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Twin Cities Campus

Computational Biology Minor

College of Biological Sciences - Adm
College of Biological Sciences
  • Program Type: Undergraduate free-standing minor
  • Requirements for this program are current for Fall 2020
  • Required credits in this minor: 25 to 26
Large-scale data is now a norm in biology and the math and computational skills needed to analyze large-scale data have become crucial in almost every field of biology. For example, the analysis of big data is essential for modern personalized medicine and precision agriculture. The ability to properly analyze and interpret biological data requires biological knowledge and experience as well. Accordingly, the number of biology-related jobs that require math or computational skills has been rapidly increasing in both industry and academia. Courses in the minor were selected mainly because they combine computation or mathematical analysis with biology. The minor is designed to give undergraduate students in biology-related majors the math and computational skills necessary for current biological research.
Program Delivery
This program is available:
  • via classroom (the majority of instruction is face-to-face)
Admission Requirements
For information about University of Minnesota admission requirements, visit the Office of Admissions website.
Required prerequisites
Prerequisites
These courses are prerequisites for courses required in the minor.
BIOL 1009 - General Biology [BIOL] (4.0 cr)
or BIOL 1951 - Foundations of Biology Lecture I for Biological Sciences Majors [BIOL] (4.0 cr)
or BIOL 1951H - Foundations of Biology Lecture I for Biological Sciences Majors [BIOL] (4.0 cr)
Minor Requirements
Students may take both BIOL 3272/3272H/5272 and CSCI 3003 and can count one of them as a required course and the other for additional credits toward the minor.
Genetics
GCD 3022 - Genetics (3.0 cr)
or BIOL 4003 - Genetics (3.0 cr)
Applied Biostatistics or Intro to Computing in Biology
BIOL 3272 - Applied Biostatistics (4.0 cr)
or BIOL 3272H - Applied Biostatistics (4.0 cr)
or BIOL 5272 - Applied Biostatistics (4.0 cr)
or CSCI 3003 - Introduction to Computing in Biology (3.0 cr)
Computational Biology Minor Electives
Take 15 or more credit(s) from the following:
· AGRO 5431 - Applied Plant Genomics and Bioinformatics (3.0 cr)
· BIOC 4521 - Introduction to Physical Biochemistry (3.0 cr)
· BIOC 5361 - Microbial Genomics and Bioinformatics (3.0 cr)
· BIOC 5527 {Inactive} (4.0 cr)
· CSCI 3003 - Introduction to Computing in Biology (3.0 cr)
· CSCI 5461 - Functional Genomics, Systems Biology, and Bioinformatics (3.0 cr)
· CSCI 5481 - Computational Techniques for Genomics (3.0 cr)
· EEB 5042 - Quantitative Genetics (3.0 cr)
· EEB 5371 - Principles of Systematics (3.0 cr)
· GCD 3485 - Bioinformatic Analysis: Introduction to the Computational Characterization of Genes and Proteins (4.0 cr)
· GCD 5005 - Computer Programming for Biology (3.0 cr)
· MATH 2241 - Mathematical Modeling of Biological Systems (3.0 cr)
· PHCL 5111 - Pharmacogenomics (3.0 cr)
· PLPA 5301 - Large Scale Omic Data in Plant Biology (3.0 cr)
· VMED 5181 - Spatial Analysis in Infectious Disease Epidemiology (3.0 cr)
· BIOL 3272 - Applied Biostatistics (4.0 cr)
or BIOL 3272H - Applied Biostatistics (4.0 cr)
or BIOL 5272 - Applied Biostatistics (4.0 cr)
 
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· College of Biological Sciences

View future requirement(s):
· Fall 2022


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· Computational Biology Minor
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BIOL 1009 - General Biology (BIOL)
Credits: 4.0 [max 4.0]
Course Equivalencies: Biol 1009/Biol 1009H
Typically offered: Every Fall, Spring & Summer
A comprehensive introduction to biology - includes molecular structure of living things, cell processes, energy utilization, genetic information and inheritance, mechanisms of evolution, biological diversity, and ecology. Includes lab. This comprehensive course serves as a prerequisite and requirement in many majors.
BIOL 1951 - Foundations of Biology Lecture I for Biological Sciences Majors (BIOL)
Credits: 4.0 [max 4.0]
Course Equivalencies: Biol 1951/H/Biol 2002/H
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Core biological concepts, from biomolecules to ecosystems. Emphasizes evolution, organismal diversity, and genetics within context of problem solving/applications. Students must take both BIOL 1951 and BIOL 1961 to be awarded the Biological Sciences LE. This course is required for all CBS majors
BIOL 1951H - Foundations of Biology Lecture I for Biological Sciences Majors (BIOL)
Credits: 4.0 [max 4.0]
Course Equivalencies: Biol 1951/H/Biol 2002/H
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Core biological concepts, from biomolecules to ecosystems. Emphasizes evolution, organismal diversity, and genetics within context of problem solving/applications. Students must take both BIOL 1951H and BIOL 1961 to be awarded the Biological Sciences LE. This course is required for all CBS honors students
GCD 3022 - Genetics
Credits: 3.0 [max 3.0]
Course Equivalencies: Biol 4003/GCD 3022
Typically offered: Every Fall, Spring & Summer
Mechanisms of heredity, implications for biological populations. Applications to practical problems. prereq: Introductory biology course such as Biol 1009
BIOL 4003 - Genetics
Credits: 3.0 [max 3.0]
Course Equivalencies: Biol 4003/GCD 3022
Typically offered: Every Fall, Spring & Summer
Genetic information, its transmission from parents to offspring, its expression in cells/organisms, and its course in populations. prereq: Biol 2003/2003H or BioC 3021 or BioC 4331 or grad
BIOL 3272 - Applied Biostatistics
Credits: 4.0 [max 3.0]
Course Equivalencies: Biol 3272Biol 3272H//Biol 5272
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Conceptual basis of statistical analysis. Statistical analysis of biological data. Data visualization, descriptive statistics, significance tests, experimental design, linear model, simple/multiple regression, general linear model. Lectures, computer lab. prereq: High school algebra; BIOL 2003 recommended
BIOL 3272H - Applied Biostatistics
Credits: 4.0 [max 4.0]
Course Equivalencies: Biol 3272Biol 3272H//Biol 5272
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Conceptual basis of statistical analysis. Statistical analysis of biological data. Data visualization, descriptive statistics, significance tests, experimental design, linear model, simple/multiple regression, general linear model. Lectures, computer lab. prereq: High school algebra; BIOL 2003 recommended.
BIOL 5272 - Applied Biostatistics
Credits: 4.0 [max 3.0]
Course Equivalencies: Biol 3272Biol 3272H//Biol 5272
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Conceptual basis of statistical analysis. Statistical analysis of biological data. Data visualization, descriptive statistics, significance tests, experimental design, linear model, simple/multiple regression, general linear model. Lectures, computer lab. prereq: High school algebra; BIOL 2003 recommended.
CSCI 3003 - Introduction to Computing in Biology
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 3003/CSci 5465
Typically offered: Fall Odd Year
This course builds computational skills needed to carry out basic data analysis tasks common in modern biology. Students will learn computing concepts (algorithm development, data structures, complexity analysis) along with practical programming skills in Python and R. No previous programming knowledge assumed. Prereq: introductory biology course.
AGRO 5431 - Applied Plant Genomics and Bioinformatics
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Analysis, interpretation, visualization of large plant genomic datasets. Basic computer programming, applying large-scale genomics to answer basic/applied biological questions, understanding limitations of each application, presenting concise visual findings from large-scale datasets. prereq: Grad student or [undergrad with genetics course]
BIOC 4521 - Introduction to Physical Biochemistry
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Physical chemical principles, their applications in biochemistry. Thermodynamics, kinetics, spectroscopy, solution dynamics as applied to biochemical reactions/ biopolymers. prereq: 4331 recommended, (Chem 1081 or 1061 and 1065) AND (Physics 1221 or 1201W or 1301W) required
BIOC 5361 - Microbial Genomics and Bioinformatics
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Introduction to genomics. Emphasizes microbial genomics. Sequencing methods, sequence analysis, genomics databases, genome mapping, prokaryotic horizontal gene transfer, genomics in biotechnology, intellectual property issues. Hands-on introduction to UNIX shell scripting, genomic data analysis using R and Excel in a computer lab setting. prereq: College-level courses in [organic chemistry, biochemistry, microbiology]
CSCI 3003 - Introduction to Computing in Biology
Credits: 3.0 [max 3.0]
Course Equivalencies: CSci 3003/CSci 5465
Typically offered: Fall Odd Year
This course builds computational skills needed to carry out basic data analysis tasks common in modern biology. Students will learn computing concepts (algorithm development, data structures, complexity analysis) along with practical programming skills in Python and R. No previous programming knowledge assumed. Prereq: introductory biology course.
CSCI 5461 - Functional Genomics, Systems Biology, and Bioinformatics
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Computational methods for analyzing, integrating, and deriving predictions from genomic/proteomic data. Analyzing gene expression, proteomic data, and protein-protein interaction networks. Protein/gene function prediction, Integrating diverse data, visualizing genomic datasets. prereq: 3003 or 4041 or instr consent
CSCI 5481 - Computational Techniques for Genomics
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Techniques to analyze biological data generated by genome sequencing, proteomics, cell-wide measurements of gene expression changes. Algorithms for single/multiple sequence alignments/assembly. Search algorithms for sequence databases, phylogenetic tree construction algorithms. Algorithms for gene/promoter and protein structure prediction. Data mining for micro array expression analysis. Reverse engineering of regulatory networks. prereq: 4041 or instr consent
EEB 5042 - Quantitative Genetics
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
Fundamentals of quantitative genetics. Genetic/environmental influences on expression of quantitative traits. Approaches to characterizing genetic basis of trait variation. Processes that lead to change in quantitative traits. Applied/evolutionary aspects of quantitative genetic variation. prereq: [BIOL 4003 or GCD 3022] or instr consent; a course in statistics is recommended
EEB 5371 - Principles of Systematics
Credits: 3.0 [max 3.0]
Typically offered: Fall Odd Year
Theoretical/practical procedures of biological systematics. Phylogeny reconstruction. Computer-assisted analyses, morphological and molecular approaches, species concepts/speciation, comparative methods, classification, historical biogeography, nomenclature, use/value of museums. prereq: Grad student or instr consent
GCD 3485 - Bioinformatic Analysis: Introduction to the Computational Characterization of Genes and Proteins
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Bioinformatic analysis is the exploration of molecular sequence, structure, and function using online tools and databases. In this class, we'll learn to use some of the most powerful tools available for biologists to investigate the nature of genes and proteins. We will each explore a gene and the protein it encodes that no one before us has studied. We will learn to analyze and interpret the diverse forms of bioinformatic data we obtain, and we will consider how the data we find allows us to generate and evaluate original hypotheses that can be tested in the laboratory. This is a hands-on course. While the class has no exams, it does require the completion of four problem sets and a summative final project over the course of the semester. It also involves doing some peer review of classmates? work. prereq: introductory course in genetics and cell biology such as Foundations
GCD 5005 - Computer Programming for Biology
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Computer programming skills with applications in biology. Design/build new computer programs for applications in cell/developmental biology, including modeling of biological processes, advanced data analysis, automated image analysis. prereq: BIOL 4003 or BIOL 4004 or GCD 3033 or CBS grad or BMBB or MCDB&G grad student, general statistics course
MATH 2241 - Mathematical Modeling of Biological Systems
Credits: 3.0 [max 4.0]
Typically offered: Every Fall & Spring
Development, analysis and simulation of models for the dynamics of biological systems. Mathematical topics include discrete and continuous dynamical systems, linear algebra, and probability. Models from fields such as ecology, epidemiology, physiology, genetics, neuroscience, and biochemistry. prereq: [1241 or 1271 or 1371] w/grade of at least C-
PHCL 5111 - Pharmacogenomics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Human genetic variation, its implications. Functional genomics, pharmacogenomics, toxicogenomics, proteomics. Interactive, discussion-based course. prereq: Grad student or instr consent Keywords: Pharmacology, Pharmacogenomics, Toxicogenomics, Proteomics, Genetics, Drug
PLPA 5301 - Large Scale Omic Data in Plant Biology
Credits: 3.0 [max 3.0]
Typically offered: Every Fall
Introduction to large scale data in plant biology. Emphasizes model plants and important agricultural crops focusing on new approaches and technologies in the field. Fundamentals, acquisition, and analysis of high-throughput DNA and RNA sequencing, high-throughput plant phenotyping, functional and comparative genomics, epigenomics, proteomics, metabolomics, and microbiomics. prereq: Intro course in genetics or instr consent
VMED 5181 - Spatial Analysis in Infectious Disease Epidemiology
Credits: 3.0 [max 3.0]
Grading Basis: OPT No Aud
Typically offered: Every Spring
Spatial distribution of disease events. Exposures/outcomes. Factors that determine where diseases occur. Analyzing spatial disease data in public health, geography, epidemiology. Focuses on human/animal health related examples. prereq: Intro to epidemiology, statistics,
BIOL 3272 - Applied Biostatistics
Credits: 4.0 [max 3.0]
Course Equivalencies: Biol 3272Biol 3272H//Biol 5272
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Conceptual basis of statistical analysis. Statistical analysis of biological data. Data visualization, descriptive statistics, significance tests, experimental design, linear model, simple/multiple regression, general linear model. Lectures, computer lab. prereq: High school algebra; BIOL 2003 recommended
BIOL 3272H - Applied Biostatistics
Credits: 4.0 [max 4.0]
Course Equivalencies: Biol 3272Biol 3272H//Biol 5272
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Conceptual basis of statistical analysis. Statistical analysis of biological data. Data visualization, descriptive statistics, significance tests, experimental design, linear model, simple/multiple regression, general linear model. Lectures, computer lab. prereq: High school algebra; BIOL 2003 recommended.
BIOL 5272 - Applied Biostatistics
Credits: 4.0 [max 3.0]
Course Equivalencies: Biol 3272Biol 3272H//Biol 5272
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Conceptual basis of statistical analysis. Statistical analysis of biological data. Data visualization, descriptive statistics, significance tests, experimental design, linear model, simple/multiple regression, general linear model. Lectures, computer lab. prereq: High school algebra; BIOL 2003 recommended.