Fostering bioinformatics education through skill development of professors: Big Genomic Data Skills Training for Professors

Abstract

Bioinformatics has become an indispensable part of life science over the past 2 decades. However, bioinformatics education is not well integrated at the undergraduate level, especially in liberal arts colleges and regional universities in the United States. One significant obstacle pointed out by the Network for Integrating Bioinformatics into Life Sciences Education is the lack of faculty in the bioinformatics area. Most current life science professors did not acquire bioinformatics analysis skills during their own training. Consequently, a great number of undergraduate and graduate students do not get the chance to learn bioinformatics or computational biology skills within a structured curriculum during their education. To address this gap, we developed a module-based, week-long short course to train small college and regional university professors with essential bioinformatics skills. The bioinformatics modules were built to be adapted by the professor-trainees afterward and used in their own classes. All the course materials can be accessed at https://github.com/TheJacksonLaboratory/JAXBD2K-ShortCourse.

Fig 1. Participant profile of Big Genomic Data Skills Training for Professors.

Background knowledge survey on 11 subjects. The expertise on each subject was evaluated from 1 (no knowledge) to 10 (expert). The mean score of each subject is shown at the right. The respondent ratio for each subject at every score is scaled to the center of each row and shown in color (middle panel). K-means clustering was conducted on the respondent ratio and presented to the left of the score matrix.

Fig 2. Postevent survey on the satisfaction and evaluation of Big Genomic Data Skills Training for Professors.

(A) Participants’ overall satisfaction on the training program. (B) Distribution of degree of agreement on specific statements regarding the program. (C) Distribution of answers to their confidence to launch a course focused on genomics and genomics data analysis. (D) Distribution of participants’ willingness to implement our modules to their course. ChIP-Seq, chromatin immunoprecipitation sequencing; RNA-Seq, RNA sequencing.