The foundation disciplines for BCB are genetics, molecular biology, mathematics, computer science, statistics and physics. Students entering the BCB program are expected to have a strong undergraduate background in at least one of these disciplines and additional coursework in another.
The following tables summarize the three areas in which BCB majors must demonstrate basic competence. A flow chart CurriculumChart2015.pdf of the prerequisite, background and core courses is also provided.
Students are strongly encouraged to take courses equivalent to the ISU courses listed under Course Prerequisites for Admission to BCB prior to enrollment in the BCB program, but will have the opportunity to make up deficiencies during the first year of BCB graduate training. Courses listed under BCB Background Coursework Requirements are prerequisites for BCB core courses. These background courses should be completed either prior to admission or during the first year of BCB graduate training. The temporary advisor or major professor helps each student determine whether additional courses are needed. The student's POS committee will evaluate competence in the three background areas during the student's second Annual POS Committee meeting.

Course Prerequisites for Admission to BCB 
Category I. Mathematics and Statistics 

Math 265 or equiv.  Math 265. Calculus III. (40) Cr. 4. F*.S.SS.Prereq: Grade of C or better in 166 or 166H. Analytic geometry and vectors, differential calculus of functions of several variables, multiple integrals, vector calculus. 
Stat 341 or equiv  Stat 341. Introduction to the Theory of Probability and Statistics I. (30) Cr. 3. F.S.Prereq: Math 265 (or 265H). Probability; distribution functions and their properties; classical discrete and continuous distribution functions; multivariate probability distributions and their properties; moment generating functions; simulation of random variables and use of the R statistical package. 
Category II. Biological Sciences 

Biol 313 or equiv.  Biol 313. Principles of Genetics. (Crosslisted with Gen). (30) Cr. 3. F.S.Prereq: 211, 211L, 212, and 212L. Introduction to the principles of transmission and molecular genetics of plants, animals, and bacteria. Recombination, structure and replication of DNA, gene expression, cloning, quantitative and population genetics. 
BBMB 316 or equiv. 
BBMB 316. Principles of Biochemistry. (30) Cr. 3. F. Prereq: CHEM 231 or CHEM 331, BIOL 212. Understanding biological systems at the molecular level; chemistry of biological macromolecules, enzyme function and regulation, metabolic pathways; integration of metabolism in diverse living systems. For students in biology and related majors who do not require the more rigorous treatment of biochemistry found in BBMB 404/405. 
Biol 315 
Biol 315. Biological Evolution. (30) Cr. 3. F.S.Prereq: 313. The mechanisms of evolution. Topics in microevolution: population genetics, natural selection, genetic variation, and adaptation. Macroevolution: speciation, extinction, phylogeny, and major evolutionary patterns. 
Category III. Computer Science 

Com S 227 or equiv 
COM S 227. Introduction to Objectoriented Programming. (32) Cr. 4. F.S. Prereq: Placement into Math 143, 165, or higher; recommended: a previous high school or college course in programming or equivalent experience. Introduction to objectoriented design and programming techniques. Symbolic and numerical computation, recursion and iteration, modularity procedural and data abstraction, and specifications and subtyping. Objectoriented techniques including encapsulation, inheritance and polymorphism. Imperative programming. Emphasis on principles of programming and objectoriented design through extensive practice in design, writing, running, debugging, and reasoning. Course intended for Com S majors. Credit may not be applied toward graduation for both Com S 207 and 227. 
Com S 228 or equiv 
COM S 228. Introduction to Data Structures. (31) Cr. 3. F.S. Prereq: Minimum of C in 227, credit or enrollment in Math 165. An objectoriented approach to data structures and algorithms. Objectoriented analysis, design, and programming, with emphasis on data abstraction, inheritance and subtype polymorphism. Abstract data type specification and correctness. Collections and associated algorithms, such as stacks, queues, lists, trees. Searching and sorting algorithms. Graphs. Data on secondary storage. Analysis of algoritms. Emphasis on objectoriented design, writing and documenting mediumsized programs. This course is designed for majors. 
Com S 330 or equiv 
Com S 330. Discrete Computational Structures. (31) Cr. 3. F.S.Prereq: C or higher in 228, C or higher in Math 166 and Engl 250. Concepts in discrete mathematics as applied to computer science. Logic, proof techniques, set theory, relations, graphs, combinatorics, discrete probability and number theory. 
*F = Fall semester; S = Spring semester; SS = Summer Session

BCB Background CourseworkCourses (or equiv.) that should be taken prior to enrollment or during first year unless similar coursework was completed prior to joining the BCB Program 
Category I. Mathematics and Statistics 

Stat 430 
Empirical Methods for the Computational Sciences. (30) Cr. 3. F. Prereq: STAT 330 or an equivalent course, MATH 166, knowledge of linear algebra. Statistical methods for research involving computers; exploratory data analysis; selected topics from analysis of designed experiments  analysis of variance, hypothesis testing, interaction among variables; linear regression, logistic regression, Poisson regression; parameter estimation, prediction, confidence regions, dimension reduction techniques, model diagnostics and sensitivity analysis; Markov chains and processes; simulation techniques and bootstrap methods; applications to computer science, bioinformatics, computer engineering  programs, models and systems as objects of empirical study; communicating results of empirical studies. Statistical software: R. 
Category II. Biological Sciences 

Gen 409 
Molecular Genetics. (30) Cr. 3. F. Prereq: Biol 314. The principles of molecular genetics: gene structure and function at the molecular level, including regulation of gene expression, genetic rearrangement, and the organization of genetic information in prokaryotes and eukaryotes. 
Category III. Computer Science 

Com S 311 
COM S 311. Design and Analysis of Algorithms. (31) Cr. 3. F.S. Prereq: Minimum of C in Com S 228, Math 166, Engl 250, and Com S 330 or CPRE 310. Basic techniques for design and analysis of efficient algorithms. Sorting, searching, graph algorithms, computational geometry, string processing and NPcompleteness. Design techniques such as dynamic programming and the greedy method. Asymptotic, worstcase, averagecase and amortized analyses. Data structures including heaps, hash tables, binary search trees and redblack trees. Programming projects. 
*F = Fall semester; S = Spring semester; SS = Summer Session