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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.Palabras clave – provistas por la editorial
No disponibles.
Disponibilidad
| 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
1996-
Cobertura temática
Tabla de contenidos
Personalized medicine is having its day
Caroline Seydel
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
SEACells infers transcriptional and epigenomic cellular states from single-cell genomics data
Sitara Persad; Zi-Ning Choo; Christine Dien; Noor Sohail; Ignas Masilionis; Ronan Chaligné; Tal Nawy
; Chrysothemis C. Brown; Roshan Sharma; Itsik Pe’er; Manu Setty; Dana Pe’er
<jats:title>Abstract</jats:title><jats:p>Metacells are cell groupings derived from single-cell sequencing data that represent highly granular, distinct cell states. Here we present single-cell aggregation of cell states (SEACells), an algorithm for identifying metacells that overcome the sparsity of single-cell data while retaining heterogeneity obscured by traditional cell clustering. SEACells outperforms existing algorithms in identifying comprehensive, compact and well-separated metacells in both RNA and assay for transposase-accessible chromatin (ATAC) modalities across datasets with discrete cell types and continuous trajectories. We demonstrate the use of SEACells to improve gene–peak associations, compute ATAC gene scores and infer the activities of critical regulators during differentiation. Metacell-level analysis scales to large datasets and is particularly well suited for patient cohorts, where per-patient aggregation provides more robust units for data integration. We use our metacells to reveal expression dynamics and gradual reconfiguration of the chromatin landscape during hematopoietic differentiation and to uniquely identify CD4 T cell differentiation and activation states associated with disease onset and severity in a Coronavirus Disease 2019 (COVID-19) patient cohort.</jats:p>
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
Quantification of absolute transcription factor binding affinities in the native chromatin context using BANC-seq
Hannah K. Neikes; Katarzyna W. Kliza; Cathrin Gräwe; Roelof A. Wester; Pascal W. T. C. Jansen; Lieke A. Lamers; Marijke P. Baltissen; Simon J. van Heeringen; Colin Logie; Sarah A. Teichmann; Rik G. H. Lindeboom; Michiel Vermeulen
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
Measuring the impact of chromatin context on transcription factor binding affinities
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
Make science disruptive again
Itai Yanai; Martin J. Lercher
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
Targeted DNA integration in human cells without double-strand breaks using CRISPR-associated transposases
George D. Lampe; Rebeca T. King; Tyler S. Halpin-Healy; Sanne E. Klompe; Marcus I. Hogan; Phuc Leo H. Vo; Stephen Tang; Alejandro Chavez; Samuel H. Sternberg
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
Imaging the biological microcosmos with a tiny telescope
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
Precision financing
Melanie Senior
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
Epicardioid single-cell genomics uncovers principles of human epicardium biology in heart development and disease
Anna B. Meier; Dorota Zawada; Maria Teresa De Angelis; Laura D. Martens; Gianluca Santamaria; Sophie Zengerle; Monika Nowak-Imialek; Jessica Kornherr; Fangfang Zhang; Qinghai Tian; Cordula M. Wolf; Christian Kupatt; Makoto Sahara; Peter Lipp; Fabian J. Theis; Julien Gagneur; Alexander Goedel; Karl-Ludwig Laugwitz; Tatjana Dorn; Alessandra Moretti
<jats:title>Abstract</jats:title><jats:p>The epicardium, the mesothelial envelope of the vertebrate heart, is the source of multiple cardiac cell lineages during embryonic development and provides signals that are essential to myocardial growth and repair. Here we generate self-organizing human pluripotent stem cell-derived epicardioids that display retinoic acid-dependent morphological, molecular and functional patterning of the epicardium and myocardium typical of the left ventricular wall. By combining lineage tracing, single-cell transcriptomics and chromatin accessibility profiling, we describe the specification and differentiation process of different cell lineages in epicardioids and draw comparisons to human fetal development at the transcriptional and morphological levels. We then use epicardioids to investigate the functional cross-talk between cardiac cell types, gaining new insights into the role of IGF2/IGF1R and NRP2 signaling in human cardiogenesis. Finally, we show that epicardioids mimic the multicellular pathogenesis of congenital or stress-induced hypertrophy and fibrotic remodeling. As such, epicardioids offer a unique testing ground of epicardial activity in heart development, disease and regeneration.</jats:p>
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
A relay velocity model infers cell-dependent RNA velocity
Shengyu Li; Pengzhi Zhang; Weiqing Chen; Lingqun Ye; Kristopher W. Brannan; Nhat-Tu Le; Jun-ichi Abe; John P. Cooke; Guangyu Wang
<jats:title>Abstract</jats:title><jats:p>RNA velocity provides an approach for inferring cellular state transitions from single-cell RNA sequencing (scRNA-seq) data. Conventional RNA velocity models infer universal kinetics from all cells in an scRNA-seq experiment, resulting in unpredictable performance in experiments with multi-stage and/or multi-lineage transition of cell states where the assumption of the same kinetic rates for all cells no longer holds. Here we present cellDancer, a scalable deep neural network that locally infers velocity for each cell from its neighbors and then relays a series of local velocities to provide single-cell resolution inference of velocity kinetics. In the simulation benchmark, cellDancer shows robust performance in multiple kinetic regimes, high dropout ratio datasets and sparse datasets. We show that cellDancer overcomes the limitations of existing RNA velocity models in modeling erythroid maturation and hippocampus development. Moreover, cellDancer provides cell-specific predictions of transcription, splicing and degradation rates, which we identify as potential indicators of cell fate in the mouse pancreas.</jats:p>
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible