This list has every graduate level ‘omics class WSU offers. If you would like to add to this list please email res.dev@wsu.edu.
- Biology:
- BIOLOGY 519 Introduction to Population Genetics Survey of basic population and quantitative
genetics - BIOLOGY 521 Quantitative Genetics Fundamentals of quantitative genetics; evolutionary quantitative
genetics - BIOLOGY 534 Modern Methods in Population Genomics Problems and prospects of designing a
study with genomic data: from raw data to demography and selection inferences. - BIOLOGY 566 Mathematical Genetics See MATH 563.
- BIOLOGY 519 Introduction to Population Genetics Survey of basic population and quantitative
- Computer science:
- CPT S 570 Machine Learning Introduction to building computer systems that learn from their experience;
classification and regression problems; unsupervised and reinforcement learning. - CPT S 571 Computational Genomics Fundamental algorithms, techniques and applications.
- CPT S 572 Numerical Methods in Computational Biology Prereq cell biology, probability and
statistics, graduate standing in computer science, or permission of the instructor. Computational methods
for solving scientific problems related to information processing in biological systems at the molecular and
cellular levels.
- CPT S 570 Machine Learning Introduction to building computer systems that learn from their experience;
- Crop and Soil Sciences:
- CROP SCI 545 Statistical Genomics Concepts and applications in modern breeding programs.
- CROP SCI 555 Epigenetics in Plants Understanding principles of epigenetics in plants with a focus on
its role in understanding and improving plant genomes and their adaptation to the changing environment.
Recommended preparation: General genetics.
- Horticulture:
- HORT 503 Advanced Topics in Horticulture
- Mathematics
- MATH 563 Mathematical Genetics Mathematical approaches to population genetics and genome
analysis; theories and statistical analyses of genetic parameters. (Crosslisted course offered as MATH
563, BIOLOGY 566).
- MATH 563 Mathematical Genetics Mathematical approaches to population genetics and genome
- Molecular Biosciences:
- MBIOS 503 Advanced Molecular Biology I DNA replication and recombination in prokaryotes and
eukaryotes; recombinant DNA methods and host/vector systems; genome analysis; transgenic
organisms. Recommended preparation: Introductory genetics and biochemistry coursework. - MBIOS 578 Bioinformatics Computer analysis of protein and nucleic acid sequences, functional
genomics and proteomics data; modeling biological networks and pathways. Recommended preparation:
Introductory genetics or biochemistry coursework.
- MBIOS 503 Advanced Molecular Biology I DNA replication and recombination in prokaryotes and
- Statistics:
- STAT 523 Statistical Methods for Engineers and Scientists Hypothesis testing; linear, multilinear, and
nonlinear regression; analysis of variance for designed experiments; quality control; statistical computing. - STAT 530 Applied Linear Models The design and analysis of experiments by linear models.
- MATH/STAT 536 Statistical Computing Generation of random variables, Monte Carlo simulation,
bootstrap and jackknife methods, EM algorithm, Markov chain Monte Carlo methods. - STAT 565 Analyzing Microarray and Other Genomic Data Statistical issues from pre-processing
(transforming, normalizing) and analyzing genomic data (differential expression, pattern discovery and
predictions).
- STAT 523 Statistical Methods for Engineers and Scientists Hypothesis testing; linear, multilinear, and