
The author explores the application of reinforcement learning in genome assembly, aiming to automate and improve accuracy. By enhancing reward systems and exploration strategies, the study seeks to optimize machine learning approaches for de novo genome assembly.


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reinforcement-learning-for-genome-assembly-study


Reinforcement Learning for Genome Assembly Study


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Applying reinforcement learning to genome assembly shows promise but faces challenges in real-world scenarios.


reinforcement-learning-approach-to-genome-assembly


Reinforcement Learning Approach to Genome Assembly
