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Associate Professor

Computer Science

Volen Center for Complex Systems 135

MS 018, Brandeis University

Waltham, MA 02453

Phone: 781-736-2729

Fax: 781-736-2741


Openings: Iam recruting PhD students to work with me on Big Data Analytics in interdisciplinary fields, such as, Bioinformatics, Glycomics (Glycan mass spec analysis), Biomedical Informatics, and so on. Candidates with strong mathematical background and programming skills are preferred.

Research Highlights:

Glycomics -- the new frontier: coming soon ...

High-Content Neuronal Analysis: Cell-based high-content screening is becoming a widely used high-throughput methodology in therapeutic drug discovery and functional genomics. One of the challenges in high-content screens is to reliably and automatically analyze a large quantity of high-content images. Images of neuronal cell cultures are particularly challenging to analyze because of their complex morphology. My group has developed a robust pipeline for quantifying and comparing the morphology of neuronal cell cultures (Wu et al 2010). Our analysis pipeline has been a key innovation for high-throughput neuronal screening and has been applied to several large-scale high-content screening projects (Sepp et al. 2008, Wu et al. 2010, Schoemans et al. 2010, Schulte et al. 2011). Our computational results have led to successful follow-up studies (Sepp et al 2008, Schulte et al 2010). We are also developing a novel computing paradigm that integrates unsupervised pattern mining techniques, visual data exploration interfaces and interactive image analysis techniques to facilitate the application of the HCS technology to biomedical research. A prototype, called imCellPhen -- interactive mining of cellular phenotypes, has been realized (details).

Computational Systems Biology: Animal organogenesis is a complicate process controlled by a network of intercellular signaling, intracellular signal transduction, and transcriptional regulation. The construction of quantitative models for this network can provide insights into the underlying biological mechanisms. We have developed a mathematical model to model the biological network that governs C. elegans vulval induction. The model was automatically learned from heterogeneous biological data and is capable of simulating vulval induction under various different genetic conditions. (details). In another ongoing project, we inferred a large-scale multi-cellular regulatory network that contains 2000+ cells and governs the development of Drosophila eye (details) from high-content images and other biological data. At the same time, we are generating a comprehensive signaling network in Drosophila by using tandem affinity purification/mass spectrometry protein-protein interaction mapping (details).

Recent publications: