Bioinformatics Program Area

The vast molecular biology information resulting from high throughput genomic, proteomic and other ‘omic’ projects challenges the understanding of the role of genes, proteins and other molecules and the use of this knowledge in applications related to health, well-being, agriculture, society, and environment. The field of bioinformatics encompasses a wide range of research efforts that aim at gaining insights into biological processes through the development and implementation of repositories and tools, and the computational and statistical analysis of biological information. Computational, informatics, statistical, and mathematical resources and technologies are integrated to organize, analyze, and visualize biological data at multiple levels of organization, from molecules and phenotypes to populations and ecosystems. The Bioinformatics Area of the Ph.D. in Informatics will foster the academic, research, and intellectual development of students on bioinformatics theory and applications important for our understanding biological patterns and processes in the living world, including human, model and agricultural species, and microbes of economic or medical importance. This Area incorporates coursework in multiple disciplines related to bioinformatics including ‘omic’ themes (i.e. genomics, proteomics, metabolomics, comparative omics), phylogenetics, molecular evolution, evolutionary genomics, statistical genetics, statistical genomics, systems and network biology, quantitative genetics, structural biology, biotext mining, and e-science.

Bioinformatics faculty

Area Leads: Gustavo Caetano-Anolles (Crop Sciences) and Sandra Rodriguez-Zas (Animal Sciences)

Faculty: If you would like to affiliate with I3 and appear on this list, please contact Karin Readel.

College of Agricultural, Consumer, and Environmental Sciences (ACES)
Animal Sciences Sandra Rodriguez-ZasAlfred RocaJuan Loor, Bryan White, Anna Kukekova
Crop Sciences Gustavo Caetano-AnollesDonald BullockSteven CloughLila VodkinStephen Long, Stephen Moose, Alexander Lipka, Maria B. Villamil
Food Science and Human Nutrition Yuan-Xiang PanMargarita Teran-Garcia
Natural Resources and Environmental Sciences Schuyler Korban
College of Engineering
Computer Science Dan RothJulia Hockenmaier, Jian Peng
Bioengineering  Paul Jensen
College of Liberal Arts & Sciences (LAS)
Plant Biology Surangi Punyasena, Amy Marshall-Colon
Molecular & Integrative Physiology Philip Best
Chemical & Biomolecular Engineering Nathan PriceHuimin Zhao
Geography and Geographic Information Science Mei-Po Kwan
Integrative Biology Alison Bell
Microbiology Gary Olsen
Cell and Developmental Biology Lisa Stubbs
Chemistry Martin Burke
Entomology Gene Robinson, Allison Hansen
Anthropology Charles Roseman
Psychology Jaime Derringer
Statistics Dave Zhao, Stéphane Guerrier, Naveen Narisetty
College of Medicine
Medical Information Science Bruce Schatz
College of Veterinary Medicine
Pathobiology Ron Weigel
School of Information Sciences
Library & Information Science Les Gasser

 

Recommended Bioinformatics Courses

Bioinformatics Application Courses

ANSC 542/CPSC 569/IB 506 Applied Bioinformatics
ANSC 545/CPSC 545/IB 507 Statistical Genomics
BIOE 598 Computational Cancer Biology
CHBE 571/MCB 571/STAT 530 Bioinformatics
CPSC 567 Bioinformatics & Systems Biology
CPSC 558 Quantitative Plant Breeding
CPSC 565 Perl & UNIX for Bioinformatics (2 credit course)
EPSY 589 Categorical Data in Ed/Psyc
LIS 590 BDI Biodiversity Informatics

Bioinformatics Foundation Courses

CS 511 Advanced Database Systems
CS 512 Data Mining Principles
CS 545 Systems Modeling & Simulation
CS 558 Topics in Numerical Analysis
CS 573 Topics in Algorithms
CS 578 Information Theory
CS 598 Advanced Bioinformatics
CPSC 541 Regression Analysis
CPSC 542 Applied Statistical Methods II
LIS 542 Data, Stat and Info
MATH 580/CS 571 Combinatorial Mathematics
STAT 510 Mathematical Statistics I
STAT 525 Computational Statistics
STAT 542 Statistical Learning
STAT 563 Information Theory
STAT 571 Multivariate Analysis
STAT 587 Hierarchical Linear Models
PSYC 594 Multivar Analysis in Psych and Ed
EPSY 582 Advanced Statistical Methods
EPSY 580 Statistical Inference in Educ
EPSY 587 Hierarchical Linear Models
EPSY 588 Covar Struct and Factor Models
LIS 590DC Foundations of Data Curation