Evidence map›Paper›PMID 39264874›Full record

ArticlePLoS computational biology2024

Design and implementation of an asynchronous online course-based undergraduate research experience (CURE) in computational genomics.

Seema B Plaisier, Danielle O Alarid, Joelle A Denning, Sara E Brownell, Kenneth H Buetow, Katelyn M Cooper, Melissa A Wilson

Abstract read
In one paragraph

Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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

7 authors.

Seema B PlaisierSchool of Life Sciences, Arizona State University, Tempe, Arizona, United States of America.ORCID 0000-0002-9093-8400
Danielle O AlaridSchool of Life Sciences, Arizona State University, Tempe, Arizona, United States of America.
Joelle A DenningSchool of Life Sciences, Arizona State University, Tempe, Arizona, United States of America.ORCID 0009-0005-3130-161X
Sara E BrownellSchool of Life Sciences, Arizona State University, Tempe, Arizona, United States of America.
Kenneth H BuetowSchool of Life Sciences, Arizona State University, Tempe, Arizona, United States of America.
Katelyn M CooperSchool of Life Sciences, Arizona State University, Tempe, Arizona, United States of America.
Melissa A WilsonSchool of Life Sciences, Arizona State University, Tempe, Arizona, United States of America.ORCID 0000-0002-2614-0285

Funding

Population dynamics and medical consequences of sex chromosome evolutionR35GM124827 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI WILSON, MELISSA A · 2017 to 2024
$2.7M
NIGMS NIH HHS R35 GM124827
6 · The paper itself

Abstract

As genomics technologies advance, there is a growing demand for computational biologists trained for genomics analysis but instructors face significant hurdles in providing formal training in computer programming, statistics, and genomics to biology students. Fully online learners represent a significant and growing community that can contribute to meet this need, but they are frequently excluded from valuable research opportunities which mostly do not offer the flexibility they need. To address these opportunity gaps, we developed an asynchronous course-based undergraduate research experience (CURE) for computational genomics specifically for fully online biology students. We generated custom learning materials and leveraged remotely accessible computational tools to address 2 novel research questions over 2 iterations of the genomics CURE, one testing bioinformatics approaches and one mining cancer genomics data. Here, we present how the instructional team distributed analysis needed to address these questions between students over a 7.5-week CURE and provided concurrent training in biology and statistics, computer programming, and professional development. Scores from identical learning assessments administered before and after completion of each CURE showed significant learning gains across biology and coding course objectives. Open-response progress reports were submitted weekly and identified self-reported adaptive coping strategies for challenges encountered throughout the course. Progress reports identified problems that could be resolved through collaboration with instructors and peers via messaging platforms and virtual meetings. We implemented asynchronous communication using the Slack messaging platform and an asynchronous journal club where students discussed relevant publications using the Perusall social annotation platform. The online genomics CURE resulted in unanticipated positive outcomes, including students voluntarily discussing plans to continue research after the course. These outcomes underscore the effectiveness of this genomics CURE for scientific training, recruitment and student-mentor relationships, and student successes. Asynchronous genomics CUREs can contribute to a more skilled, diverse, and inclusive workforce for the advancement of biomedical science.

Indexed as

Computational BiologyGenomicsCurriculumEducation, DistanceHumansInternetStudentsUniversities

Identifiers

PMID39264874
PMCPMC11392228

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.