{ "item_title" : "Machine Learning for Protein Science and Engineering", "item_author" : [" Christian Dallago", "Peter Koo", "Kevin Yang "], "item_description" : "Machine learningtechniques are having a huge impact on how biologists study andunderstand proteins. Protein structure prediction has beenrevolutionized, and new tools are improving functional annotation ofproteins, 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 Biologyexplores the rapidly evolving intersection of machine learning andprotein science. The contributors review various approaches for learningrepresentations of proteins, as well as statistical models ofco-evolution and large-scale homology searches, which have importantimplications for protein structure prediction. In addition, they examineapplications of machine learning for functional annotation of proteinsand variant effect prediction.The collection also exploresgenerative models for protein sequence and structure and looks at theenvironmental impact of applying these tools, acknowledging the need tobalance technological advancement with sustainable computing. It istherefore an essential reference for all scientists interested in bothlearning more about these techniques and implementing them in researchinstitutions.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/1/62/182/480/1621824802_b.jpg", "price_data" : { "retail_price" : "79.00", "online_price" : "79.00", "our_price" : "79.00", "club_price" : "79.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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