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.
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Hardcover. Etat : 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. N° de réf. du vendeur 9781621824800
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