Computational Biology & Bioinformatics-Department of Biological Sciences - Carnegie Mellon University

Computational Biology & Bioinformatics

Ziv Bar-Joseph

Affiliated Biological Sciences Faculty

Dr. Bar-Joseph's primary research is in computational and systems biology. Machine learning and statistical algorithms are used to study time series expression experiments and to combine high throughput biological data sources to model biological networks.
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Dannie Durand

Associate Professor

The Durand group works in comparative genomics, focusing on the evolution of genome organization and functional diversity.
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N. Luisa Hiller

Assistant Professor

The Hiller group applies comparative genomics to study the genomic diversity and plasticity of strains within a single species.
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Veronica F. Hinman

Associate Professor

The Hinman laboratory studies evolution of developmental mechanisms using marine invertebrate embryo and larval models. Of particular interest are gene regulatory networks (GRNs), which are researched to discover essential features of animal development and gain a better understanding of how evolutionary changes are incorporated into developmental programs.
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Sandra J. Kuhlman

Assistant Professor

There is a division of labor among cell types within cortical brain circuits. The Kuhlman laboratory employs computational approaches to better understand how cell-type diversity contributes to sensory encoding and learning.
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Christopher J. Langmead

Affiliated Biological Sciences Faculty

The Langmead laboratory's interests encompass the areas of structural and temporal phenomena in biological systems. Projects range from new techniques for problems in structural biology to modeling of the 3D growth of brain tumors.
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C. Joel McManus

Assistant Professor

The McManus lab studies the evolution of gene expression networks using high-throughput sequencing and comparative genomics approaches. We are particularly interested in how multi-layered expression networks change and in investigating the evolution of cross-talk between gene regulatory processes.
Faculty Webpage, Laboratory Website

Jonathan S. Minden

Professor

A major objective in the Minden laboratory is developing new tools for comparative proteomics. An important aspect of this proteomics work is to develop automated image analysis software to detect and rank protein changes during development and disease.
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Robert F. Murphy

Professor

Computational cell biology projects in the Murphy laboratory include using computational approaches to analyze the patterns of proteins in fluorescence microscope images to create self-populating knowledge bases and models of protein subcellular location.
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Gordon S. Rule

Professor

Computational interests in the Rule laboratory include developing methods for the rapid assignment of NMR spectral peaks and, in collaboration with Dr. Michael Erdmann of the Computer Science Department, developing geometric methods to detect structural homologies in proteins from NMR data.
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Russell S. Schwartz

Professor

The Schwartz lab works on many topics in modeling, simulation, and optimization in biology. One major focus is the development and use of stochastic simulations to study macromolecular assembly systems. Another focus is phylogenetics, with specific interests in the analysis of intraspecies genetic variation data and the evolution of tumor cells in cancers.
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Nathan N. Urban

Dr. Frederick A. Schwertz Distinguished Professor of Life Sciences

Currently, work in the Urban lab focuses on understanding the physiological mechanisms underlying the functional and computational properties of brain neuronal networks, focusing on the olfactory system.  In particular, we are interested in measuring the detailed anatomical and physiological properties of cells and synapses and then constructing models that provide insight into how these physiological properties give rise to circuits that transform and store information in the brain.
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Eric Xing

Affiliated Biological Sciences Faculty

Eric Xing develops statistical models and machine learning algorithms for biological network inference and characterization, cis-regulatory module decoding, regulatory evolution modeling, quantitative trait locus mapping, genome polymorphism patterning, and population genetic analysis. He is also applying these quantitative approaches to investigate the mechanisms of breast cancer development and metazoan morphagenesis.
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