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In this dissertation, I develop three novel machine learning algorithms tailored towards biological sequence data to aid in answering such biological questions.
May 14, 2021 · Recent advances in sequencing and synthesis technologies have sparked extraordinary growth in large-scale biological experimentation and ...
May 14, 2021 · In this dissertation, I develop three novel machine learning algorithms tailored towards biological sequence data to aid in answering such ...
Analyzing biological sequences help researches to explore the structural and functional properties of sequences [6, 7], disease diagnosis [8-10], drug target.
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Apr 5, 2021 · Learning biological properties from sequence data is a logical step toward generative and predictive artificial intelligence for biology.
This Special Issue aims to target the recent large-scale machine learning techniques together with biomedicine applications. Applications in medical and ...
This chapter highlights successful applications of machine learning to protein engineering and directed evolution, organized by the improvements that have been ...
The methods discussed include traditional machine learning methods, as these are still the best choices in many cases, and deep learning with artificial neural ...
Sep 22, 2023 · By uniting recent work on deep representation learning for molecules, scalable Gaussian processes, and high dimensional black-box optimization, ...
Jul 25, 2022 · In the current review, we address development and application of deep learning methods/models in different subarea of human genomics.