{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T20:24:16Z","timestamp":1793046256557,"version":"4.5.0"},"reference-count":70,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2024,3,6]],"date-time":"2024-03-06T00:00:00Z","timestamp":1709683200000},"content-version":"vor","delay-in-days":44,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62002111"],"award-info":[{"award-number":["62002111"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62372158"],"award-info":[{"award-number":["62372158"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Antimicrobial peptides (AMPs), short peptides with diverse functions, effectively target and combat various organisms. The widespread misuse of chemical antibiotics has led to increasing microbial resistance. Due to their low drug resistance and toxicity, AMPs are considered promising substitutes for traditional antibiotics. While existing deep learning technology enhances AMP generation, it also presents certain challenges. Firstly, AMP generation overlooks the complex interdependencies among amino acids. Secondly, current models fail to integrate crucial tasks like screening, attribute prediction and iterative optimization. Consequently, we develop a integrated deep learning framework, Diff-AMP, that automates AMP generation, identification, attribute prediction and iterative optimization. We innovatively integrate kinetic diffusion and attention mechanisms into the reinforcement learning framework for efficient AMP generation. Additionally, our prediction module incorporates pre-training and transfer learning strategies for precise AMP identification and screening. We employ a convolutional neural network for multi-attribute prediction and a reinforcement learning-based iterative optimization strategy to produce diverse AMPs. This framework automates molecule generation, screening, attribute prediction and optimization, thereby advancing AMP research. We have also deployed Diff-AMP on a web server, with code, data and server details available in the Data Availability section.<\/jats:p>","DOI":"10.1093\/bib\/bbae078","type":"journal-article","created":{"date-parts":[[2024,2,19]],"date-time":"2024-02-19T08:52:27Z","timestamp":1708332747000},"source":"Crossref","is-referenced-by-count":91,"title":["Diff-AMP: tailored designed antimicrobial peptide framework with all-in-one generation, identification, prediction and optimization"],"prefix":"10.1093","volume":"25","author":[{"given":"Rui","family":"Wang","sequence":"first","affiliation":[{"name":"School of Data Science and Artificial Intelligence, Wenzhou University of Technology , 325000 Wenzhou , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Data Science and Artificial Intelligence, Wenzhou University of Technology , 325000 Wenzhou , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linlin","family":"Zhuo","sequence":"additional","affiliation":[{"name":"School of Data Science and Artificial Intelligence, Wenzhou University of Technology , 325000 Wenzhou , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinhang","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Data Science and Artificial Intelligence, Wenzhou University of Technology , 325000 Wenzhou , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangzheng","family":"Fu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University , 410012 Changsha , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quan","family":"Zou","sequence":"additional","affiliation":[{"name":"Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China , 611730 Chengdu , 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