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Creators/Authors contains: "Talbot, Austin"

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  1. Advancements in computation and machine learning have revolutionized science, enabling researchers to address once insurmountable challenges. Bioinformatics, a field that heavily relies on computer-driven analysis of biological data, has greatly benefited from these developments. However, traditional bioinformatics instruction frequently lacks the necessary coding skills. This article explores the transformation of a bioinformatics course in which feedback from students revealed limitations in traditional web application interfaces and the absence of coding automated pipelines for real-world applications. To address these shortcomings, the authors redesigned the project to incorporate computer programming using Google Colaboratory, where students access databases and websites by coding. The curriculum outlined the integration of modern programming skills with essential bioinformatics concepts. This article evaluates the effectiveness of this redesign by analyzing a selfresponse survey completed by course participants. Results show a positive impact on students’ perception of science and scientific research. Bayesian statistical analysis reveals that the programming component significantly predicts students’ career clarity in science and their pursuit of graduate education. Integrating coding exercises in bioinformatics education enhances students’ preparedness for real-world applications. The freely available GitHub repository will facilitate adoption. By embracing computational tools, students can become adept researchers capable of tackling complex biological questions. 
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    Free, publicly-accessible full text available January 2, 2026