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Educational Opportunities

Online Bioinformatics Workshops

The Iowa Institute of Human Genetics (IIHG) will host workshops focusing on a bioinformatics tool or software.

Computational Biology Seminar Series

The Iowa Institute of Human Genetics (IIHG) hosts informational seminars on key topics and developments in bioinformatics, led by experts in the field. The next Computational Biology Seminar will be scheduled for fall/winter 2020.

Personalized Genomic Medicine: Careers in Bioinformatics and Big Data Information Session

The Iowa Institute of Human Genetics (IIHG) is hosting a Careers in Bioinformatics Information Session to expose students to career opportunities that are being created by personalized genomic medicine in bioinformatics and the management of big data. You can learn first-hand about the diversity of career options and job growth in bioinformatics that is occurring with the advent of personalized genomic medicine. Listen to a panel with expertise in bioinformatics, software development, systems administration, clinical informatics, and industry and their role in the field of personalized genomic medicine. Undergraduate students, academic advisors and graduate students wishing to learn more about careers in bioinformatics. Enrollment is limited to 50 participants. 


We provide video learning opportunities for a variety of bioinformatics topics. View past lectures and walkthrough videos on introductory bioinformatics material.

Previous Bioinformatics Education Events

The Iowa Institute of Human Genetics (IIHG) has hosted a range of educational opportunities focused on bioinformatics, including hands-on learning sessions, summer short courses in bioinformatics, and more.

CBIO:3310 Practical Data Science and Bioinformatics

The IIHG has been involved with Miles Pufall to develop and TA this course for undergraduates in computational biology. 

Course summary:  "Understanding how to access large biological data sets and use them to answer biological questions is an important skill for researchers; immersive introduction to computational handling of data; how to access and analyze publicly available data; critically evaluate data quality and analysis in context of measuring gene expression; basic coding in R/RStudio, plotting and data display, fitting and regression, statistical inference, statistical models, downloading and data wrangling; basic introduction to machine learning (clustering); for students with no computational background. Prerequisites: BIOL:1411 with a minimum grade of C- and BIOL:1412 with a minimum grade of C-. Requirements: college algebra. Recommendations: BIOC:3110, or BIOC:3120 and BIOC:3130, or other upper-level life sciences courses. Same as BIOC:3310, MMED:3310."