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

Title:
The experience of teaching introductory programming skills to bioscientists in Brazil.
Authors:
Zuvanov L; São Carlos Institute of Physics, University of São Paulo, São Carlos, Brazil., Basso Garcia AL; Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, Brazil., Correr FH; Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, Brazil., Bizarria R Jr; 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., Filho APDC; Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil., da Costa AH; Department of Computer Science, Federal University of São Carlos, São Carlos, Brazil., Thomaz AT; School of Natural Sciences, Universidad del Rosario, Bogotá, Colombia., Pinheiro ALM; Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, Brazil., Riaño-Pachón DM; Computational, Evolutionary and Systems Biology Lab, Center for Nuclear Energy in Agriculture, University of São Paulo, Piracicaba, Brazil., Winck FV; Regulatory Systems Biology Lab, Center for Nuclear Energy in Agriculture, University of São Paulo, Piracicaba, Brazil., 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., Margarido GRA; Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, Brazil., Casagrande GMS; Barretos Cancer Hospital, Barretos, Brazil., Frajacomo HC; Department of Computer Science, Federal University of São Carlos, São Carlos, Brazil., Martins L; Paulista School of Medicine, Federal University of São Paulo, São Paulo, Brazil., 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., Grachet NG; Roche Sequencing Solutions, Pleasanton, California, United States of America., 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., Cerri R; Department of Computer Science, Federal University of São Carlos, São Carlos, Brazil., Ramos RTJ; Institute of Biological Sciences, Federal University of Pará, Belém, Brazil., Medeiros SDS; Department of Informatics and Statistics, Federal University of Santa Catarina, Florianópolis, Brazil., Tavares TV; Department of Genetics and Evolution, Federal University of São Carlos, São Carlos, Brazil., 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.
Source:
PLoS computational biology [PLoS Comput Biol] 2021 Nov 11; Vol. 17 (11), pp. e1009534. Date of Electronic Publication: 2021 Nov 11 (Print Publication: 2021).
Publication Type:
Congress; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE
Imprint Name(s):
Original Publication: San Francisco, CA : Public Library of Science, [2005]-
MeSH Terms:
Curriculum* , Programming Languages*, Computational Biology/*education, Brazil ; COVID-19 ; Education, Distance ; Humans ; Pandemics ; Physical Distancing
References:
Bioinformatics. 2009 Jun 1;25(11):1422-3. (PMID: 19304878)
PLoS Comput Biol. 2020 Sep 10;16(9):e1008090. (PMID: 32911527)
Biochem Mol Biol Educ. 2019 May;47(3):288-295. (PMID: 30860646)
PLoS Comput Biol. 2020 Nov 5;16(11):e1008326. (PMID: 33151926)
Sci Data. 2016 Mar 15;3:160018. (PMID: 26978244)
PLoS Comput Biol. 2016 Jun 07;12(6):e1004867. (PMID: 27271528)
Brief Bioinform. 2019 Nov 27;20(6):1981-1996. (PMID: 30084940)
Data Brief. 2019 Nov 07;27:104770. (PMID: 31763416)
PLoS Comput Biol. 2020 Jul 23;16(7):e1007976. (PMID: 32702016)
Entry Date(s):
Date Created: 20211111 Date Completed: 20211124 Latest Revision: 20211124
Update Code:
20250114
PubMed Central ID:
PMC8584955
DOI:
10.1371/journal.pcbi.1009534
PMID:
34762646
Database:
MEDLINE

Weitere Informationen

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.

The authors have declared that no competing interests exist.