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Nature Biotechnology

Resumen/Descripción – provisto por la editorial en inglés
Nature Biotechnology is a monthly journal covering the science and business of biotechnology. It publishes new concepts in technology/methodology of relevance to the biological, biomedical, agricultural and environmental sciences as well as covers the commercial, political, ethical, legal, and societal aspects of this research. The first function is fulfilled by the peer-reviewed research section, the second by the expository efforts in the front of the journal. We provide researchers with news about business; we provide the business community with news about research developments.
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Institución detectada Período Navegá Descargá Solicitá
No detectada desde jul. 2012 / hasta dic. 2023 Nature.com

Información

Tipo de recurso:

revistas

ISSN impreso

1087-0156

ISSN electrónico

1546-1696

Editor responsable

Springer Nature

País de edición

Reino Unido

Fecha de publicación

Tabla de contenidos

Kirigami electronics for long-term electrophysiological recording of human neural organoids and assembloids

Xiao YangORCID; Csaba Forró; Thomas L. LiORCID; Yuki MiuraORCID; Tomasz J. Zaluska; Ching-Ting Tsai; Sabina Kanton; James P. McQueen; Xiaoyu Chen; Valentina Mollo; Francesca Santoro; Sergiu P. PașcaORCID; Bianxiao CuiORCID

Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.

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Mosaic integration and knowledge transfer of single-cell multimodal data with MIDAS

Zhen HeORCID; Shuofeng HuORCID; Yaowen ChenORCID; Sijing AnORCID; Jiahao ZhouORCID; Runyan Liu; Junfeng Shi; Jing WangORCID; Guohua Dong; Jinhui ShiORCID; Jiaxin Zhao; Le Ou-Yang; Yuan ZhuORCID; Xiaochen BoORCID; Xiaomin YingORCID

<jats:title>Abstract</jats:title><jats:p>Integrating single-cell datasets produced by multiple omics technologies is essential for defining cellular heterogeneity. Mosaic integration, in which different datasets share only some of the measured modalities, poses major challenges, particularly regarding modality alignment and batch effect removal. Here, we present a deep probabilistic framework for the mosaic integration and knowledge transfer (MIDAS) of single-cell multimodal data. MIDAS simultaneously achieves dimensionality reduction, imputation and batch correction of mosaic data by using self-supervised modality alignment and information-theoretic latent disentanglement. We demonstrate its superiority to 19 other methods and reliability by evaluating its performance in trimodal and mosaic integration tasks. We also constructed a single-cell trimodal atlas of human peripheral blood mononuclear cells and tailored transfer learning and reciprocal reference mapping schemes to enable flexible and accurate knowledge transfer from the atlas to new data. Applications in mosaic integration, pseudotime analysis and cross-tissue knowledge transfer on bone marrow mosaic datasets demonstrate the versatility and superiority of MIDAS. MIDAS is available at <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/labomics/midas">https://github.com/labomics/midas</jats:ext-link>.</jats:p>

Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.

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Slow release of a synthetic auxin induces formation of adventitious roots in recalcitrant woody plants

Ohad Roth; Sela Yechezkel; Ori Serero; Avi Eliyahu; Inna Vints; Pan Tzeela; Alberto Carignano; Dorina P. Janacek; Verena Peters; Amit KesselORCID; Vikas Dwivedi; Mira Carmeli-Weissberg; Felix Shaya; Adi Faigenboim-Doron; Kien Lam Ung; Bjørn Panyella PedersenORCID; Joseph Riov; Eric Klavins; Corinna Dawid; Ulrich Z. Hammes; Nir Ben-Tal; Richard NapierORCID; Einat Sadot; Roy WeinstainORCID

Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.

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A synthetic auxin for cloning mature trees

Catherine BelliniORCID

Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.

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Author Correction: Genotoxic effects of base and prime editing in human hematopoietic stem cells

Martina FiumaraORCID; Samuele FerrariORCID; Attya Omer-Javed; Stefano BerettaORCID; Luisa AlbanoORCID; Daniele CanaruttoORCID; Angelica Varesi; Chiara Gaddoni; Chiara Brombin; Federica Cugnata; Erika Zonari; Matteo Maria NaldiniORCID; Matteo Barcella; Bernhard Gentner; Ivan Merelli; Luigi NaldiniORCID

Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.

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Computer-based design of sensors that can monitor endogenous Ras activity

Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.

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Computationally designed sensors detect endogenous Ras activity and signaling effectors at subcellular resolution

Jason Z. ZhangORCID; William H. NguyenORCID; Nathan Greenwood; John C. RoseORCID; Shao-En Ong; Dustin J. MalyORCID; David BakerORCID

<jats:title>Abstract</jats:title><jats:p>The utility of genetically encoded biosensors for sensing the activity of signaling proteins has been hampered by a lack of strategies for matching sensor sensitivity to the physiological concentration range of the target. Here we used computational protein design to generate intracellular sensors of Ras activity (LOCKR-based Sensor for Ras activity (Ras-LOCKR-S)) and proximity labelers of the Ras signaling environment (LOCKR-based, Ras activity-dependent Proximity Labeler (Ras-LOCKR-PL)). These tools allow the detection of endogenous Ras activity and labeling of the surrounding environment at subcellular resolution. Using these sensors in human cancer cell lines, we identified Ras-interacting proteins in oncogenic EML4-Alk granules and found that Src-Associated in Mitosis 68-kDa (SAM68) protein specifically enhances Ras activity in the granules. The ability to subcellularly localize endogenous Ras activity should deepen our understanding of Ras function in health and disease and may suggest potential therapeutic strategies.</jats:p>

Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.

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The perpetual motion machine of AI-generated data and the distraction of ChatGPT as a ‘scientist’

Jennifer ListgartenORCID

Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.

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Scalable, accessible and reproducible reference genome assembly and evaluation in Galaxy

Delphine LarivièreORCID; Linelle Abueg; Nadolina Brajuka; Cristóbal Gallardo-Alba; Bjorn GrüningORCID; Byung June Ko; Alex Ostrovsky; Marc Palmada-FloresORCID; Brandon D. PickettORCID; Keon RabbaniORCID; Agostinho AntunesORCID; Jennifer R. Balacco; Mark J. P. ChaissonORCID; Haoyu Cheng; Joanna Collins; Melanie Couture; Alexandra DenisovaORCID; Olivier FedrigoORCID; Guido Roberto GalloORCID; Alice Maria GianiORCID; Grenville MacDonald Gooder; Kathleen Horan; Nivesh JainORCID; Cassidy Johnson; Heebal KimORCID; Chul Lee; Tomas Marques-BonetORCID; Brian O’Toole; Arang Rhie; Simona SecomandiORCID; Marcella Sozzoni; Tatiana TilleyORCID; Marcela Uliano-Silva; Marius van den BeekORCID; Robert W. WilliamsORCID; Robert M. WaterhouseORCID; Adam M. PhillippyORCID; Erich D. JarvisORCID; Michael C. SchatzORCID; Anton Nekrutenko; Giulio FormentiORCID

Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.

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An optimized toolkit for prime editing

Ryan M. MarksORCID; Ori Scott; Evgueni A. IvakineORCID; Ronald D. CohnORCID

Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.

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