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Bioinformatics and Computational Biology

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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

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
PHYS 111General Physics5
or
Introduction to Classical Physics I
or
Physics for the Life Sciences
and Laboratory in Physics for the Life Sciences
STAT 330Probability and Statistics for Computer Science3
STAT 430Empirical Methods for the Computational Sciences3
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 314Principles of Molecular Cell Biology3
or
Biological Evolution
or
Molecular Genetics
Total Credits22

Complementary courses 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

6-7 credits:6-7
Principles of Genetics
and Genetics Laboratory
COM S 227
COM S 228
Introduction to Object-oriented Programming
and Introduction to Data Structures (recommended when developing course plan)
or
Fundamentals of Computer Programming
and Intermediate Computer Programming (allowed for students entering major who took these courses)
COM S 230Discrete Computational Structures3
COM S 311Design and Analysis of Algorithms3
MATH 165
MATH 166
Calculus I
and Calculus II (recommended when developing course plan)
8
or
Calculus and Mathematical Modeling for the Life Sciences I
and Calculus and Mathematical Modeling for the Life Sciences II (allowed for students entering major who took these courses)
BCBIO 110BCBIO Orientation0.5
BCBIO 322Introduction to Bioinformatics and Computational Biology3
BCBIO 401Fundamentals of Bioinformatics and Computational Biology3
BCBIO 402Fundamentals of Systems Biology and Network Science3
BCBIO 490Independent Study1-5
or BCBIO 491 Team Research Projects.
Total Credits30.5-35.5

Core courses note: The Com S 227/228 and Math 165/166 core course series is required for BCBio majors.  However, students transferring into the major who have already earned credit for Com S 207/208 and/or the Math 181/182 can substitute those courses for the respective Com S 227/228 and/or Math 165/166 series. Students will need permission of the instructors to enroll in any upper level course that requires a pre-req in Com S 227/228 and/or Math 165/166.

C. Support Electives

3-9 credits to be chosen from the following list:

BBMB 404Biochemistry I3
BBMB 405Biochemistry II3
BBMB 461Molecular Biophysics2
BIOL 328Molecular and Cellular Biology of Human Diseases3
BIOL 423Developmental Biology3
BIOL 451Plant Evolution and Phylogeny4
BIOL 462Evolutionary Genetics3
BIOL 487Microbial Ecology3
COM S 252Linux Operating System Essentials3
COM S 309Software Development Practices3
COM S 319Software Construction and User Interfaces3
COM S 327Advanced Programming Techniques3
COM S 363Introduction to Database Management Systems3
COM S 425High Performance Computing for Scientific and Engineering Applications3
COM S 426Introduction to Parallel Algorithms and Programming4
GEN 340Human Genetics3
GEN 410Analytical Genetics3
MATH 207Matrices and Linear Algebra3
or MATH 317 Theory of Linear Algebra
MATH 265Calculus III4
MATH 266Elementary Differential Equations3
or MATH 267 Elementary Differential Equations and Laplace Transforms
MATH 304Combinatorics3
MATH 314Graph Theory3
MATH 373Introduction to Scientific Computing3
MICRO 402Microbial Genetics and Genomics3
STAT 342Introduction to the Theory of Probability and Statistics II3
STAT 402Statistical Design and the Analysis of Experiments3
STAT 407Methods of Multivariate Analysis3
STAT 416Statistical Design and Analysis of Gene Expression Experiments3
STAT 444Bayesian Data Analysis3
STAT 480Statistical Computing Applications3

D. The communications and English proficiency requirements of the LAS college are met by:

ENGL 150Critical Thinking and Communication3
ENGL 250Written, Oral, Visual, and Electronic Composition3
or ENGL 250H Written, Oral, Visual, and Electronic Composition: Honors
And one of the following:
ENGL 309Proposal and Report Writing3
or
Biological Communication
or
Technical Communication

BCBio majors must earn a minimum grade of C in ENGL 250 Written, Oral, Visual, and Electronic Composition or ENGL 250H Written, Oral, Visual, and Electronic Composition: Honors.

Minor in Bioinformatics and Computational Biology

The administering departments offer a minor in Bioinformatics and Computational Biology, which requires the following courses.

BIOL 211Principles of Biology I3
BIOL 212Principles of Biology II3
GEN 313Principles of Genetics3
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 330Probability and Statistics for Computer Science3
BCBIO 322Introduction to Bioinformatics and Computational Biology3
BCBIO 401Fundamentals of Bioinformatics and Computational Biology3
BCBIO 402Fundamentals of Systems Biology and Network Science3
Total Credits28

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

2.  The Com S 227/228 course series is required for the BCBio minor.  However, students transferring into the minor who have already earned credit for Com S 207/208 can substitute those courses for the Com S 227/228 series. Students will need permission of the instructors to enroll in any upper level course that requires a pre-req in Com S 227/228.

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.

Bioinformatics and Computational Biology B.S.

Freshman
FallCreditsSpringCredits
BCBIO 1100.5BIOL 2123
BIOL 2113BIOL 212L1
BIOL 211L1CHEM 2313
CHEM 1634CHEM 231L1
CHEM 163L1MATH 1664
MATH 1654LIB 1601
ENGL 1503Humanities choice3
 16.5 16
Sophomore
FallCreditsSpringCredits
BIOL 3133COM S 2283
BIOL 313L1BIOL 3143
BCBIO 3223PHYS 1154
COM S 2274PHYS 115L1
ENGL 2503Social Science choice3
International Perspectives or U.S. Diversity3 
 17 14
Junior
FallCreditsSpringCredits
COM S 230 (or Cpr E 310)3COM S 3113
STAT 3303STAT 4303
ENGL 309 (or ENGL 312 or ENGL 314)3Bioinformatics Support Elective3-9
MATH 265 (or other Support Elective)4Humanities choice3
Humanites Choice3Social Science choice3
 16 15-21
Senior
FallCreditsSpringCredits
BCBIO 401 (or BCBIO 444)3BCBIO 4023
Humanities choice3BCBIO 490 or 4911-5
World Language if neeeded4World Language if needed or elective4
COM S 363 (Recommended or other support elective)3International Perspectives or US Diversity3
Social Science choice3 
 16 11-15

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 265Calculus III4
STAT 341Introduction to the Theory of Probability and Statistics I3
COM S 207Fundamentals of Computer Programming3
COM S 208Intermediate Computer Programming3
COM S 230Discrete Computational Structures3
CPR E 310Theoretical Foundations of Computer Engineering3
CHEM 163College Chemistry4
CHEM 231Elementary Organic Chemistry3
BBMB 301Survey of Biochemistry3
BIOL 313Principles of Genetics3
BIOL 315Biological Evolution3

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 567Bioinformatics I (Bioinformatics Algorithms)3
BCB 568Bioinformatics II (Statistical Bioinformatics)3
BCB 569Bioinformatics III (Structural Bioinformatics)3
BCB 570Bioinformatics IV (Systems Biology)3
And also should include
Advanced 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.)

Expand all courses

Courses

Courses primarily for undergraduates:

(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: bioinformatic data processing, Perl programming, genome assembly, database search, sequence alignment, gene prediction, next-generation sequencing, comparative and functional genomics, and systems biology.

Cr. 1-5. Repeatable, maximum of 9 credits. F.S.SS.

Prereq: Permission of instructor

Courses primarily for graduate students, open to qualified undergraduates:

(Cross-listed with COM S, CPR E, GDCB). (4-0) Cr. 4. F.

Prereq: MATH 165 or STAT 401 or equivalent
A practical, hands-on overview of how to apply bioinformatics to biological research. Recommended for biologists desiring to gain computational molecular biology skills. Topics include: sequence analysis, genomics, proteomics, phylogenetic analyses, ontology enrichment, systems biology, data visualization and emergent technologies.

(Cross-listed with COM S, CPR E). (3-0) Cr. 3. F.

Prereq: COM S 228; COM S 330; credit or enrollment in BIOL 315, STAT 430
Biology as an information science. A review of the algorithmic principles that are driving the advances in bioinformatics and computational biology.

(Cross-listed with COM S, GDCB, STAT). (3-0) Cr. 3. S.

Prereq: BCB 567 or (BIOL 315 and STAT 430), credit or enrollment in GEN 409
Statistical models for sequence data, including applications in genome annotation, motif discovery, variant discovery, molecular phylogeny, gene expression analysis, and metagenomics. Statistical topics include model building, inference, hypothesis testing, and simple experimental design, including for big data/complex models.

(Cross-listed with BBMB, COM S, CPR E, GDCB). (3-0) Cr. 3. F.

Prereq: BCB 567, BBMB 316, GEN 409, STAT 430
Molecular structures including genes and gene products: protein, DNA and RNA structure. Structure determination methods, structural refinement, structure representation, comparison of structures, visualization, and modeling. Molecular and cellular structure from imaging. Analysis and prediction of protein secondary, tertiary, and higher order structure, disorder, protein-protein and protein-nucleic acid interactions, protein localization and function, bridging between molecular and cellular structures. Molecular evolution.

(Cross-listed with COM S, CPR E, GDCB, STAT). (3-0) Cr. 3. S.

Prereq: BCB 567 or COM S 311, COM S 228, GEN 409, STAT 430
Algorithmic and statistical approaches in computational functional genomics and systems biology. Analysis of high throughput biological data obtained using system-wide measurements. Topological analysis, module discovery, and comparative analysis of gene and protein networks. Modeling, analysis, and inference of transcriptional regulatory networks, protein-protein interaction networks, and metabolic networks. Dynamic systems and whole-cell models. Ontology-driven, network based, and probabilistic approaches to information integration.

Cr. arr. Repeatable.

Prereq: Permission of instructor

(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.

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.

Courses for graduate students:

(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.

Cr. 1. Repeatable. S.


Student research presentations.

(1-0) Cr. 1. Repeatable.


Faculty research series.

Cr. arr. Repeatable. F.S.SS.


Graduate research projects performed under the supervision of selected faculty members in the Bioinformatics and Computational Biology major.

Cr. arr. Repeatable.


Courses

Courses primarily for undergraduates:

(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.

(Cross-listed with BIOL, GEN). (3-0) Cr. 3. F.

Prereq: BIOL 212
Genome sequencing, assembly, structural and functional annotation, and comparative genomics. Investigating these topics will develop skills in programming and scripting (Perl and/or Python), the use of biological databases, sequence alignment, similarity search, identification of sequence patterns, construction of phylogenetic trees, and comparative genomics.

(3-0) Cr. 3. F.

Prereq: BCBIO 322 and basic programming experience (e.g. COM S 207, COM S 227 or permission of instructor)
Application of computer science and engineering to molecular biology. String algorithms, sequence alignments, 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.

(3-0) Cr. 3. S.

Prereq: BIOL 212
Technologies: transcriptome, proteome, metabolome; Networks: Gene regulatory network, Protein-protein interaction network, Literature network; Theories: Graph theory, random network, scale-free network, evolving network, network robustness; Tools: Jmol, MeV, Cytoscape, Citespace.

(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.

(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.

(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.

(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.

(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.

(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: bioinformatic data processing, Perl programming, genome assembly, database search, sequence alignment, gene prediction, next-generation sequencing, comparative and functional genomics, and systems biology.

Cr. 1-5. Repeatable, maximum of 9 credits. F.S.SS.

Prereq: BCBIO 322, junior or senior classification, permission of instructor
Independent research projects for undergraduate students in bioinformatics and computational biology. Students in the College of Liberal Arts and Sciences may use no more than 9 credits of BCBIO 490 and 491 toward graduation.

Cr. 1-5. Repeatable, maximum of 9 credits. F.S.SS.

Prereq: BCBIO 322, 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.