About

Members

Curriculum

Research

Students

About

The Genomics Education Partnership is a nationwide collaboration of institutions that integrates active learning into the undergraduate curriculum through Course-based Undergraduate Research Experiences centered in bioinformatics and genomics.

Members

Our nationwide community of 250+ faculty from more than 200 colleges and universities are dedicated to facilitating equity in undergraduate biology education.

Curriculum

Our members use GEP materials in a wide variety of ways depending on the course structure and student backgrounds. These implementations range from incorporating short lessons into an existing course (e.g., using a genome browser to investigate eukaryotic gene structure) to participating in a genomics Course-based Undergraduate Research Experience centered around comparative gene annotation.

Research

Research Projects

The Genomics Education Partnership introduces students to research in genomics by engaging them in projects for which careful annotation of genes from recently sequenced species provides important data. Many scientific questions can be addressed using comparative genomics, as evolution enables us to identify conserved features and important changes.

Students

Genomics Education Partnership students can receive real time support in GEP activities and research by visiting a Virtual TA.

Isoforms

Module 6. Alternative splicing

August 15, 2020January 15, 2023

This module explores how multiple different mRNAs and polypeptides can be encoded by the same gene. After completing this module students will be able to explain how alternative splicing of a gene can lead to different mRNAs and illustrate how alternative splicing can lead to the production of different polypeptides and result in drastic changes in phenotype.

Module 4. Removal of introns from pre-mRNA by splicing

August 15, 2020January 15, 2023

This module uses mRNA data to identify splice sites. After completing this module students will be able to identify intron-exon boundaries using canonical splice donor and acceptor sequences and determine which are best supported by RNA-Seq and TopHat splice junction predictions.