he experience of teaching introductory programming skills to bioscientists in Brazi

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Zuvanov, Luiza ^[1] ; Basso Garcia, Ana Letycia ^[2] ; Correr, Fernando Henrique ^[2] ; Bizarria Jr, Rodolfo ; da Costa Filho, Ailton Pereira ^[3] ; da Costa, Alisson Hayasi ^[4] ; Thomaz, Andrea T. ^[5] ; Mendes Pinheiro, Ana Lucia ^[2] ; Riano-Pachon, Diego Mauricio ^[6] ; Winck, Flavia Vischi ^[7] ; Esteves, Franciele Grego ^[8] ; Alves Margarido, Gabriel Rodrigues ^[2] ; Stanfoca Casagrande, Giovanna Maria ^[9] ; Frajacomo, Henrique Cordeiro ^[4] ; Martins, Leonardo ^[10] ; Cavalheiro, Mariana Feitosa ^{[11, 12]} ; Grachet, Nathalia Graf ^[13] ; Costa da Silva, Raniere Gaia ^[14] ; Cerri, Ricardo ^[4] ; Juca Ramos, Rommel Thiago ^[15] ; Sartorio de Medeiros, Simone Daniela ^[16] ; Tavares, Thayana Vieira ^[17] ; Correa dos Santos, Renato Augusto ^{[18, 19]}

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^[1] Univ Sao Paulo, Sao Carlos Inst Phys, Sao Carlos - Brazil

^[2] Univ Sao Paulo, Luiz de Queiroz Coll Agr, Dept Genet, Piracicaba - Brazil

^[3] Univ Sao Paulo, Ribeirao Preto Med Sch, Ribeirao Preto - Brazil

^[4] Univ Fed Sao Carlos, Dept Comp Sci, Sao Carlos - Brazil

^[5] Univ Rosario, Sch Nat Sci, Bogota - Colombia

^[6] Univ Sao Paulo, Ctr Nucl Energy Agr, Computat Evolutionary & Syst Biol Lab, Piracicaba - Brazil

^[7] Univ Sao Paulo, Ctr Nucl Energy Agr, Regulatory Syst Biol Lab, Piracicaba - Brazil

^[8] Bizarria Jr, Jr., Rodolfo, Sao Paulo State Univ, Ctr Study Social Insects, Inst Biosci Rio Claro, Dept Gen & Appl Biol, Rio Claro - Brazil

^[9] Barretos Canc Hosp, Barretos - Brazil

^[10] Univ Fed Sao Paulo, Paulista Sch Med, Sao Paulo - Brazil

^[11] Univ Estadual Campinas, Inst Biol, Dept Genet Evolut Microbiol & Immunol, Campinas - Brazil

^[12] Univ Estadual Campinas, Genom Climate Change Res Ctr, Campinas - Brazil

^[13] Roche Sequencing Solut, Pleasanton, CA - USA

^[14] City Univ Hong Kong, Jockey Club Coll Vet Med & Life Sci, Dept Infect Dis & Publ Hlth, Hong Kong - Peoples R China

^[15] Fed Univ Para, Inst Biol Sci, Belem, Para - Brazil

^[16] Univ Fed Santa Catarina, Dept Informat & Stat, Florianopolis, SC - Brazil

^[17] Univ Fed Sao Carlos, Dept Genet & Evolut, Sao Carlos - Brazil

^[18] Univ Sao Paulo, Sch Pharmaceut Sci Ribeirao Preto, Ribeirao Preto - Brazil

^[19] Univ Estadual Campinas, Inst Biol, Campinas - Brazil

• Tipo de documento: Artigo Científico
• Fonte: PLOS COMPUTATIONAL BIOLOGY; v. 17, n. 11 NOV 2021.
• Citações Web of Science: 0

Resumo

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. (AU)

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