CLS Relevant Courses

These include courses in areas of life science for which computation is a major tool and courses in computation and methodology that have "major" applicability to life sciences.

The Relevant Courses of the CLS track are listed below by department.

CLS specialization at MS level requires 1 relevant course and at PhD level requires 2 relevant courses.

• Agronomy Courses
• Animal Sciences Courses
• Biochemistry Courses
• Biology Courses
• Biomedical Engineering Courses
• Chemical Engineering Courses
• Chemistry Courses
• Computer Science Courses
• Electrical and Computer Engineering Courses
• Industrial Engineering Courses
• Health Sciences Courses
• Horticulture Courses
• Mathematics Courses
• Medicinal Chemistry and Molecular Pharmacology Courses
• Physics Courses
• Statistics Courses

Agronomy Courses

AGRY 530: Advanced Plant Genetics
AGRY 600: Genomics

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Animal Sciences Courses

ANSC 511/AGRY 511: Population Genetics

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Biochemistry Courses

BCHM 561: General Biochemistry I/ BCHM 562: General Biochemistry II
BCHM 60501: Macromolecules
BCHM 610: Regulation of Eukaryotic Gene Expression 

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Biology Courses

BIOL 517: Molecular Biology: Proteins
BIOL 541: Molecular Genetics of Bacteria
BIOL 55001: Eukaryotic Molecular Biology
BIOL 56310: Protein Bioinformatics
BIOL 580: Evolution
BIOL 595: Cell Biology of Plants
BIOL 595: CryoEM 3D Reconstruction
BIOL 595: Introduction to Bioinformatics
BIOL 595: Practical Biocomputing
BIOL 611: Crystallography of Macromolecules
BIOL 647: Structure-Function of Membrane Proteins

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Biomedical Engineering Courses

BME 595/ME 577: Kinematics and Dynamics of Human Motion

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Chemical Engineering Courses

CHE 525: Biochemical Engineering
CHE 633: Probabilistic Methods in Chemical Engineering

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Chemistry Courses

CHM 579: Molecular Modeling and Simuations (Computational Chemistry)
CHM 671: Quantum Chemistry I
CHM 673: Computational Quantum Chemistry
CHM 676: Molecular Spectoscopy

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Computer Sciences Courses

CS 501: Computing for Science and Engineering
CS 514/MA 514: Numerical Analysis
CS 515: Numerical Linear Algebra
CS 525: Parallel Computing
CS 530: Introduction to Scientific Visualization
CS 541: Database Systems
CS 573: Data Mining
CS 578: Statistical Machine Learning
CS 579: Bioinformatics Algorithms
CS 580: Algorithm Design, Analysis and Implementation
CS 615/MA 615: Numerical Methods For Partial Differential Equations I

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Electrical and Computer Engineering Courses

ECE 528/BME 528: Measurement And Stimulation Of The Nervous System
ECE 580: Optimization Methods for Systems and Control (equivalent to CS 520/ IE 538)
ECE 662: Pattern Recognition and Decision-Making Processes

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Health Sciences Courses

HSCI 525: Introduction to Statistical and Computational Approaches to Health Sciences

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Horticulture Courses

HORT 590: Introduction to Data Analysis for Biology

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Industrial Engineering Courses

IE 538: Nonlinear Optimization Algorithms And Models (equivalent to CS 520/ ECE 580)

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Mathematics Courses

MA 523: Introduction to Partial Differential Equations
MA 527: Advanced Mathematics For Engineers And Physicists I
MA 532/STAT 532: Elements of Stochastic Processes

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Medicinal Chemistry and Molecular Pharmacology Courses

MCMP 570: Basic Principles of Chemical Action on Biological Systems
MCMP 690: Computer-Aided Drug Design

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Physics and Astronomy Courses

PHYS 570A: Computational Biomolecular Physics
PHYS 580: Computational Physics

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Statistics Courses

STAT 503: Statistical Methods for Biology
STAT 512: Applied Regression Analysis
STAT 514: Design of Experiments
STAT 516: Basic Probability and Applications
STAT 517: Statistical Inference or STAT 525: Intermediate Statistical Methodology/STAT 526: Advanced Statistical Methodology
STAT 524: Applied Multivariate Analysis
STAT 549: An Introduction To QTL Mapping In Experimental Populations
STAT 598C: Statistical Methods for Bioinformatics and Computational Biology
STAT 598G: Introduction to Computational Statistics

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