Charles Lawrence, Professor of Applied Mathematics

Chip's research continues to be focused on the application of Bayesian algorithms that he and his collaborators have developed, leading to biological insights on transcription regulation and identification of regulatory motifs in prokaryotic and eukaryotic sequences, comparative genomics, antisense oligonucleotide and siRNA design, the composition of nucleotide sequences, and detailed analyses of several protein families.

Nicola Neretti, Assistant Professor (Research), Department of Molecular Biology, Cell Biology, and Biochemistry, and Institute for Brain and Neural Systems

Dr. Neretti was formally trained in physics and has been working on interdisciplinary projects which involve signal/image processing, and modeling of biological systems. His current focus is the application of high throughput techniques such as gene expression microarrays to study changes in the transcriptional network caused by genetic and environmental interventions that extend life span in model organisms. His most recent work includes the development of computational methods to detect age-associated chromatin changes in ChIP-chip and ChIP-seq experiments.

William Thompson, Assistant Professor of Applied Mathematics (Research)

To turn the genetic blueprint into a functional organism, genes must be expressed in a specific temporal and spatial patterns. Finding the signals that control this expression and understanding their interactions is a key to learning the language of the genes. One of the first steps in this process is locating the regulatory elements directly encoded in DNA and RNA sequences. The focus of my research is to develop computational methods to locate these key regulatory elements.

Eric Ruggieri

Over time, glaciers on the Earth's have melted and reformed at fairly regular intervals.  However, the glacial record exhibits times of drastic change, both in the size and periodicity of glaciations.  My research has focused on applications of the Change Point algorithm to this glacial record.  Least squares and Bayesian models have been developed, as well as a efficient model selection algorithm to try and determine the exact nature of the glacial changes.  My other research interests include Genome Wide Association Studies in the context of Phasing Algorithms and measures of Linkage Disequilibrium, as well as applications of Information Theory and statistical modeling.

Jessica Nadel

Lauren Alpert

Daniel Klein

A sequence of DNA base pairs composes into regulatory regions, exons (made up of codons), and introns, with overlaid epigenetic features and population-level patterns. Computational biologists have developed a full toolbox--hierarchical models, Bayesian inference, grammars, alignment algorithms, dynamic programming, etc.--to study the multi-layered structure of DNA and other biopolymers. These methods often have terse, elegant mathematical definitions, but implementing them is slow and error-prone, hampering exploration. I am interested in building domain-specific languages (DSLs) that transform high-level specifications into efficient and correct programs. My current project is a DSL for using next-generation sequencing to study recurrent structural variation in chromosomes, which has been implicated in cancer.

Luan Lin

I graduated from the Department of Mathematics, USTC, and received a Master's degree in Mathematics at Georgia Tech. My main interests are focused in the areas of probability and statistics. It is very fascinating to me when probability and statistics are applied to the study of Biology and Geology.