Synopsis
Tremendous advances in machine learning are enabling scientists to make computational predictions about numerous biological phenomena. The volume will examine how machine learning is being used to help understand the structure and function of proteins.
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Machine Learning for Protein Science and Engineering
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Cold Spring Harbor Laboratory Pr, 2025
ISBN 10: 1621824802
ISBN 13: 9781621824800
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Machine Learning for Protein Science and Engineering
Published by
Cold Spring Harbor Laboratory Press, 2025
ISBN 10: 1621824802
ISBN 13: 9781621824800
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Machine Learning for Protein Science and Engineering
Published by
Cold Spring Harbor Laboratory Press, 2025
ISBN 10: 1621824802
ISBN 13: 9781621824800
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Machine Learning for Protein Science and Engineering
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Cold Spring Harbor Laboratory Press, 2025
ISBN 10: 1621824802
ISBN 13: 9781621824800
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Machine Learning for Protein Science and Engineering
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Cold Spring Harbor Laboratory Press, 2025
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ISBN 13: 9781621824800
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Machine Learning for Protein Science and Engineering
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Cold Spring Harbor Laboratory Press, 2025
ISBN 10: 1621824802
ISBN 13: 9781621824800
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Machine Learning for Protein Science and Engineering
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ISBN 10: 1621824802
ISBN 13: 9781621824800
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Machine Learning for Protein Science and Engineering (Hardcover)
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ISBN 10: 1621824802
ISBN 13: 9781621824800
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Hardcover. Condition: new. Hardcover. Machine learning techniques are having a huge impact on how biologists study and understand proteins. Protein structure prediction has been revolutionized, and new tools are improving functional annotation of proteins, as well as opening up new possibilities for protein design. Written and edited by experts in the field, this collection from Cold Spring Harbor Perspectives in Biology explores the rapidly evolving intersection of machine learning and protein science. The contributors review various approaches for learning representations of proteins, as well as statistical models of co-evolution and large-scale homology searches, which have important implications for protein structure prediction. In addition, they examine applications of machine learning for functional annotation of proteins and variant effect prediction. The collection also explores generative models for protein sequence and structure and looks at the environmental impact of applying these tools, acknowledging the need to balance technological advancement with sustainable computing. It is therefore an essential reference for all scientists interested in both learning more about these techniques and implementing them in research institutions. "Tremendous advances in machine learning are enabling scientists to make computational predictions about numerous biological phenomena. The volume will examine how machine learning is being used to help understand the structure and function of proteins"-- This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781621824800
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Machine Learning for Protein Science and Engineering
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Machine Learning for Protein Science and Engineering
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