Evidence map›Paper›PMID 25790483›Full record

ArticlePLoS computational biology2015

Integrating interactive computational modeling in biology curricula.

Tomáš Helikar, Christine E Cutucache, Lauren M Dahlquist, Tyler A Herek, Joshua J Larson, Jim A Rogers

Abstract read
In one paragraph

Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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  5. Review
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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

6 authors.

Tomáš HelikarDepartment of Biochemistry, University of Nebraska-Lincoln, Lincoln, Nebraska, United States of America.
Christine E CutucacheDepartment of Biology, University of Nebraska-Omaha, Omaha, Nebraska, United States of America.
Lauren M DahlquistDepartment of Biology, University of Nebraska-Omaha, Omaha, Nebraska, United States of America.
Tyler A HerekDepartment of Biology, University of Nebraska-Omaha, Omaha, Nebraska, United States of America.
Joshua J LarsonDepartment of Biology, University of Nebraska-Omaha, Omaha, Nebraska, United States of America.
Jim A RogersDepartment of Mathematics, University of Nebraska-Omaha, Omaha, Nebraska, United States of America.

Funding

Transcriptional Regulation, the Nuclear Proteome, and HIV/Meth/cART: From ProfiliR01DA030962 · NIDA · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI CIBOROWSKI, PAWEL S, FOX, HOWARD S · 2010 to 2014
$3.1M
NIDA NIH HHS 5R01DA030962NIDA NIH HHS R01 DA030962
6 · The paper itself

Abstract

While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

Indexed as

Computer SimulationCurriculumModels, ImmunologicalSoftwareBiologyComputational BiologyHumans

Identifiers

PMID25790483
PMCPMC4366374

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.