identified computationally. Indeed, gene pairs with a very high...

FlyExpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis

Summary: Images containing spatial expression patterns illuminate the roles of different genes during embryogenesis. In order to generate initial clues to regulatory interactions, biologists frequently need to know the set of genes expressed at the same time at specific locations in a developing embryo, as well as related research publications. However, text-based mining of image...