The Biocomputing Research Lab

Image: Figures pertaining to research

Computational Drug Discovery against Schistosomiasis


Schistosomiasis or bilharzia is a disease that afflicts more than 200 million people around the world with 20 million suffering severe effects and places over 600 million people at risk. Schistosomiasis ranks second only behind malaria, in terms of socio-economic and public health impact in developing countries. This disease is caused by parasitic worms of the genus Schistosoma which live in fresh water snails. The larval forms of the parasites have the ability to penetrate the skin and thus infect people who come into contact with contaminated water. The disease has been classified as one of the seventeen neglected tropical diseases by the Centers for Disease Control and Prevention and the World Health Organization. As such, it causes great misery both through physical suffering and by depriving people of their health and economic potential. The objective of our research is to use Computer Science in novel ways to develop a quantitative and mechanistic understanding of schistosomiasis and accelerate the development of therapeutics against this disease.

Our research foci include: (1) image and video-based phenotype analysis and identification, (2) development of computational phenomics-based high-throughput drug screening methods (3) designing algorithms for structure-activity modeling, given the phenomic responses of the parasite to putative drugs, (4) designing novel algorithms and user-data interaction paradigms for mining phenotype-phenotype and phenotype-structure relationships.


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Dose-Response Characterization in Phenotypic Assays

Research into methods for automatic determination dose-response (or time-response) characteristics in phenotypic screens, including EC50 values.

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Clustering and indexing of phenotypic time-series data

Development of clustering and indexing methods suited for phenotypic time-series data.

See also

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