Teaching the ABCs of bioinformatics: a brief introduction to the Applied Bioinformatics Course

E-learning strategies from a bioinformatics postgraduate programme to improve student engagement and completion rate

Motivation

E-learning is the standard solution adopted in transnational study programmes for which multiple face-to-face learning places are not an option. Bioinformatics is compatible with e-learning because its resource requirements are low. Online learning, however, is usually associated with high dropout rates because students start from a very low computational level and/or they need support to conduct practical analyses on their own.

Results

In this article, we analyse the academic results of an online bioinformatics educational programme based on learning communities. The programme has been offered by the Spanish Pablo de Olavide University for more than 5 years with a completion rate of close to 90%. Learning bioinformatics requires technical and operational competencies that can only be acquired through a practical methodology. We have thus developed a student-centred and problem-based constructivist learning model; the model uses faculty and peer mentoring to drive individual work and retain students. Regarding our innovative learning model, the recruitment level (i.e. the number of applicants per available places and international origin), the results obtained (i.e. the retention index and learning outcomes) as well as the satisfaction index expressed by students and faculty lead us to regard this programme as a successful strategy for online graduate learning in bioinformatics.

Availability and implementation

All data and results for this article are available in the figures and supplementary files. The current syllabus (Supplementary File S7) and other details of the course are available at: https://www.upo.es/postgrado/Diploma-de-Especializacion-Analisis-Bioinformatico and https://www.upo.es/postgrado/Master-Analisis-Bioinformatico-Avanzado.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Blending Gagne's Instructional Model with Peyton's Approach to Design an Introductory Bioinformatics Lesson Plan for Medical Students: Proof-of-Concept Study

BACKGROUND

With the rapid integration of genetics into medicine, it has become evident that practicing physicians as well as medical students and clinical researchers need to be updated on the fundamentals of bioinformatics. To achieve this, the following gaps need to be addressed: a lack of defined learning objectives for "Bioinformatics for Medical Practitioner" courses, an absence of a structured lesson plan to disseminate the learning objectives, and no defined step-by-step strategy to teach the essentials of bioinformatics in the medical curriculum.

OBJECTIVE

The objective of this study was to address these gaps to design a streamlined pedagogical strategy for teaching basics of bioinformatics in the undergraduate medical curriculum.

METHODS

The established instructional design strategies employed in medical education-Gagne's 9 events of instruction-were followed with further contributions from Peyton's four-step approach to design a structured lesson plan in bioinformatics.

RESULTS

First, we defined the specifics of bioinformatics that a medical student or health care professional should be introduced to use this knowledge in a clinical context. Second, we designed a structured lesson plan using a blended approach from both Gagne's and Peyton's instructional models. Lastly, we delineated a step-by-step strategy employing free Web-based bioinformatics module, combining it with a clinical scenario of familial hypercholesterolemia to disseminate the defined specifics of bioinformatics. Implementation of Schon's reflective practice model indicated that the activity was stimulating for the students with favorable outcomes regarding their basic training in bioinformatics.

CONCLUSIONS

To the best of our knowledge, the present lesson plan is the first that outlines an effective dissemination strategy for integrating introductory bioinformatics into a medical curriculum. Further, the lesson plan blueprint can be used to develop similar skills in workshops, continuing professional development, or continuing medical education events to introduce bioinformatics to practicing physicians.

The Topology Prediction of Membrane Proteins: A Web-Based Tutorial

There is a great need for development of educational materials on the transfer of current bioinformatics knowledge to undergraduate students in bioscience departments. In this study, it is aimed to prepare an example in silico laboratory tutorial on the topology prediction of membrane proteins by bioinformatics tools. This laboratory tutorial is prepared for biochemistry lessons at bioscience departments (biology, chemistry, biochemistry, molecular biology and genetics, and faculty of medicine). The tutorial is intended for students who have not taken a bioinformatics course yet or already have taken a course as an introduction to bioinformatics. The tutorial is based on step-by-step explanations with illustrations. It can be applied under supervision of an instructor in the lessons, or it can be used as a self-study guide by students. In the tutorial, membrane-spanning regions and α-helices of membrane proteins were predicted by internet-based bioinformatics tools. According to the results achieved from internet-based bioinformatics tools, the algorithms and parameters used were effective on the accuracy of prediction. The importance of this laboratory tutorial lies on the facts that it provides an introduction to the bioinformatics and that it also demonstrates an in silico laboratory application to the students at natural sciences. The presented example education material is applicable easily at all departments that have internet connection. This study presents an alternative education material to the students in biochemistry laboratories in addition to classical laboratory experiments.

A survey of scholarly literature describing the field of bioinformatics education and bioinformatics educational research

Bioinformatics education can be broadly defined as the teaching and learning of the use of computer and information technology, along with mathematical and statistical analysis for gathering, storing, analyzing, interpreting, and integrating data to solve biological problems. The recent surge of genomics, proteomics, and structural biology in the potential advancement of research and development in complex biomedical systems has created a need for an educated workforce in bioinformatics. However, effectively integrating bioinformatics education through formal and informal educational settings has been a challenge due in part to its cross-disciplinary nature. In this article, we seek to provide an overview of the state of bioinformatics education. This article identifies: 1) current approaches of bioinformatics education at the undergraduate and graduate levels; 2) the most common concepts and skills being taught in bioinformatics education; 3) pedagogical approaches and methods of delivery for conveying bioinformatics concepts and skills; and 4) assessment results on the impact of these programs, approaches, and methods in students' attitudes or learning. Based on these findings, it is our goal to describe the landscape of scholarly work in this area and, as a result, identify opportunities and challenges in bioinformatics education.