BioPrediction Framework

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About
BioPrediction Framework addresses the challenge of extracting insights from growing biological sequence databases across sectors like health and agriculture. Given the complexity of biological sequences, this end-to-end automated Machine Learning (ML) framework detects implicit molecular interactions without needing researchers to master ML. With three primary objectives - accurate molecular interaction prediction, user-friendly ML tool development for biologists, and enhancing ML interpretability - the project aims to revolutionise research in protein interactions, metabolic mapping, and pharmacology, promising significant societal impacts.
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