Students in the computational life sciences graduate certificate program develop expertise in the understanding, interpretation and analysis of diverse data types generated from a variety of life sciences disciplines, including ecology, botany, evolutionary biology, neuroscience, molecular and cellular biology, and animal behavior. 

The current degree requirements are below. Remember you are required to fulfill the requirements for the academic year you were admitted -- refer to the corresponding handbook as needed.

Required Core (1 credit hour)

BIO 511 Big Data in Context: Ethics, Policy, History, and Philosophy

BIO 610 Introduction to Responsible Conduct of Research in Life Sciences

Electives (15 credit hours)

BIO 543 Molecular Genetics and Genomics (3)

BIO 514 Statistical Models for Biology (4)

BIO 539 Computing for Research (3)

MCB 540 Functional Genomics (3)

BIO 579 Data Analysis and Visualization in R (3)

BIO 544 Discovering Biodiversity (3)

BIO 598 Genomics Research Experience (3)

BIO 591 Quantitative Methods in Conservation and Ecology (4)

BIO 598 Population and Community Ecology (3)

Non-SOLS Elective Options

BMI 517 Adv Biostats Biomed Research

BMI 603 Health Informatics Database 

BMI 515 App Biostats Med & Informatics

HCD 501 Biostatistics & Data Management 

APM 533 Mathematical Population Biology I 

BME  598 Systems Biology of Disease

BMI 555 Statistics Learning for Data Mining  

BMI 598 Biostatistics with Computational Applications 

CHM 598 Quantitative Foundation of Modern Biochemistry 

CHM 598 Unraveling the Noise: Data Driven Models and Analysis

CSE 598 Algorithms in Computational Biology

CSE 598 Bio-Inspired Computing

ERM 598 Algal Bioprocess and Biosystems Engineering

GIS 598 GIS methods for Non-Majors

HCR 562 Clinical Research Data Management & Technology

SOS 598 Research Data Management course

Additional Curriculum Information
Elective coursework is selected from a restricted list in consultation with the academic unit.

The final requirement to complete the certificate and graduate is to write a one‐page summary explaining how you applied computational approaches to a biological problem. It may be based on a course project or lab experience. Please email this summary to Program Directors, Dr. Snyder-Mackler and Dr. Kenneth Buetow.