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Cancer Research
|
May 16, 2025
Cells keep diverse company in diseased tissues
Kieran R Campbell, Aleksandrina Goeva
Nature Communications
|
November 2, 2024
HiDDEN: a machine learning method for detection of disease-relevant populations in case-control single-cell transcriptomics data
Aleksandrina Goeva, Michael-John Dolan, Judy Luu, et al.
Nature Biotechnology
|
February 19, 2021
Robust decomposition of cell type mixtures in spatial transcriptomics
Dylan M Cable, Evan Murray, Luli S Zou, et al.
Developmental Medicine and Child Neurology
|
March 13, 2018
Initial evaluation of the effects of an environmental-focused problem-solving intervention for transition-age young people with developmental disabilities: Project TEAM
Jessica M Kramer, Christine Helfrich, Melissa Levin, et al.
Cell Reports
|
April 22, 2023
Emergence of division of labor in tissues through cell interactions and spatial cues
Miri Adler, Noa Moriel, Aleksandrina Goeva, et al.
Science (New York, N.Y.)
|
March 30, 2019
Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution
Samuel G Rodriques, Robert R Stickels, Aleksandrina Goeva, et al.
Development (Cambridge, England)
|
February 15, 2024
Exploiting spatiotemporal regulation of FZD5 during neural patterning for efficient ventral midbrain specification
Andy Yang, Rony Chidiac, Emma Russo, et al.
Cell
|
August 11, 2018
Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain
Arpiar Saunders, Evan Z Macosko, Alec Wysoker, et al.
Nature Immunology
|
July 27, 2023
Exposure of iPSC-derived human microglia to brain substrates enables the generation and manipulation of diverse transcriptional states in vitro
Michael-John Dolan, Martine Therrien, Saša Jereb, et al.
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Search research articles
Search
Showing results (1-10 of 9) with videos related to
Sort By:
Page
of 1
Cancer Research
|
May 16, 2025
Cells keep diverse company in diseased tissues
Kieran R Campbell, Aleksandrina Goeva
Nature Communications
|
November 2, 2024
HiDDEN: a machine learning method for detection of disease-relevant populations in case-control single-cell transcriptomics data
Aleksandrina Goeva, Michael-John Dolan, Judy Luu, et al.
Nature Biotechnology
|
February 19, 2021
Robust decomposition of cell type mixtures in spatial transcriptomics
Dylan M Cable, Evan Murray, Luli S Zou, et al.
Developmental Medicine and Child Neurology
|
March 13, 2018
Initial evaluation of the effects of an environmental-focused problem-solving intervention for transition-age young people with developmental disabilities: Project TEAM
Jessica M Kramer, Christine Helfrich, Melissa Levin, et al.
Cell Reports
|
April 22, 2023
Emergence of division of labor in tissues through cell interactions and spatial cues
Miri Adler, Noa Moriel, Aleksandrina Goeva, et al.
Science (New York, N.Y.)
|
March 30, 2019
Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution
Samuel G Rodriques, Robert R Stickels, Aleksandrina Goeva, et al.
Development (Cambridge, England)
|
February 15, 2024
Exploiting spatiotemporal regulation of FZD5 during neural patterning for efficient ventral midbrain specification
Andy Yang, Rony Chidiac, Emma Russo, et al.
Cell
|
August 11, 2018
Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain
Arpiar Saunders, Evan Z Macosko, Alec Wysoker, et al.
Nature Immunology
|
July 27, 2023
Exposure of iPSC-derived human microglia to brain substrates enables the generation and manipulation of diverse transcriptional states in vitro
Michael-John Dolan, Martine Therrien, Saša Jereb, et al.
Page
of 1