Mor Nitzan
@mornitzan.bsky.social
Faculty member at the Hebrew University, studying inference of spatial organization and dynamics from single-cell data, information processing, computation & self-organization in biology. www.nitzanlab.com
Reposted by Mor Nitzan
3 reviews on planning, execution, & validation of transcriptomic experiments in neuroscience published in @natureportfolio.bsky.social #NatureNeuroscience.
A MUST READ if you're doing transcriptomics.
3 reviews, an amazing editorial, a beautiful cover – this is the issue of the year!
(mini thread)
A MUST READ if you're doing transcriptomics.
3 reviews, an amazing editorial, a beautiful cover – this is the issue of the year!
(mini thread)
December 11, 2024 at 5:04 PM
3 reviews on planning, execution, & validation of transcriptomic experiments in neuroscience published in @natureportfolio.bsky.social #NatureNeuroscience.
A MUST READ if you're doing transcriptomics.
3 reviews, an amazing editorial, a beautiful cover – this is the issue of the year!
(mini thread)
A MUST READ if you're doing transcriptomics.
3 reviews, an amazing editorial, a beautiful cover – this is the issue of the year!
(mini thread)
Characterizing single-cell and spatial data structure and identifying gaps in our knowledge of their annotations by analyzing deep learning training dynamics!
Led by @jonathankarin.bsky.social and Reshef Mintz, with
@ravehlab.bsky.social
Led by @jonathankarin.bsky.social and Reshef Mintz, with
@ravehlab.bsky.social
1/3 Annotatability is out in Nature Computational Science! With Reshef Mintz,
@ravehlab.bsky.social
and @mornitzan.bsky.social
www.nature.com/articles/s43...
@ravehlab.bsky.social
and @mornitzan.bsky.social
www.nature.com/articles/s43...
Interpreting single-cell and spatial omics data using deep neural network training dynamics - Nature Computational Science
The Annotatability framework analyzes neural network training dynamics to interpret single-cell and spatial omics data. It identifies erroneous annotations and ambiguous cell states, infers trajectori...
www.nature.com
December 8, 2024 at 2:11 PM
Characterizing single-cell and spatial data structure and identifying gaps in our knowledge of their annotations by analyzing deep learning training dynamics!
Led by @jonathankarin.bsky.social and Reshef Mintz, with
@ravehlab.bsky.social
Led by @jonathankarin.bsky.social and Reshef Mintz, with
@ravehlab.bsky.social
Reposted by Mor Nitzan
1/3 Annotatability is out in Nature Computational Science! With Reshef Mintz,
@ravehlab.bsky.social and @mor_nitzan www.nature.com/articles/s43...
.
@ravehlab.bsky.social and @mor_nitzan www.nature.com/articles/s43...
.
Interpreting single-cell and spatial omics data using deep neural network training dynamics - Nature Computational Science
The Annotatability framework analyzes neural network training dynamics to interpret single-cell and spatial omics data. It identifies erroneous annotations and ambiguous cell states, infers trajectori...
www.nature.com
December 5, 2024 at 6:43 PM
1/3 Annotatability is out in Nature Computational Science! With Reshef Mintz,
@ravehlab.bsky.social and @mor_nitzan www.nature.com/articles/s43...
.
@ravehlab.bsky.social and @mor_nitzan www.nature.com/articles/s43...
.