Evidence map›Paper›PMID 29324777›Full record

ArticlePLoS computational biology2018

Assessing an effective undergraduate module teaching applied bioinformatics to biology students.

Andreas Madlung

Abstract read
In one paragraph

Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Integrating Programming into Neuroscience Courses.Journal of undergraduate neuroscience education : JUNE : a publication of FUN, Faculty for Undergraduate Neuroscience · 2024
    Article
  8. Article
  9. Article
  10. Development of a Remote, Course-Based Undergraduate Experience to FacilitateJournal of microbiology & biology education · 2022
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Andreas MadlungUniversity of Puget Sound, Department of Biology, Tacoma, Washington.ORCID 0000-0003-3563-5797

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Applied bioinformatics skills are becoming ever more indispensable for biologists, yet incorporation of these skills into the undergraduate biology curriculum is lagging behind, in part due to a lack of instructors willing and able to teach basic bioinformatics in classes that don't specifically focus on quantitative skill development, such as statistics or computer sciences. To help undergraduate course instructors who themselves did not learn bioinformatics as part of their own education and are hesitant to plunge into teaching big data analysis, a module was developed that is written in plain-enough language, using publicly available computing tools and data, to allow novice instructors to teach next-generation sequence analysis to upper-level undergraduate students. To determine if the module allowed students to develop a better understanding of and appreciation for applied bioinformatics, various tools were developed and employed to assess the impact of the module. This article describes both the module and its assessment. Students found the activity valuable for their education and, in focus group discussions, emphasized that they saw a need for more and earlier instruction of big data analysis as part of the undergraduate biology curriculum.

Indexed as

Computational BiologyCurriculumEducational MeasurementHigh-Throughput Nucleotide SequencingHumansSequence Analysis, RNAStudentsSurveys and QuestionnairesTeaching

Identifiers

PMID29324777
PMCPMC5764237

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.