The experience of teaching introductory programming skills to bioscientists in Brazil.


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
11 2021
Historique:
entrez: 11 11 2021
pubmed: 12 11 2021
medline: 25 11 2021
Statut: epublish

Résumé

Computational biology has gained traction as an independent scientific discipline over the last years in South America. However, there is still a growing need for bioscientists, from different backgrounds, with different levels, to acquire programming skills, which could reduce the time from data to insights and bridge communication between life scientists and computer scientists. Python is a programming language extensively used in bioinformatics and data science, which is particularly suitable for beginners. Here, we describe the conception, organization, and implementation of the Brazilian Python Workshop for Biological Data. This workshop has been organized by graduate and undergraduate students and supported, mostly in administrative matters, by experienced faculty members since 2017. The workshop was conceived for teaching bioscientists, mainly students in Brazil, on how to program in a biological context. The goal of this article was to share our experience with the 2020 edition of the workshop in its virtual format due to the Coronavirus Disease 2019 (COVID-19) pandemic and to compare and contrast this year's experience with the previous in-person editions. We described a hands-on and live coding workshop model for teaching introductory Python programming. We also highlighted the adaptations made from in-person to online format in 2020, the participants' assessment of learning progression, and general workshop management. Lastly, we provided a summary and reflections from our personal experiences from the workshops of the last 4 years. Our takeaways included the benefits of the learning from learners' feedback (LLF) that allowed us to improve the workshop in real time, in the short, and likely in the long term. We concluded that the Brazilian Python Workshop for Biological Data is a highly effective workshop model for teaching a programming language that allows bioscientists to go beyond an initial exploration of programming skills for data analysis in the medium to long term.

Identifiants

pubmed: 34762646
doi: 10.1371/journal.pcbi.1009534
pii: PCOMPBIOL-D-21-00913
pmc: PMC8584955
doi:

Types de publication

Congress Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1009534

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Références

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Auteurs

Luíza Zuvanov (L)

São Carlos Institute of Physics, University of São Paulo, São Carlos, Brazil.

Ana Letycia Basso Garcia (AL)

Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, Brazil.

Fernando Henrique Correr (FH)

Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, Brazil.

Rodolfo Bizarria (R)

Department of General and Applied Biology, São Paulo State University, Rio Claro, Brazil.
Center of the Study of Social Insects, Department of General and Applied Biology, Institute of Biosciences of Rio Claro, São Paulo State University, Rio Claro, Brazil.

Ailton Pereira da Costa Filho (APDC)

Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil.

Alisson Hayasi da Costa (AH)

Department of Computer Science, Federal University of São Carlos, São Carlos, Brazil.

Andréa T Thomaz (AT)

School of Natural Sciences, Universidad del Rosario, Bogotá, Colombia.

Ana Lucia Mendes Pinheiro (ALM)

Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, Brazil.

Diego Mauricio Riaño-Pachón (DM)

Computational, Evolutionary and Systems Biology Lab, Center for Nuclear Energy in Agriculture, University of São Paulo, Piracicaba, Brazil.

Flavia Vischi Winck (FV)

Regulatory Systems Biology Lab, Center for Nuclear Energy in Agriculture, University of São Paulo, Piracicaba, Brazil.

Franciele Grego Esteves (FG)

Center of the Study of Social Insects, Department of General and Applied Biology, Institute of Biosciences of Rio Claro, São Paulo State University, Rio Claro, Brazil.

Gabriel Rodrigues Alves Margarido (GRA)

Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, Brazil.

Giovanna Maria Stanfoca Casagrande (GMS)

Barretos Cancer Hospital, Barretos, Brazil.

Henrique Cordeiro Frajacomo (HC)

Department of Computer Science, Federal University of São Carlos, São Carlos, Brazil.

Leonardo Martins (L)

Paulista School of Medicine, Federal University of São Paulo, São Paulo, Brazil.

Mariana Feitosa Cavalheiro (MF)

Department of Genetics, Evolution, Microbiology and Immunology, Institute of Biology, University of Campinas, Campinas, Brazil.
Genomics for Climate Change Research Center, University of Campinas, Campinas, Brazil.

Nathalia Graf Grachet (NG)

Roche Sequencing Solutions, Pleasanton, California, United States of America.

Raniere Gaia Costa da Silva (RGC)

Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, Special Administrative Region, People's Republic of China.

Ricardo Cerri (R)

Department of Computer Science, Federal University of São Carlos, São Carlos, Brazil.

Rommel Thiago Juca Ramos (RTJ)

Institute of Biological Sciences, Federal University of Pará, Belém, Brazil.

Simone Daniela Sartorio de Medeiros (SDS)

Department of Informatics and Statistics, Federal University of Santa Catarina, Florianópolis, Brazil.

Thayana Vieira Tavares (TV)

Department of Genetics and Evolution, Federal University of São Carlos, São Carlos, Brazil.

Renato Augusto Corrêa Dos Santos (RA)

School of Pharmaceutical Sciences of Ribeirao Preto, University of São Paulo, Ribeirão Preto, Brazil.
Institute of Biology, State University of Campinas, Campinas, Brazil.

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