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Winck, F. V.

Publications and source records attributed to Winck, F. V..

2 recordsLinked to original sources

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

The rapid evolution of high-throughput technologies in biosciences has generated diverse and voluminous datasets, requiring bioscientists to develop data manipulation and analysis skills. Python, known for its versatility and powerful libraries, has become a crucial tool for managing these datasets. However, there is a significant lack of programming training for bioscientists in many countries. To address this knowledge gap among scientists in Brazil, the Brazilian Python Workshop for Biological Data was introduced several years ago, focusing on basic programming concepts and data handling techniques using popular Python libraries. Despite the progress and positive feedback from earlier editions, challenges persisted, necessitating continuous adaptation and improvement to meet the evolving needs of bioscientists.This work describes the advancements made in the 2021 and 2022 editions of the workshop and discusses new suggestions for its ongoing enhancement. Key innovations were introduced in the workshop structure and coordination, including the creation of new committees and the establishment of a code of conduct. Feedback forms were updated to enable real-time adjustments during the event, improving its overall effectiveness. The workshop also expanded its reach by increasing geographical diversity among participants. New didactic strategies, such as pair-teaching, code clubs, and the integration of information and communication technologies (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, efforts to enhance scientific dissemination were intensified, with an increased presence on social media and participation in international scientific events and communication networks. Finally, we present updated recommendations for students, researchers, and educators interested in organizing and promoting similar events, building on those previously described.

scientific communication and education↗

PhycoMine: A Microalgae Data Warehouse

PhycoMine is data warehouse system created to fostering the analysis of complex and integrated data from microalgae species in a single computational environment. The PhycoMine was developed on top of the InterMine software system, and it has implemented an extended database model, containing a series of tools that help the users in the analysis and mining of individual data and group data. The platform has widgets created to facilitate simultaneous data mining of different datasets. Among the widgets implemented in PhycoMine, there are options for mining chromosome distribution, gene expression variation via transcriptomics, proteomics sets, Gene Onthology enrichment, KEGG enrichment, publication enrichment, EggNOG, Transcription factors and transcriptional regulators enrichment and phenotypical data. These widgets were created to facilitate data visualization of the gene expression levels in different experimental setups, for which RNA-seq experimental data is available in data repositories. For comparative purposes, we have reanalyzed 200 RNA-seq datasets from Chlamydomonas reinhardtii, a model unicellular microalga, for optimizing the performance and accuracy of data comparisons. We have also implemented widgets for metabolic pathway analysis of selected genes and proteins and options for biological network analysis. The option for analysis of orthologue genes was also included. With this platform, the users can perform data mining for a list of genes or proteins of interest in an integrated way through accessing the data from different sources and visualizing them in graphics and by exporting the data into table formats. The PhycoMine platform is freely available and can be visited through the URL https://PhycoMine.iq.usp.br.

systems biology↗