Bioinformatics and Computational Biology
Undergraduate study
Undergraduate study in BCBio is jointly administered by the Department of Computer Science, the Department of Genetics, Development, and Cell Biology, and the Department of Mathematics. The undergraduate B.S. degree is offered through the College of Liberal Arts and Sciences.
Bioinformatics and Computational Biology is an interdisciplinary science at the interfaces of the biological, informational and computational sciences. The science focuses on a variety of topics. These include gene identification, expression, and evolution; RNA, protein, and genome structure; and molecular and cellular systems and networks. The large group of participating faculty provides students with a multidimensional perspective on bioinformatics and computational biology and presents them with broad range of possibilities to get involved in research.
This major will prepare students for careers at the interfaces of biological, informational and computational sciences. BCBio graduates with a B.S. seeking direct employment will find ready markets for their talents in agricultural and medical biotechnology industries, as well as in academia, national laboratories, and clinics. Although some students find employment directly after their baccalaureate training, many students will continue their education in one of the many excellent graduate programs in bioinformatics and computational biology that now exist.
Participation in this field requires that students achieve a high level of competence not only in biology, but also in mathematics, computer science, and statistics. As a result, the program includes required courses from many different disciplines. Graduates demonstrate an above-average ability to synthesize methods from these different disciplines to solve problems.
In addition to basic degree requirements listed in the Curriculum in Liberal Arts and Sciences, BCBio majors must satisfy the following requirements:
A. Complementary Courses for the BCBio Major
| Choose from: | 5-8 | |
| College Chemistry and Laboratory in College Chemistry | ||
| or | ||
| General Chemistry I and Laboratory in General Chemistry I and General Chemistry II | ||
| or | ||
| Advanced General Chemistry and Laboratory in Advanced General Chemistry | ||
| Elementary Organic Chemistry and Laboratory in Elementary Organic Chemistry | ||
| or | ||
| Organic Chemistry I and Laboratory in Organic Chemistry I and Organic Chemistry II and Laboratory in Organic Chemistry II | ||
| General Physics | ||
| or | ||
| Introduction to Classical Physics I | ||
| or | ||
| Physics for the Life Sciences and Laboratory in Physics for the Life Sciences | ||
| STAT 330 | Probability and Statistics for Computer Science | 3 |
| STAT 430 | Empirical Methods for the Computational Sciences | 3 |
| BIOL 211 & 211L | Principles of Biology I and Principles of Biology Laboratory I | 4 |
| BIOL 212 & 212L | Principles of Biology II and Principles of Biology Laboratory II | 4 |
| BIOL 314 | Principles of Molecular Cell Biology | 3 |
| or | ||
| Biological Evolution | ||
| or | ||
| Molecular Genetics | ||
| Total Credits | 22-25 | |
Note : The following other STAT courses may be substituted for STAT 330 and STAT 430, with permission of the BCBio Major.
STAT 330: STAT 101, 104, 105, 201, 231, 305, or 341
STAT 430: STAT 301, 401, or 432
B. Core Courses Within the BCBio Major
| GEN 313 & 313L | Principles of Genetics and Genetics Laboratory | 4 |
| one of the following combinations: | 6-7 | |
| Introduction to Object-oriented Programming and Introduction to Data Structures | ||
| or | ||
| Fundamentals of Computer Programming and Intermediate Computer Programming | ||
| COM S 330 | Discrete Computational Structures | 3 |
| or CPR E 310 | Theoretical Foundations of Computer Engineering | |
| COM S 311 | Design and Analysis of Algorithms | 3 |
| MATH 165 & MATH 166 | Calculus I and Calculus II | 8 |
| or | ||
| Calculus and Mathematical Modeling for the Life Sciences I and Calculus and Mathematical Modeling for the Life Sciences II | ||
| BCBIO 110 | BCBIO Orientation | 0.5 |
| BCBIO 211 | Introduction to Bioinformatics and Computational Biology | 3 |
| BCBIO 401 | Fundamentals of Bioinformatics and Computational Biology I | 3 |
| BCBIO 402 | Fundamentals of Bioinformatics and Computational Biology II | 3 |
| BCBIO 490 | Independent Study | 1-5 |
| or BCBIO 491 | Team Research Projects. | |
| Total Credits | 34.5-39.5 | |
C. Support Electives
3-9 credits to be chosen from the following list:
| BBMB 404 | Biochemistry I | 3 |
| BBMB 405 | Biochemistry II | 3 |
| BBMB 461 | Molecular Biophysics | 2 |
| BIOL 328 | Molecular and Cellular Biology of Human Diseases | 3 |
| BIOL 423 | Developmental Biology | 3 |
| BIOL 451 | Plant Evolution and Phylogeny | 4 |
| BIOL 462 | Evolutionary Genetics | 3 |
| BIOL 465 | Morphometric Analysis | 4 |
| BIOL 487 | Microbial Ecology | 3 |
| COM S 252 | Linux Operating System Essentials | 3 |
| COM S 309 | Software Development Practices | 3 |
| COM S 319 | Software Construction and User Interfaces | 3 |
| COM S 327 | Advanced Programming Techniques | 3 |
| COM S 363 | Introduction to Database Management Systems | 3 |
| COM S 425 | High Performance Computing for Scientific and Engineering Applications | 3 |
| COM S 426 | Introduction to Parallel Algorithms and Programming | 4 |
| GEN 340 | Human Genetics | 3 |
| GEN 410 | Analytical Genetics | 3 |
| MATH 207 | Matrices and Linear Algebra | 3 |
| or MATH 317 | Theory of Linear Algebra | |
| MATH 265 | Calculus III | 4 |
| MATH 266 | Elementary Differential Equations | 3 |
| or MATH 267 | Elementary Differential Equations and Laplace Transforms | |
| MATH 304 | Combinatorics | 3 |
| MATH 314 | Graph Theory | 3 |
| MATH 373 | Introduction to Scientific Computing | 3 |
| MICRO 402 | Microbial Genetics and Genomics | 3 |
| STAT 342 | Introduction to the Theory of Probability and Statistics II | 3 |
| STAT 402 | Statistical Design and the Analysis of Experiments | 3 |
| STAT 407 | Methods of Multivariate Analysis | 3 |
| STAT 416 | Statistical Design and Analysis of Gene Expression Experiments | 3 |
| STAT 444 | Bayesian Data Analysis | 3 |
| STAT 480 | Statistical Computing Applications | 3 |
D. The communications and English proficiency requirements of the LAS college are met by:
| ENGL 150 | Critical Thinking and Communication | 3 |
| ENGL 250 | Written, Oral, Visual, and Electronic Composition | 3 |
| or ENGL 250H | Written, Oral, Visual, and Electronic Composition: Honors | |
| And one of the following: | ||
| Report and Proposal Writing | ||
| Biological Communication | ||
| Technical Communication | ||
The lowest grade acceptable in ENGL 150 Critical Thinking and Communication, ENGL 250 Written, Oral, Visual, and Electronic Composition or ENGL 250H Written, Oral, Visual, and Electronic Composition: Honors is C-.
Minor in Bioinformatics and Computational Biology
The administering departments offer a minor in Bioinformatics and Computational Biology, which requires the following courses.
| BIOL 211 | Principles of Biology I | 3 |
| BIOL 212 | Principles of Biology II | 3 |
| GEN 313 | Principles of Genetics | 3 |
| COM S 227 & COM S 228 | Introduction to Object-oriented Programming and Introduction to Data Structures | 7 |
| or | ||
| Fundamentals of Computer Programming and Intermediate Computer Programming | ||
| STAT 330 | Probability and Statistics for Computer Science | 3 |
| BCBIO 211 | Introduction to Bioinformatics and Computational Biology | 3 |
| BCBIO 401 | Fundamentals of Bioinformatics and Computational Biology I | 3 |
| BCBIO 402 | Fundamentals of Bioinformatics and Computational Biology II | 3 |
| Total Credits | 28 | |
Note: The following other STAT courses may be substituted for STAT 330, with permission of the BCBio Major: STAT 101, 104, 105, 201, 231, 305, or 341
Most students pursuing a minor in Bioinformatics and Computational Biology will be biology, genetics, computer science, computer engineering, statistics, or mathematics students who have already taken some of these courses for their major. However, a total of 9 credits must be used only to fulfill the requirements of the minor.
Graduate Study
Work is offered for the master of science and doctor of philosophy degrees with a major in Bioinformatics and Computational Biology (BCB). Faculty are drawn from several departments: Agronomy; Animal Science; Astronomy and Physics; Biochemistry, Biophysics and Molecular Biology; Biomedical Sciences; Chemical and Biological Engineering; Chemistry; Computer Science; Ecology, Evolution, and Organismal Biology; Electrical and Computer Engineering; Entomology, Genetics, Development and Cell Biology; Materials Science and Engineering; Mathematics; Plant Pathology; Statistics; Veterinary Microbiology and Preventive Medicine; and Veterinary Pathology.
The BCB program emphasizes interdisciplinary training in nine related areas of focus: Bioinformatics, Computational Molecular Biology, Structural and Functional Genomics, Macromolecular Structure and Function, Metabolic and Developmental Networks, Integrative Systems Biology, information Integration and Data Mining, Biological Statistics, and Mathematical Biology. Additional information about research areas and individual faculty members is available at: www.bcb.iastate.edu .
BCB students are trained to develop an independent and creative approach to science through an integrative curriculum and thesis research projects that include both computational and biological components. First year students are appointed as research assistants and participate in BCB 697 Graduate Research Rotation, working with three or more different research groups to gain experience in both “wet” (biological) and “dry” (computer) laboratory environments. In the second year, students initiate a thesis research project under the joint mentorship of two BCB faculty mentors, one from the biological sciences and one from the quantitative/computational sciences. The M.S. and Ph.D. degrees are usually completed in two and five years, respectively.
Before entering the graduate BCB program, prospective BCB students should have taken courses in mathematics, statistics, computer science, biology, and chemistry. A course load similar to the following list would be considered acceptable:
| MATH 265 | Calculus III | 4 |
| STAT 341 | Introduction to the Theory of Probability and Statistics I | 3 |
| COM S 207 | Fundamentals of Computer Programming | 3 |
| COM S 208 | Intermediate Computer Programming | 3 |
| COM S 330 | Discrete Computational Structures | 3 |
| CPR E 310 | Theoretical Foundations of Computer Engineering | 3 |
| CHEM 163 | College Chemistry | 4 |
| CHEM 231 | Elementary Organic Chemistry | 3 |
| BBMB 301 | Survey of Biochemistry | 3 |
| BIOL 313 | Principles of Genetics | 3 |
| BIOL 315 | Biological Evolution | 3 |
During the first year, BCB students are required to address any background deficiencies in calculus, molecular genetics, computer science, statistics and discrete structures, with specific courses determined by prior training. Among the total course requirements for Ph.D. students are four core courses in Bioinformatics:
| BCB 567 | Bioinformatics I (Fundamentals of Genome Informatics) | 3 |
| BCB 568 | Bioinformatics II (Advanced Genome Informatics) | 3 |
| BCB 569 | Bioinformatics III (Structural Genome Informatics) | 3 |
| BCB 570 | Bioinformatics IV (Computational Functional Genomics and Systems Biology) | 3 |
| And also should include | ||
| Molecular Genetics | ||
| Student Seminar in Bioinformatics and Computational Biology | ||
| Faculty Seminar in Bioinformatics and Computational Biology | ||
| Workshop in Bioinformatics and Computational Biology | ||
M.S. students take the above background and core courses, take at least 6 credits of advanced coursework, and may elect to participate in fewer seminars and workshops. Additional coursework may be selected to satisfy individual interests or recommendations of the Program of Study Committee. All graduate students are encouraged to teach as part of their training for an advanced degree. (For curriculum details and sample programs of study, see: www.bcb.iastate.edu .)
Courses
Courses primarily for undergraduates:
BCB 444. Introduction to Bioinformatics.
(Dual-listed with BCB 544). (Cross-listed with BCBIO, BIOL, COM S, CPR E, GEN). (4-0) Cr. 4.
F.
Prereq: MATH 165 or STAT 401 or equivalent
Broad overview of bioinformatics with a significant problem-solving component, including hands-on practice using computational tools to solve a variety of biological problems. Topics include: database searching, sequence alignment, gene prediction, RNA and protein structure prediction, construction of phylogenetic trees, comparative and functional genomics, systems biology.
BCB 490. Independent Study.
Cr. 1-5.
Repeatable, maximum of 9 credits. F.S.SS.
Prereq: Permission of instructor
Courses primarily for graduate students, open to qualified undergraduates:
BCB 544. Introduction to Bioinformatics.
(Dual-listed with BCB 444). (Cross-listed with COM S, CPR E, GDCB). (4-0) Cr. 4.
F.
Prereq: MATH 165 or STAT 401 or equivalent
Broad overview of bioinformatics with a significant problem-solving component, including hands-on practice using computational tools to solve a variety of biological problems. Topics include: database searching, sequence alignment, gene prediction, RNA and protein structure prediction, construction of phylogenetic trees, comparative, functional genomics, and systems biology.
BCB 567. Bioinformatics I (Fundamentals of Genome Informatics).
(Cross-listed with COM S, CPR E). (3-0) Cr. 3.
F.
Prereq: COM S 228; COM S 330; STAT 341; credit or enrollment in BIOL 315, STAT 430
Biology as an information science. Review of algorithms and information processing. Generative models for sequences. String algorithms. Pairwise sequence alignment. Multiple sequence alignment. Searching sequence databases. Genome sequence assembly.
BCB 568. Bioinformatics II (Advanced Genome Informatics).
(Cross-listed with COM S, GDCB, STAT). (3-0) Cr. 3.
S.
Prereq: BCB 567, BBMB 301, BIOL 315, STAT 430, credit or enrollment in GEN 411
Advanced sequence models. Basic methods in molecular phylogeny. Hidden Markov models. Genome annotation. DNA and protein motifs. Introduction to gene expression analysis.
BCB 569. Bioinformatics III (Structural Genome Informatics).
(Cross-listed with BBMB, COM S, CPR E). (3-0) Cr. 3.
F.
Prereq: BCB 567, GEN 411, STAT 430
Algorithmic and statistical approaches in structural genomics including protein, DNA and RNA structure. Structure determination, refinement, representation, comparison, visualization, and modeling. Analysis and prediction of protein secondary and tertiary structure, disorder, protein cores and surfaces, protein-protein and protein-nucleic acid interactions, protein localization and function.
BCB 570. Bioinformatics IV (Computational Functional Genomics and Systems Biology).
(Cross-listed with COM S, CPR E, GDCB, STAT). (3-0) Cr. 3.
S.
Prereq: BCB 567, BIOL 315, COM S 311 and either 208 or 228, GEN 411, STAT 430
Algorithmic and statistical approaches in computational functional genomics and systems biology. Elements of experiment design. Analysis of high throughput gene expression, proteomics, and other datasets obtained using system-wide measurements. Topological analysis, module discovery, and comparative analysis of gene and protein networks. Modeling, analysis, simulation and inference of transcriptional regulatory modules and networks, protein-protein interaction networks, metabolic networks, cells and systems: Dynamic systems, Boolean, and probabilistic models. Multi-scale, multi-granularity models. Ontology-driven, network based, and probabilistic approaches to information integration.
BCB 590. Special Topics.
Cr. arr.
Repeatable.
Prereq: Permission of instructor
BCB 593. Workshop in Bioinformatics and Computational Biology.
(1-0) Cr. 1.
Repeatable. F.S.
Current topics in bioinformatics and computational biology research. Lectures by off-campus experts. Students read background literature, attend preparatory seminars, attend all lectures, meet with lecturers.
BCB 598. Cooperative Education.
Cr. R.
Repeatable. F.S.SS.
Prereq: Permission of the program chair
Off-campus work periods for graduate students in the field of bioinformatics and computational biology.
BCB 599. Creative Component.
Cr. arr.
Courses for graduate students:
BCB 660. Selected Topics in Bioinformatics and Computational Biology.
(3-0) Cr. 1-4.
Repeatable, maximum of 4 times. F.S.SS.
Prereq: Permission of Instructor
Topics of interest in the major research areas of computational molecular biology, including genomics, structural genomics, functional genomics, and computational systems biology.
BCB 690. Student Seminar in Bioinformatics and Computational Biology.
Cr. 1.
Repeatable. S.
Student research presentations.
BCB 691. Faculty Seminar in Bioinformatics and Computational Biology.
(1-0) Cr. 1.
Repeatable.
Faculty research series.
BCB 697. Graduate Research Rotation.
Cr. arr.
Repeatable. F.S.SS.
Graduate research projects performed under the supervision of selected faculty members in the Bioinformatics and Computational Biology major.
BCB 699. Research.
Cr. arr.
Repeatable.
Courses
Courses primarily for undergraduates:
BCBIO 110. BCBIO Orientation.
(1-0) Cr. 0.5.
F.
First 8 weeks. Orientation to the area of bioinformatics and computational biology. For students considering a major in BCBIO. Specializations and career opportunities.
Offered on a satisfactory-fail basis only.
BCBIO 211. Introduction to Bioinformatics and Computational Biology.
(3-0) Cr. 3.
S.
Perl programming, molecular biology, biological databases, sequence alignment, homology search, identification of sequence patterns, construction of phylogenetic trees, gene function prediction, gene structure prediction, genomic annotation and comparative genomics.
BCBIO 401. Fundamentals of Bioinformatics and Computational Biology I.
(3-0) Cr. 3.
F.
Prereq: BCBIO 211 and basic programming experience (e.g. COM S 207, COM S 208, COM S 227 or permission of instructor)
Application of computer science to molecular biology. String algorithms, sequence alignments, indexing data structures, homology search methods, pattern recognition, fragment assembly, genome annotation, construction of bioinformatics databases, and gathering and distribution of biological information with the Internet.
BCBIO 402. Fundamentals of Bioinformatics and Computational Biology II.
(3-0) Cr. 3.
S.
Prereq: BCBIO 401
Genomics: Gene structure prediction, gene function prediction and comparative genomics. Post-genomics: Gene expression studies, DNA microarrays, next-generation sequencing of transcriptome. Structural biology: Protein and RNA structure predictions, structure representation, comparison and visualization. Systems biology: Signal transduction pathway inference, biological networks and systems.
BCBIO 442. Bioinformatics and Computational Biology Techniques.
(0.2-0.5) Cr. 0.5.
Repeatable, maximum of 2 credits. S.SS.
Prereq: BIOL 314 recommended
Modular minicourses consisting of guided tutorials and hands-on computer software exercises focused on fundamental problems, approaches, and software applications in bioinformatics and computational biology.
Offered on a satisfactory-fail basis only.
BCBIO 442A. Bioinformatics and Computational Biology Techniques: Sequence Database Searching.
(0.2-0.5) Cr. 0.5.
Repeatable, maximum of 2 credits. S.SS.
Prereq: BIOL 314 recommended
Modular minicourses consisting of guided tutorials and hands-on computer software exercises focused on fundamental problems, approaches, and software applications in bioinformatics and computational biology.
Offered on a satisfactory-fail basis only.
BCBIO 442B. Bioinformatics and Computational Biology: Protein Structure Databases, Visualization, and Prediction.
(0.2-0.5) Cr. 0.5.
Repeatable, maximum of 2 credits. S.SS.
Prereq: BIOL 314 recommended
Modular minicourses consisting of guided tutorials and hands-on computer software exercises focused on fundamental problems, approaches, and software applications in bioinformatics and computational biology.
Offered on a satisfactory-fail basis only.
BCBIO 442C. Bioinformatics and Computational Biology Techniques: Phylogenetic Analysis.
(0.2-0.5) Cr. 0.5.
Repeatable, maximum of 2 credits. S.SS.
Prereq: BIOL 314 recommended
Modular minicourses consisting of guided tutorials and hands-on computer software exercises focused on fundamental problems, approaches, and software applications in bioinformatics and computational biology.
Offered on a satisfactory-fail basis only.
BCBIO 442D. Bioinformatics and Computational Biology Techniques: Microarray Analysis.
(0.2-0.5) Cr. 0.5.
Repeatable, maximum of 2 credits. S.SS.
Prereq: BIOL 314 recommended
Modular minicourses consisting of guided tutorials and hands-on computer software exercises focused on fundamental problems, approaches, and software applications in bioinformatics and computational biology.
Offered on a satisfactory-fail basis only.
BCBIO 444. Introduction to Bioinformatics.
(Cross-listed with BCB, BIOL, COM S, CPR E, GEN). (4-0) Cr. 4.
F.
Prereq: MATH 165 or STAT 401 or equivalent
Broad overview of bioinformatics with a significant problem-solving component, including hands-on practice using computational tools to solve a variety of biological problems. Topics include: database searching, sequence alignment, gene prediction, RNA and protein structure prediction, construction of phylogenetic trees, comparative and functional genomics, systems biology.
BCBIO 490. Independent Study.
Cr. 1-5.
Repeatable, maximum of 9 credits. F.S.SS.
Prereq: BCBIO 211, junior or senior classification, permission of instructor
Students in the College of Liberal Arts and Sciences may use no more than 9 credits of BCBIO 490 and 491 toward graduation.
BCBIO 491. Team Research Projects..
Cr. 1-5.
Repeatable, maximum of 9 credits.
Prereq: BCBIO 211, junior or senior classification, permission of instructor
Research projects in bioinformatics and computational biology done by teams of students.
Students in the College of Liberal Arts and Sciences may use no more than 9 credits of BCBIO 490 and 491 toward graduation.
