Computational Biology

Inference and Modeling of Genetic Regulatory Networks
Using the HL60 multipotent promyelocytic leukemia cell line, experiments were performed that ultimately led to two different cell fate attractors by two treatments of varying dosage and duration of the differentiation agent all-trans-retinoic acid (ATRA). We monitored the gene expression changes in the two populations after their respective treatments over a period of five days and identified a set of genes that diverged in their expression, a subset of which promotes neutrophil differentiation while the other represses cell cycle progression.

Image Analysis
A number of systems analysis projects at ISB rely on fluorescence microscopy, which is the standard tool for detection and analysis of cellular phenomena. This technique, however, has a number of drawbacks such as the limited number of available fluorescent channels in microscopes, overlapping excitation and emission spectra of the stains, and phototoxicity. A method was developed and validated to automatically detect cell population outlines directly from bright field images.

Image analysis algorithms were developed and applied to >3,000 live-cell imaging experiments to investigate the mating pheromone response in Saccharomyces cerevisiae under combined genetic perturbations and changing environmental conditions. For this study, a high-throughput microfluidic imaging platform for single-cell studies of network response under hundreds of combined genetic perturbations and time-varying stimulant sequences was developed.

Computational biology tools and methods
A method of computing P-values based on tail approximation was developed. The tail of the distribution of permutation values is approximated by a generalized Pareto distribution. A good fit and thus accurate P-value estimates can be obtained with a drastically reduced number of permutations when compared with the standard empirical way of computing P-values.