Evidence map›Paper›PMID 42524850›Full record

ArticleBiochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology

Bridging the Python Training Gap for Bioscientists in Brazil: Improvements and Challenges.

Gustavo Schiavone Crestana, Ubiratan da Silva Batista, Michelli Inácio Gonçalves Funnicelli, Larissa Graciano Braga, Luíza Zuvanov, Rodolfo Bizarria, Raissa Melo de Sousa, Pedro Henrique Narciso Ferreira, Flavia Vischi Winck, Gabriel Rodrigues Alves Margarido and 3 more

Abstract read
In one paragraph

Article in Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Gustavo Schiavone CrestanaCampus Luiz de Queiroz, Department of Genetics, Genomics Group, University of São Paulo (USP), Piracicaba, São Paulo, Brazil.ORCID https://orcid.org/0000-0003-2564-1173
Ubiratan da Silva BatistaDepartment of Biological Science, Federal University of Ouro Preto (UFOP), Ouro Preto, Minas Gerais, Brazil.ORCID https://orcid.org/0000-0001-8850-9052
Michelli Inácio Gonçalves FunnicelliVector-Borne Bioagents Laboratory, Department of Pathology, Reproduction and One Health, School of Agricultural and Veterinary Sciences, São Paulo State University (UNESP), Jaboticabal, São Paulo, Brazil.ORCID https://orcid.org/0000-0002-5322-0862
Larissa Graciano BragaDepartment of Exact Sciences, School of Agricultural and Veterinary Sciences, São Paulo State University, Jaboticabal, São Paulo, Brazil.ORCID https://orcid.org/0000-0002-8374-5168
Luíza ZuvanovInstitute of Chemistry and Biochemistry, Free University of Berlin, Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0003-0132-4894
Rodolfo BizarriaInstitute of Biosciences, São Paulo State University (UNESP), Rio Claro, São Paulo, Brazil.ORCID https://orcid.org/0000-0003-4293-5886
Raissa Melo de SousaFrancisco Mauro Salzano Molecular Biology Laboratory, Institute of Biological Sciences, Federal University of Pará (UFPA), Belém, Pará, Brazil.
Pedro Henrique Narciso FerreiraDepartment of Genetics, Evolution, Microbiology, and Immunology/Laboratory of Genomics and BioEnergy (LGE), State University of Campinas, Campinas, São Paulo, Brazil.ORCID https://orcid.org/0000-0003-4483-7489
Flavia Vischi WinckLaboratório de Biologia de Sistemas Regulatórios LABIS, Centro de Energia Nuclear Na Agricultura, Universidade de São Paulo, Piracicaba, São Paulo, Brazil.ORCID https://orcid.org/0000-0002-8399-4156
Gabriel Rodrigues Alves MargaridoDepartment of Genetics, University of São Paulo (USP)-Campus Luiz de Queiroz, Piracicaba, São Paulo, Brazil.
Alessandro de Mello VaraniDepartment of Agricultural and Environmental Biotechnology, Varani's LAB, São Paulo State University (UNESP), Jaboticabal, São Paulo, Brazil.ORCID https://orcid.org/0000-0002-8876-3269
Diego Mauricio Riaño-PachónLaboratory of Computational, Evolutionary, and Systems Biology, Centro de Energia Nuclear Na Agricultura, Universidade de São Paulo, Piracicaba, São Paulo, Brazil.ORCID https://orcid.org/0000-0001-9803-3465
Renato Augusto Corrêa Dos SantosLaboratory of Computational, Evolutionary, and Systems Biology, Centro de Energia Nuclear Na Agricultura, Universidade de São Paulo, Piracicaba, São Paulo, Brazil.ORCID https://orcid.org/0000-0003-0826-5479

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid evolution of high-throughput technologies in biosciences generates vast and diverse datasets, demanding that bioscientists develop advanced data manipulation and analysis skills. Python, with its versatility and powerful libraries, has become a crucial tool for managing these datasets. However, a significant lack of programming training for bioscientists persists in many countries. To address this knowledge gap in Brazil, the Brazilian Python Workshop for Biological Data was introduced several years ago, focusing on fundamental programming concepts and data handling techniques using popular Python libraries. Despite positive feedback from earlier editions, persistent challenges necessitated continuous adaptation to meet the evolving needs of bioscientists. This work describes the advancements implemented in the 2021 and 2022 editions of the workshop and discusses suggestions for its ongoing enhancement. Key innovations were introduced in the workshop's structure and coordination, including new committees and a code of conduct. Feedback forms were updated for real-time adjustments, and the event's reach was expanded to increase geographical diversity. New didactic strategies, such as pair-teaching, code clubs, and the integration of ICTs, were implemented to enhance learning outcomes. Programming best practices and scientific reproducibility were emphasized through talks and hands-on activities guided by PEP8 conventions. Furthermore, scientific dissemination was intensified through an increased social media presence and participation in international events. Finally, we present updated recommendations for students, researchers, and educators interested in organizing similar initiatives.

Indexed as

Research PersonnelSoftwareBrazilHumansbiological dataintroductory programmingpythonworkshop

Identifiers

PMID42524850
PMCPMC13576779

What OpenQuestion holds

Textmetadata
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.