Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Lyla Atta"'
Autor:
Carrie Wright, Qier Meng, Michael R. Breshock, Lyla Atta, Margaret A. Taub, Leah R. Jager, John Muschelli, Stephanie C. Hicks
Publikováno v:
Journal of Statistics and Data Science Education, Vol 32, Iss 4, Pp 331-344 (2024)
With unprecedented and growing interest in data science education, there are limited educator materials that provide meaningful opportunities for learners to practice statistical thinking, as defined by Wild and Pfannkuch, with messy data addressing
Externí odkaz:
https://doaj.org/article/18a4cc5a04f84d3ea84a0a06222a2ced
Publikováno v:
Genome Biology, Vol 25, Iss 1, Pp 1-25 (2024)
Abstract Background Recent advances in imaging-based spatially resolved transcriptomics (im-SRT) technologies now enable high-throughput profiling of targeted genes and their locations in fixed tissues. Normalization of gene expression data is often
Externí odkaz:
https://doaj.org/article/01f2c02da4014bcb949aa202a018ac3e
Autor:
Kalen Clifton, Manjari Anant, Gohta Aihara, Lyla Atta, Osagie K. Aimiuwu, Justus M. Kebschull, Michael I. Miller, Daniel Tward, Jean Fan
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-14 (2023)
Abstract Spatial transcriptomics (ST) technologies enable high throughput gene expression characterization within thin tissue sections. However, comparing spatial observations across sections, samples, and technologies remains challenging. To address
Externí odkaz:
https://doaj.org/article/74619ed8e49c4d0184bee33dbf658bc3
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-13 (2022)
Identifying cell-type-specific spatial patterns in ST data is critical for understanding tissue organization but current methods rely on external references. Here the authors develop a reference-free method to effectively recover cell-type transcript
Externí odkaz:
https://doaj.org/article/8169b376adb24eae99a8f90a6c88b8d9
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-5 (2021)
Spatially resolved transcriptomic data demand new computational analysis methods to derive biological insights. Here, we comment on these associated computational challenges as well as highlight the opportunities for standardized benchmarking metrics
Externí odkaz:
https://doaj.org/article/30b39018bedf4a9f9b290b200f3c9857
Autor:
Akshay Kothakonda, Lyla Atta, Deborah Plana, Ferrous Ward, Chris Davis, Avilash Cramer, Robert Moran, Jacob Freake, Enze Tian, Ofer Mazor, Pavel Gorelik, Christopher Van, Christopher Hansen, Helen Yang, Yao Li, Michael S. Sinha, Ju Li, Sherry H. Yu, Nicole R. LeBoeuf, Peter K. Sorger
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 9 (2021)
The rapid spread of COVID-19 and disruption of normal supply chains has resulted in severe shortages of personal protective equipment (PPE), particularly devices with few suppliers such as powered air-purifying respirators (PAPRs). A scarcity of info
Externí odkaz:
https://doaj.org/article/7bc8e1eda7d341f69a1c467acdffc863
Autor:
Marc-Joseph Antonini, Deborah Plana, Shriya Srinivasan, Lyla Atta, Aditya Achanta, Helen Yang, Avilash K. Cramer, Jacob Freake, Michael S. Sinha, Sherry H. Yu, Nicole R. LeBoeuf, Ben Linville-Engler, Peter K. Sorger
Publikováno v:
Frontiers in Digital Health, Vol 3 (2021)
The disruption of conventional manufacturing, supply, and distribution channels during the COVID-19 pandemic caused widespread shortages in personal protective equipment (PPE) and other medical supplies. These shortages catalyzed local efforts to use
Externí odkaz:
https://doaj.org/article/a520abe21e3e486ab94225d024a8ddd4
Publikováno v:
Bioinformatics
Motivation Single-cell transcriptomics profiling technologies enable genome-wide gene expression measurements in individual cells but can currently only provide a static snapshot of cellular transcriptional states. RNA velocity analysis can help infe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6c061a03f1a0f2e2b4529c03dbbc0669
https://doi.org/10.1093/bioinformatics/btab653
https://doi.org/10.1093/bioinformatics/btab653
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-5 (2021)
Nature Communications
Nature Communications
Spatially resolved transcriptomic data demand new computational analysis methods to derive biological insights. Here, we comment on these associated computational challenges as well as highlight the opportunities for standardized benchmarking metrics
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cdc856123c22d38cae15d7fd2a379ca3
https://doaj.org/article/30b39018bedf4a9f9b290b200f3c9857
https://doaj.org/article/30b39018bedf4a9f9b290b200f3c9857
Publikováno v:
Nature Communications. 13
Recent technological advancements have enabled spatially resolved transcriptomic profiling but at multi-cellular pixel resolution, thereby hindering the identification of cell-type-specific spatial patterns and gene expression variation. To address t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::327a764e8e6f459a0eda9ba77297b07f
https://doi.org/10.1038/s41467-022-30033-z
https://doi.org/10.1038/s41467-022-30033-z