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Bioinformatics & Computational Biology

Fluorescent microscopy DIC images of the nematode Caenorhabditis elegans after long-term exposures to nanoparticles (Zhong Lab)

 

Bioinformatics is a broad field that includes many aspects of the juncture between biology and computer science. Bioinformatics at Rice involves applications such as the use of functional genomics to describe the dynamic aspects of genes within a related cluster or pathway,to design synthetic circuits, and to make computational predictions of genetic interactions based on databases of experimentally-derived interaction data. Computational methods are employed for identifying phylogenetic relationships, modeling signaling networks, and many aspects of data-mining.

Faculty links:

George N. Bennett:  Response of microbes to stress and use of metabolic engineering to generate strains with beneficial properties (lab home page).

Matthew Bennett:  Synthetic biology and the dynamics of gene regulation. The Bennett lab uses a hybrid computational and experimental approach to design, construct, and understand gene regulatory networks (lab home page).

Herbert Levine: Physics of nonequilibrium processes, especially in the emergence of spatial patterns in extended systems such as Dictyostelium chemotaxis, neuronal circuits, and phenotypic transitions in bacterial colonies.

Luay Nahkleh :  Focus on computational evolutionary biology, particularly "networks of evolution and evolution of networks," as well as other topics related to biological networks (lab home page).

John S. Olson:  Biochemical, biophysical, and physiological properties of myoglobins, hemoglobins, and red blood cells; genetic engineering of heme protein based blood substitutes; application of rapid kinetic techniques to biological problems (lab home page).

José Onuchic: Biophysical studies and modeling of protein folding and convergent kinetic pathways, the theory of chemical reactions in condensed matter with emphasis on biological electron transfer reactions, and stochastic effects in genetic networks.

Studies of ADK secondary structure elements from the Shamoo Lab

George N. Phillips, Jr.: Modern computers offer tremendous opportunities for the development of new algorithms and software in the study of biological questions. Members of the Phillips group actively test new ideas related to X-ray crystallography, simulation of the thermal stability and dynamics of molecules, and course-grained models of diffusion of substrates and enzymes in solution and on surfaces.

Nicholas H. Putnam: Computational comparative genomics, mechanisms and dynamics of genome evolution, studies of genome structure variation in a natural population.

Yousif Shamoo: The evolutionary and molecular basis for antibiotic resistance, directed evolution of protein structure-function, and the underlying biophysical and physiochemical principles of adaptation within bacterial populations (lab home page).

Jonathan Silberg: Investigation of the processes controlling molecular evolution, particularly the evolution of protein structure, function, and molecular recognition using biochemical, computational, and molecular biological methods (lab home page).

Jeffrey J. Tabor: Use of light and other forms of electromagnetic radiation to control the activities in proteins inside of cells in real time, constructing synthetic transcriptional and post-translational signaling circuits, programming cells to communicate using unnatural signals, and combining all of these technologies to program synthetic multicellular behaviors.

Yizhi Jane Tao:  Structure and function of RNA viruses; RNA virus genome replication and genome packaging; influenza A virus; dsRNA viruses; astroviruses (lab home page).

Peter Wolynes: Application of statistical energy landscapes to understand biomolecular regulatory networks, proteing folding kinetics, gene recognition and genetic network regulation. Development of bioinformatically based schemes for predicting structure from sequence using computer simulation.

Weiwei Zhong:  Using the nematode C. elegans as a model to decipher gene interaction networks regulating development and behavior (lab home page).

Predicting evolutionary outcomes using experimental evolution and biochemistry at the Shamoo Lab