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Bioinformatics and Computational Biology

M.S. Bioinformatics and Computational Biology, Ph.D. Bioinformatics and Computational Biology

» Bioinformatics & Computational Biology Program     » College of College of Graduate Studies


  • INTRODUCTION
  • WHAT IT TAKES
  • WHAT PEOPLE DO
  • GET INVOLVED
  • FACULTY
Bioinformatics student in the lab

Major technological advancements in molecular and genetic research have resulted in an explosion of new biological information. With a master's or doctorate degree in bioinformatics and computational biology, you will have the specialized expertise and technical skills to decipher this complex data. You may also have opportunities to research and discover new applications that could potentially improve human health and agriculture.


Specialize in one of the following areas:

  • Biology: Focus on the study and research of biological systems and the understanding of the molecular and genetic data.
  • Mathematics: Explore the methods and models used in genetic and molecular biological research.
  • Computer Science: Concentrate on the skills and techniques to develop and use databases and other data management systems.


Drawing on expertise and resources from nine university departments, this progressive graduate degree merges study and research in biology, mathematics, computer science and statistics.  You'll develop the interdisciplinary knowledge and specialized tools to manage, process and analyze complex biological data.

Depending on your area of specialization, you may study and conduct research in:

  • Molecular biology
  • Evolution
  • Statistical genetics
  • Database management systems
  • Probability theory
  • Mathematical methods and models
  • Biochemistry
  • Ecology


As a student in the bioinformatics and computational biology program, you will have the opportunity to engage in exciting collaborative research projects through the Initiative for Bioinformatics and Evolutionary Studies (IBEST), a group of faculty and students from several disciplines investigating evolutionary phenomena and the bioinformatics tools to explain them.


Bioinformatics students

Prepare for Success

Acceptance into the Bioinformatics and Computational Biology Program is extremely competitive. If you’re interested in a degree in these newly emerging disciplines, you should build a strong background with experience in at least two of the three areas of biological, mathematical or computer sciences. You should also have an undergraduate degree related to at least one of these areas of study.


Your First Year

During your first years in the 32-credit master’s degree program (78 credits for a Ph.D.), you will form an interdisciplinary foundation by completing the following core courses:
Computational Biology I: Sequences
Principles of Systematic Biology
Mathematical Methods in Genetics

You may be required to take courses that provide the program's general background requirements in biology, mathematics and/or computer science. Depending on your undergraduate degree and experience, you may complete courses in:

  • High level programming
  • Data structures
  • General biology
  • Basic genetics
  • Calculus
  • Basic probability and statistics

Program Requirements


What You Can Do

Depending on your area of specialization, you may become a:

  • Bioinformatician
  • Biomedical computer scientist
  • Geneticist
  • Computational biologist
  • Biostatistician
  • Biomedical chemist
  • Clinical data manager
  • Molecular microbiologist
  • Software/database programmer
  • Medical writer/technical writer
  • Research associate and research scientist
  • Academic professor/researcher


Opportunities

Graduates of the University of Idaho Bioinformatics and Computational Biology Program are at the forefront of a newly emerging science. This ever-evolving field offers many diverse career paths, depending on your specialization and interests.

You'll be in high demand in health care, agriculture, pharmaceutical products, forestry, academia and other industries and governmental agencies that rely on the high-level ability to manage and analyze complex biological information. You could find yourself on the leading edge of human medical discovery, with opportunities to use your expertise to prevent diseases and create new treatments to improve human health.


Current Research

The Bioinformatics and Computational Biology Program has attracted more than $10 million in grants from a variety of sources for interdisciplinary research. Current faculty research interests include:

  • Experimental, theoretical, and natural evolution of viruses
  • Bacteriophage and plasmids
  • Protein flexibility
  • Evolution of retrotransposons
  • Coevolutionary genetics and plant polyploidy
  • Conservation genetics
  • Medical ecology
  • Computational methods for processing biological data
  • Phylogenetics and systematics
  • Statistical models for biological processes


Collaborative research projects as part of the Initiative for Bioinformatics and Evolutionary Studies (IBEST) include:

  • Spatial Dynamics of Plasmid-Bacteria Interactions
  • Microbial Community Analysis
  • Evolving Ecological Networks
  • Decision Theoretic Approach to Model Selection


Hands-On Experience

Collaborate with peers and nationally recognized experts on exciting research in biological, computer and mathematical sciences. Conduct laboratory experiments with one-on-one mentorship from faculty researchers in a variety of disciplines.

Thesis: Both the M.S. and Ph.D. degrees require a thesis. The M.S. degree requires at least nine credits of thesis research and the Ph.D. degree requires at least 30. Each student has a graduate committee of at least four faculty members representing the three BCB disciplines (biology, computer science and mathematical sciences). Past theses titles include:

  • Function Choice, Resiliency, and Code Growth in Genetic Programming
  • Using Classic Optimization to Speed up Burn in and Mixing in Markov Chain Monte Carlo Methods for Phylogenetic Inference
  • Computational Modeling of Cancer Etiology and Progression Using Neural Networks and Genetic Cellular Automata
  • Bacterial Diversity and Competition from the Population to the Community Level
  • On the use of Stochastic Population Dynamics Models in Microbial Ecology
  • Natural Diversity and Experimental Adaptive Evolution of Bacteriophages of the Family Microviridae


Fellowships and Assistantships:
You are encouraged to apply for a research assistantship and other funding opportunities for student research.


Facilities



Paul Joyce
Paul Joyce, Ph.D.
Professor|Director of BCB
My research focuses on developing and rigorously testing statistical methods and stochastic models to describe genetic phenomena. These include models and methods to: predict how viruses adapt; show the effect of antibiotic resistance genes encoded on plasmids; predict ancestral relationships among species; and to understand the ecological structure of bacterial communities in biofilms. This broad focus has lead to collaborations with researchers in phylogenetics, population genetics, theoretical ecology, mircobial ecology, experimental evolution, conservation genetics, and the list is growing.
» View Paul Joyce's profile.
Zaid Abdo
Zaid Abdo, Ph.D.
Associate Professor
Here are the areas I am interested in, listed in order of interest: Bioinformatics, Statistical Genetics, Bayesian Statistics, Mathematical Biology, Stochastic Processes & Optimization
» View Zaid Abdo's profile.
Celeste Brown
Celeste Brown, Ph.D.
Research Professor
Dr. Celeste Brown has two research areas, how gene regulation changes in response to selection, and the evolution of disordered proteins. The link between these two disparate areas is that often proteins involved in gene regulation are disordered. The gene regulation studies involve laboratory-based research and the disordered protein studies involve bioinformatics approaches.
» View Celeste Brown's Profile
Brian Dennis
Brian Dennis
Professor
Research interests: Statistical Ecology, Biometrics, Mathematical Modeling, Theoretical Ecology, Conservation Biology, Population Dynamics
» View Brian Dennis' profile
Larry Forney
Larry J. Forney, Ph.D.
Professor
Director of IBEST
The research done in Dr. Larry Forney’s laboratory centers on the diversity and distribution of prokaryotes. Both field and laboratory studies are done to explore the temporal and spatial patterns of community diversity, as well as factors that influence the dynamics of inter- and intra-species competition. In addition research is done to understand how spatial structure and the resulting environmental gradients influence the tempo and trajectory of adaptive radiations in bacterial species and the maintenance of diversity. Most of these studies are highly interdisciplinary in nature, and done in collaboration with mathematicians, statisticians, computer scientists, geologists, environmental engineers, physicians, and clinical scientists.
» View Larry Forney's profile
Dr. James Foster
James A. Foster, Ph.D.
Professor
Dr. Foster’s current research is focused on characterizing evolutionarily permissible ecological structures in microbial ecosystems and on developing bioinformatics for very large sequence datasets. He continues to examine simulations of evolutionary processes to design complex artifacts and optimize functions. He works in close collaboration with biologists, statisticians, mathematicians, and computer scientists.
» View James Foster's profile
Gao
Frank Gao, Ph.D.
Associate Professor
Research Interests: Interface of Probability Theory, Functional Analysis and Convex Geometry, Small Deviations of Gaussian Processes, Metric entropy and Intrinsic Volumes of convex bodies
» View Frank Gao's profile.
Dr. Luke Harmon
Luke J. Harmon, Ph.D.
Assistant Professor
Our research investigates ecological and evolutionary aspects of adaptive radiations. Current projects span a wide range of taxa and time scales, including adaptive radiation in E. coli biofilms, evolution of island lizards in the Caribbean and Indian Ocean, and macroevolutionary dynamics of vertebrates. You will find more information about all of these projects on the research and publications pages.
» View Luke Harmon's Profile
Robert Heckendorn
Robert Heckendorn, Ph.D.
Associate Professor
Robert works with anything that evolves. His research has included bioinformatics work in phylogenetics, new methods of Markov Chain Monte Carlo sampling, and the simulation of the geneics of the onset of breast cancer. He is currently working on evolutionary approaches to agent based simulations of international conflict and the cooperative behavior of swarms of thousands of robots.
» View Robert Heckendorn's profile.
Paul Hohenlohe
Paul Hohenlohe, Ph.D.
Assistant Professor
Our research focuses on the genomic architecture of evolving populations, developing sophisticated theory and analytical tools to harness the power of modern DNA sequencing technology. We address basic questions of evolutionary biology as well as applications to conservation and cancer biology.
» View Paul Hohenlohe's profile
Alexander Karasev
Alexander Karasev
Associate Professor, Plant Virology

(208) 885-2350 | akarasev@uidaho.edu
» View profile
Steve Krone
Steve Krone, Ph.D.
Professor
Research interests: Stochastic Processes and Mathematical Biology; especially interacting particle systems, population genetics and evolutionary biology, coalescent theory, spatial models in (microbial) ecology and epidemiology, combining experimental and theoretical approaches, diffusion processes and differential equations.
» View Steve Krone's profile.
Stephen Sauchi Lee
Stephen Sauchi Lee, Ph.D.
Associate Professor
My general research area is Multivariate and Computational Statistics. It includes: Integrating models and methods from statistics, neural networks, machine learning, and data mining communities to discover relationships and recognize patterns in databases; modeling using regression and classification for interpretation and forecasting; extracting information and patterns; and developing computational algorithms to increase efficiency and prediction accuracy.
» View Stephen Sauchi Lee's profile
McGuire M
Mark McGuire, Ph.D.
Professor

(208) 885-7683 | mmcguire@uidaho.edu
» View profile
Gordon Murdoch
Gordon Murdoch, Ph.D.
Assistant Professor

(208) 885-6347 | gmurdoch@uidaho.edu
» View profile
Dr. Scott Nuismer
Scott L. Nuismer, Ph.D.
Associate Professor
My research focuses on the ecology and evolution of species interactions. The overall aim is to better understand how coevolution shapes patterns of biodiversity and the geographic distributions of interacting species. Work in my lab addresses these issues with a combination of mathematical modeling and field studies.
» View Scott Nuismer's Profile
Professor Powell
Matt Powell, Ph.D.
Associate Professor

(208) 837-9096 | mpowell@uidaho.edu
» View profile
R. Robberecht
R. Robberecht
Professor
Specialty area of Interest: Physiological plant ecology (Ecophysiology); guided independent learning (use of information technology in science education); scientific visualization and modeling (integration of ecological processes, molecule to globe)
» View R. Robberecht's Site
Dr. Barrie Robison
Barrie Robison, Ph.D.
Associate Professor
My general research interests lie at the interface between genomics, evolutionary biology, and fisheries biology. Specific areas of research emphasis in my lab include the genetic architecture of complex traits, the evolution of locally adaptive phenotypes, and genomic analysis of behavioral variation in fish. I employ two study systems to investigate these issues, the rainbow trout and the zebrafish.
View Barrie's profile
» brobison@uidaho.edu
Terry Soule
Terry Soule, Ph.D.
Professor|Director of Neuroscience
Research Areas: Evolutionary computation, biological modeling
» View Terry Soule's profile
Dr. Deborah Stenkamp
Deborah Stenkamp, Ph.D.
Professor
Stenkamp’s research interests center on the examination of cellular and molecular mechanisms of vertebrate retinal development and regeneration, with a specific focus on photoreceptor differentiation, using zebrafish as the primary experimental model.
» View Deborah Stenkamp's profile
Dr. Jack Sullivan
John "Jack" M. Sullivan, Ph.D.
Professor
Our understanding of the processes of nucleotide substitution (DNA sequence evolution) has been expanding greatly over the last 10 years. Furthermore, it has become apparent that ignoring such processes as heterogeneity of base composition, substitution pattern, and rate variation among nucleotide sites can compromise attempts to estimate phylogeny from DNA sequence data. Therefore, model-based analyses of DNA sequence data have become increasingly wide spread because such approaches afford the investigator the opportunity to account for such processes explicitly.
» View Jack Sullivan's Profile
David Tank
David C. Tank
Assistant Professor & Director, Stillinger Herbarium
I am a plant systematist and am broadly interested in the investigation of the patterns and processes that shape plant biodiversity. In general, my research is focused on the use of molecular methods to reconstruct phylogenetic relationships in plants and the application of phylogenetic methods to understand plant evolution. The evolutionary causes and consequences of processes such as hybridization, polyploidy, pollination biology, biogeography, rapid diversification, and niche evolution can only be understood in light of a robust phylogenetic hypothesis, and these hypotheses are a necessary component of modern taxonomic treatments and classification systems. Research in my lab is directed at multiple levels of plant phylogeny and current projects range from comparative phylogeography of the Pacific Northwest inland rainforest communities, to the study of species boundaries and diversification among very closely related species, to patterns of diversification among some of the major lineages comprising the plant tree of life.
» View David Tank's faculty profile
Eva Top
Eva Top, Ph.D.
Professor
Eva Top is a microbial ecologist whose interests can be roughly divided into two major areas. The main research interest is the role of horizontal gene transfer in the adaptation of bacterial populations and communities to changing environmental conditions, and in bacterial evolution in general. The second area of interest is the diversity, structure and dynamics of bacterial communities in natural or bioreactor environments, such as soil, sediments, wastewater treatment reactors, and gastrointestinal ecosystems, and how these communities respond to various disturbances.
View Eva's profile
» evatop@uidaho.edu
Lisette Waits
Lisette Waits
Professor; Affiliate faculty member CATIE Costa Rica
Research interests: Conservation Genetics, Landscape Genetics, Molecular Ecology, Molecular Systematics
» View Lisette Waits' profile
Holly Whichman
Holly A. Wichman, Ph.D.
Professor
The Wichman Lab studies viruses and their subcellular relatives, transposable elements. These two lines of research are united by a molecular approach and a strong evolutionary context. L1 elements have been active in mammals for over 150 million years and make up about 20% of the genome. Most of the copies in the genome are ancient molecular fossils, so it is a challenge to sift through all of the old copies to find those that have been recently active.
View Holly's profile
» hwichman@uidaho.edu
Michelle Wiest
Michelle Wiest, Ph.D.
Assistant Professor
» View Michelle Wiest's profile
Christopher Williams
Christopher Williams, Ph.D.
Professor and Chair
Affiliate Professor of Bioinformatics and Computational Biology
My research interests are on problems in statistical genetics, biostatistics, and statistical methods applied to issues in natural resources. One of the topics that I work on is the analysis of human twin data. Another area of interest is the estimation of disease prevalence from various types of data, such as in groups of fish that are collected and have their tissue pooled to test for disease status.
» View Chris Williams' profile
Marty Ytreberg
F. Marty Ytreberg, Ph.D.
Assistant Professor
Developing computational methods for proteins and using these approaches to understand the underlying biophysical mechanisms that define protein structure, function and evolution.
» View Marty Ytreberg's profile