Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Benjamin J Auerbach"'
Autor:
Christopher J Adams, Mitchell Conery, Benjamin J Auerbach, Shane T Jensen, Iain Mathieson, Benjamin F Voight
Publikováno v:
PLoS Genetics, Vol 19, Iss 7, p e1010807 (2023)
Germline mutation is the mechanism by which genetic variation in a population is created. Inferences derived from mutation rate models are fundamental to many population genetics methods. Previous models have demonstrated that nucleotides flanking po
Externí odkaz:
https://doaj.org/article/46701a5fce6b4e619ee0f573d01e5c25
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-14 (2022)
Previous efforts to study the circadian clock using scRNA-seq have relied on time course designs that treat cell collection time as a proxy for circadian time. Here, the authors introduce a statistical method to infer circadian timing directly from e
Externí odkaz:
https://doaj.org/article/98eebcf6b82b4aa5b880e252927e3e37
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 19, Iss , Pp 3829-3841 (2021)
Recent developments in spatially resolved transcriptomics (SRT) technologies have enabled scientists to get an integrated understanding of cells in their morphological context. Applications of these technologies in diverse tissues and diseases have t
Externí odkaz:
https://doaj.org/article/2bcff681df8a485db34ce27a264bc6ea
Autor:
Christopher J. Adams, Mitchell Conery, Benjamin J. Auerbach, Shane T. Jensen, Iain Mathieson, Benjamin F. Voight
Germline mutation is the mechanism by which genetic variation in a population is created. Inferences derived from mutation rate models are fundamental to many population genetics inference methods. Previous models have demonstrated that nucleotides f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf4963f903cd775fe5d0e2cb0356f078
https://doi.org/10.1101/2022.10.14.512160
https://doi.org/10.1101/2022.10.14.512160
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 19, Iss, Pp 3829-3841 (2021)
Computational and Structural Biotechnology Journal
Computational and Structural Biotechnology Journal
Graphical abstract
Recent developments in spatially resolved transcriptomics (SRT) technologies have enabled scientists to get an integrated understanding of cells in their morphological context. Applications of these technologies in diverse tis
Recent developments in spatially resolved transcriptomics (SRT) technologies have enabled scientists to get an integrated understanding of cells in their morphological context. Applications of these technologies in diverse tis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5801bd697ebc51d8bb3a710652df4df4
http://www.sciencedirect.com/science/article/pii/S2001037021002907
http://www.sciencedirect.com/science/article/pii/S2001037021002907
Autor:
Hanrui Zhang, Jiaxin Fan, Peter A. Sims, Andrea Califano, Muredach P. Reilly, Erin C. Bush, Huize Pan, Jeremy Worley, Alexander C. Bashore, Chenyi Xue, Benjamin J. Auerbach, Wen Liu, Pasquale Laise, Edward S. Connolly, Mingyao Li, Chinyere O. Ihuegbu, Sarah B. Trignano, Jian Cui, Robert A. Solomon, Dina Y. Yang, Jianting Shi, Lukas Vlahos
Publikováno v:
Circulation
Background: Smooth muscle cells (SMCs) play significant roles in atherosclerosis via phenotypic switching, a pathological process in which SMC dedifferentiation, migration, and transdifferentiation into other cell types. Yet how SMCs contribute to th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf7ead8b22bee893b66a499e178d600d
https://doi.org/10.1161/circulationaha.120.048378
https://doi.org/10.1161/circulationaha.120.048378
Publikováno v:
Genome Res
The advent and rapid development of single-cell technologies have made it possible to study cellular heterogeneity at an unprecedented resolution and scale. Cellular heterogeneity underlies phenotypic differences among individuals, and studying cellu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bde2eafbb90a605d7fd4bb48e85679c4
https://pubmed.ncbi.nlm.nih.gov/34599006
https://pubmed.ncbi.nlm.nih.gov/34599006