Bioinformatics core competencies for undergraduate life sciences education

Abstract

Although bioinformatics is becoming increasingly central to research in the life sciences, bioinformatics skills and knowledge are not well integrated into undergraduate biology education. This curricular gap prevents biology students from harnessing the full potential of their education, limiting their career opportunities and slowing research innovation. To advance the integration of bioinformatics into life sciences education, a framework of core bioinformatics competencies is needed. To that end, we here report the results of a survey of biology faculty in the United States about teaching bioinformatics to undergraduate life scientists. Responses were received from 1,260 faculty representing institutions in all fifty states with a combined capacity to educate hundreds of thousands of students every year. Results indicate strong, widespread agreement that bioinformatics knowledge and skills are critical for undergraduate life scientists as well as considerable agreement about which skills are necessary. Perceptions of the importance of some skills varied with the respondent’s degree of training, time since degree earned, and/or the Carnegie Classification of the respondent’s institution. To assess which skills are currently being taught, we analyzed syllabi of courses with bioinformatics content submitted by survey respondents. Finally, we used the survey results, the analysis of the syllabi, and our collective research and teaching expertise to develop a set of bioinformatics core competencies for undergraduate biology students. These core competencies are intended to serve as a guide for institutions as they work to integrate bioinformatics into their life sciences curricula.

Barriers to integration of bioinformatics into undergraduate life sciences education: A national study of US life sciences faculty uncover significant barriers to integrating bioinformatics into undergraduate instruction

“…(Example responses are provided in S1 Responses) The number of answers that were judged to refer to these key concepts were counted, and the counts were analyzed with respect to other data collected in the survey (see Materials and Methods). Given the number of valid responses to the survey-1,231; 1% to 2% of all US biological sciences faculty [12]-our findings provide a national consensus view. Below we discuss the major barriers uncovered and then describe efforts we and others are taking to address them.…”

“…All members of the working group have extensive experience teaching bioinformatics to undergraduate biology students. Development and deployment of the survey is discussed in more detail by Sayres et al [12]; the survey in its entirety is provided there as a supplementary document. Approval for the study was obtained from the University of Nebraska at Omaha Institutional Review Board (IRB # 161-16-EX) before the survey was distributed.…”

“…As described by Sayres et al [12], the survey was e-mailed to the more than 11,000 addresses in a mailing list of US biology faculty purchased from MDR (http://schooldata.com) and to members of networks of faculty with interests in life sciences education. Given 75,000 to 100,000 biological sciences faculty in the United States [12] and the total number of responses (1% to 2%), we estimate that the mean margin of error for the survey questions described in this paper is ± 3% at the 95% confidence interval [43]. For the results described here, we analyzed barriers to teaching bioinformatics through four free-response questions ( Table 1).…”

The why, when, and how of computing in biology classrooms

“…Biology departments are increasingly offering or considering course work that incorporates hands-on computation (Wilson Sayres et al, 2018). There are different rationales for courses that include computation.…”

“…Perhaps the most obvious rationale is to teach computational biology, bioinformatics, and/or skills in working with large datasets. Bioinformatic skills are increasingly a core component of biology and biology education, and support students' job and/or graduate school preparation (Wilson Sayres et al, 2018). The vast majority of researchers in biology either use large datasets or could do so with sufficient training, suggesting that general training in effective use of large datasets is essential for students as well (Barone et al, 2017;Loman & Watson, 2013).…”