NIBLSE Newsletter

July 2018

Greetings from NIBLSE!

NIBLSE is an NSF-funded Research Coordination Network that facilitates the integration of bioinformatics into life science curricula. The NIBLSE network currently has 80 formal members representing a diverse set of higher education institutions. The network has established infrastructure and resources to support integration of bioinformatics exercises, modules and courses. We seek to expand our membership and support faculty who share our mission and goals.

The NIBLSE Mission

The long-term goal of NIBLSE is to achieve the full integration of bioinformatics into undergraduate life sciences education. Specific activities are:

  1. Establish a permanent network of investigators.
  2. Collaboratively identify, vet, and refine a set of bioinformatics core competencies.
  3. Identify and vet assessment tools.
  4. Organize and simplify the dissemination of materials.


Core Competencies & Resource Collection

Core Competencies

We proudly announce that NIBLSE has established a set of bioinformatics core competencies. A publication describing these core competencies was recently published in PLOS ONE.

Figure 5 from PLOS paper

NIBLSE Core Competency Highlight

In each of our newsletters we will highlight a NIBLSE core competency. All nine competencies can be found on the NIBLSE Website. Our first highlight will feature Core Competency 1 (C1).

Modern biology is inextricably linked to computation. Large datasets are the norm and computational analysis is routine. One exciting outcome of this relationship is the role of computation in hypothesis generation. In life science research, bioinformatics is a two way street; it answers questions posed by bench and field scientists and it reveals questions that direct bench and field scientist’s investigations. Therefore, life science students must become familiar with computation and data mining

C1. Explain the role of computation and data mining in addressing hypothesis-driven and hypothesis-generating questions within the life sciences.

Life sciences students should have a clear understanding of the role computing and data mining play in modern biology. Given a traditional hypothesis-driven research question, students should have ideas about what types of data and software exist that could help them answer the question quickly and efficiently. They should also appreciate that mining large datasets can generate novel hypotheses to be tested in the lab or field.

  • Compare and contrast computer-based research with wet-lab research.
  • Explain the role of computation in finding genes, detecting the function of protein domains, and inferring protein function.
  • Describe the role of various databases in identifying potential gene targets for drug development


NIBLSE Resource Collection

One of NIBLSE most important accomplishments is vetting and disseminating bioinformatics education resources. NIBLSE has partnered with QUBES to make a Resource Collection available to any interested educator. Using a unique incubator model, the Resources Review Committee (RRC) has worked with authors to develop resources that are ready for integration into courses. The RRC is actively seeking new resources and actively incubating submitted resources. Please contact Bill Morgan ( if you are interested in participating in an incubator or if you have a resource to submit.

NIBLSE Resource Collection Highlight

NIBLSE Learning Resources

In each of our newsletters we will highlight an educational resource available in the Resource Collection. Our first resource highlight will feature an exercise that explores bioinformatics concepts and tools developed by Adam Kleinschmit from Adams State University called Bioinformatics-Investigating Sequence Similarity. It is an exercise that utilizes simple paper models to help students understand matrices and algorithms prior to use of web-based computational tools. The exercise specifically addresses Core Competencies C2 (Computational Concepts), C4 (Bioinformatics Tools), C5 (Retrieve Data) and C8 (Data Types).

vase and phylogenetic tree