{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:33:43Z","timestamp":1772138023921,"version":"3.50.1"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2024,5,3]],"date-time":"2024-05-03T00:00:00Z","timestamp":1714694400000},"content-version":"vor","delay-in-days":37,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["XDB38050200"],"award-info":[{"award-number":["XDB38050200"]}]},{"name":"R&D Program of Guangzhou Laboratory","award":["SRPG22\u2013001"],"award-info":[{"award-number":["SRPG22\u2013001"]}]},{"name":"R&D Program of Guangzhou Laboratory","award":["SRPG22\u2013007"],"award-info":[{"award-number":["SRPG22\u2013007"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,3,27]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The relationship between genotype and fitness is fundamental to evolution, but quantitatively mapping genotypes to fitness has remained challenging. We propose the Phenotypic-Embedding theorem (P-E theorem) that bridges genotype\u2013phenotype through an encoder\u2013decoder deep learning framework. Inspired by this, we proposed a more general first principle for correlating genotype\u2013phenotype, and the P-E theorem provides a computable basis for the application of first principle. As an application example of the P-E theorem, we developed the Co-attention based Transformer model to bridge Genotype and Fitness model, a Transformer-based pre-train foundation model with downstream supervised fine-tuning that can accurately simulate the neutral evolution of viruses and predict immune escape mutations. Accordingly, following the calculation path of the P-E theorem, we accurately obtained the basic reproduction number (${R}_0$) of SARS-CoV-2 from first principles, quantitatively linked immune escape to viral fitness and plotted the genotype-fitness landscape. The theoretical system we established provides a general and interpretable method to construct genotype\u2013phenotype landscapes, providing a new paradigm for studying theoretical and computational biology.<\/jats:p>","DOI":"10.1093\/bib\/bbae191","type":"journal-article","created":{"date-parts":[[2024,4,10]],"date-time":"2024-04-10T02:22:31Z","timestamp":1712715751000},"source":"Crossref","is-referenced-by-count":3,"title":["Genotypic\u2013phenotypic landscape computation based on first principle and deep learning"],"prefix":"10.1093","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-0856-1869","authenticated-orcid":false,"given":"Yuexing","family":"Liu","sequence":"first","affiliation":[{"name":"Guangzhou Laboratory , Guangzhou, Guangdong Province 510005 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yao","family":"Luo","sequence":"additional","affiliation":[{"name":"National University of Singapore , 21 Lower Kent Ridge Road, 119077 , Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Lu","sequence":"additional","affiliation":[{"name":"Guangzhou Laboratory , Guangzhou, Guangdong Province 510005 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Gao","sequence":"additional","affiliation":[{"name":"Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences , Shanghai 200030 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruikun","family":"He","sequence":"additional","affiliation":[{"name":"Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences , Shanghai 200030 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences , Shanghai 200030 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuguang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Mengniu Institute of Nutrition Science , Shanghai 200126 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yixue","family":"Li","sequence":"additional","affiliation":[{"name":"Guangzhou Laboratory , Guangzhou, Guangdong Province 510005 , China"},{"name":"Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences , Shanghai 200030 , China"},{"name":"GZMU-GIBH Joint School of Life Sciences , The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, , Guangzhou 511436 , China"},{"name":"Guangzhou Medical University , The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, , Guangzhou 511436 , China"},{"name":"Key Laboratory of Systems Health Science of Zhejiang Province , School of Life Science, Hangzhou Institute for Advanced Study, , Hangzhou 310024 , China"},{"name":"University of Chinese Academy of Sciences , School of Life Science, Hangzhou Institute for Advanced Study, , Hangzhou 310024 , China"},{"name":"School of Life Sciences and Biotechnology, Shanghai Jiao Tong University , Shanghai 200240 , China"},{"name":"Collaborative Innovation Center for Genetics and Development, Fudan University , Shanghai 200433 , China"},{"name":"Shanghai Institute for Biomedical and Pharmaceutical Technologies , Shanghai 200032 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2024,5,2]]},"reference":[{"key":"2024050310260747200_ref1","doi-asserted-by":"crossref","first-page":"eabc8511","DOI":"10.1126\/science.abc8511","article-title":"Deep immune profiling of COVID-19 patients reveals distinct immunotypes with therapeutic 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