Prerequisites

Students applying must have good quantitative skills with an undergraduate or higher degree from an accredited institution in mathematics, statistics, biostatistics, computer sciences, biomedical engineering, or other closely related areas. All prospective students must provide evidence of basic skills in computer programming through coursework. Typically, we expect all applicants to have taken the following courses or their equivalents. It is recommended that candidates will also have taken basic coursework in human biology and/or genetics. If you have any questions about whether a course will meet our prerequisites, please inquire by emailing OHIDS-Education@wustl.edu.

Applicants must earn a grade of C or better in the prerequisite courses as determined by your university’s grading scale. If a grading scale is not submitted with your transcript, Washington University in St. Louis’ grading scale will be used.

All prerequisite courses must be taken before an application is reviewed. If an applicant is currently enrolled in a prerequisite course, the application will be reviewed after the grade is provided. If the course is taken after the application deadline, the applicant will need to provide a transcript demonstrating enrollment. The application will be reviewed, but the admissions decision will be delayed until the grade is available.

REQUIRED COURSES:

Calculus I

Derivatives of algebraic, trigonometric, and transcendental functions, techniques of differentiation and applications of the derivative. The definite integral and Fundamental Theorem of Calculus. Areas. Simpler integration techniques.

Calculus II

Continuation of Calculus I. A brief review of the definite integral and Fundamental Theorem of Calculus. Techniques of integration, applications of the integral, sequences and series, and some material on differential equations.

Elementary Probability and Statistics OR Introduction to Statistics

An elementary introduction to probability and statistics. Discrete and continuous random variables, mean and variance, statistical inference (elementary probability and hypothesis testing), analysis of variance (ANOVA), (multiple) regression, contingency tables. A course covering only probability will not satisfy this prerequisite.

Computer Programming

A basic course in statistical or scientific computer programming. An introduction to software concepts and implementation, emphasizing problem solving through abstraction and decomposition. Introduces processes and algorithms, procedural abstraction, data abstraction, encapsulation and object-oriented programming. Recursion, iteration and simple data structures. Accepted languages include: SAS, R, Matlab, Python, C++. Java and VRB do not meet this requirement.

HIGHLY RECOMMENDED COURSES:

Linear Algebra

An introductory course in linear algebra that focuses on Euclidean n-space, matrices and related computations. Topics include: systems of linear equations, row reduction, matrix operations, determinants, linear independence, dimension, rank, change of basis, diagonalization, eigenvalues, eigenvectors, orthogonality, symmetric matrices, least square approximation, quadratic forms. Introduction to abstract vector spaces.

Data Structures and Algorithms

Study of fundamental algorithms, data structures, and their effective use in a variety of applications. Emphasizes importance of data structure choice and implementation for obtaining the most efficient algorithm for solving a given problem.

Calculus III

Multivariable calculus. Topics include differential and integral calculus of functions of two or three variables: vectors and curves in space, partial derivatives, multiple integrals, line integrals, vector calculus at least through Green’s Theorem.

Introduction to Biology and Genetics

Fundamentals of biology and genetics. A broad overview of genetics, including Mendelian assortment, linkage, chromosomal aberrations, variations in chromosome number, mutation, developmental genetics, quantitative genetics, population genetics, mechanisms of evolution, and phylogenetics.

Acceptance of Transfer Credits

We will accept transferable credits from other accredited institutions of higher education and from other programs at Washington University, provided that the didactic courses are considered to be essentially equivalent to the courses offered in our program. The Program administration will make such determinations. If a course was included as part of an earned degree, the course will be waived, however, the credit hours will be replaced with an approved elective. To graduate from the MSBDS or MSIBS program at least 75% of the credits must be completed through our graduate program (residency requirement). Therefore, we will accept a maximum of 10 transfer credits.