{"title":"人工智能驱动的生物学:重新思考实验和计算:采访牛津大学 DeepMind 人工智能教授、奥地利科学院艾思拉研究所创始科学主任迈克尔-布朗斯坦。","authors":"Thomas Lemberger","doi":"10.1038/s44319-024-00268-6","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":11541,"journal":{"name":"EMBO Reports","volume":" ","pages":"4629-4633"},"PeriodicalIF":6.5000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11549334/pdf/","citationCount":"0","resultStr":"{\"title\":\"AI-driven biology: rethinking experiments and computation : An interview with Michael Bronstein, DeepMind Professor of Artificial Intelligence at the University of Oxford and Founding Scientific Director of the Aithyra Institute of the Austrian Academy of Sciences.\",\"authors\":\"Thomas Lemberger\",\"doi\":\"10.1038/s44319-024-00268-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":11541,\"journal\":{\"name\":\"EMBO Reports\",\"volume\":\" \",\"pages\":\"4629-4633\"},\"PeriodicalIF\":6.5000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11549334/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EMBO Reports\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1038/s44319-024-00268-6\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/9/23 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EMBO Reports","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1038/s44319-024-00268-6","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/23 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
AI-driven biology: rethinking experiments and computation : An interview with Michael Bronstein, DeepMind Professor of Artificial Intelligence at the University of Oxford and Founding Scientific Director of the Aithyra Institute of the Austrian Academy of Sciences.
期刊介绍:
EMBO Reports is a scientific journal that specializes in publishing research articles in the fields of molecular biology, cell biology, and developmental biology. The journal is known for its commitment to publishing high-quality, impactful research that provides novel physiological and functional insights. These insights are expected to be supported by robust evidence, with independent lines of inquiry validating the findings.
The journal's scope includes both long and short-format papers, catering to different types of research contributions. It values studies that:
Communicate major findings: Articles that report significant discoveries or advancements in the understanding of biological processes at the molecular, cellular, and developmental levels.
Confirm important findings: Research that validates or supports existing knowledge in the field, reinforcing the reliability of previous studies.
Refute prominent claims: Studies that challenge or disprove widely accepted ideas or hypotheses in the biosciences, contributing to the correction and evolution of scientific understanding.
Present null data: Papers that report negative results or findings that do not support a particular hypothesis, which are crucial for the scientific process as they help to refine or redirect research efforts.
EMBO Reports is dedicated to maintaining high standards of scientific rigor and integrity, ensuring that the research it publishes contributes meaningfully to the advancement of knowledge in the life sciences. By covering a broad spectrum of topics and encouraging the publication of both positive and negative results, the journal plays a vital role in promoting a comprehensive and balanced view of scientific inquiry.