linzhang @linzhang88
Bioinformatics @UCSF San Francisco, CA Joined December 2014-
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linzhang retweeted
Excited to share Nicheformer! Led by @Alejandro__TL & @AnnaCSchaar, Nicheformer is a foundation model for single-cell & spatial omics. Its innovation is going beyond disassociated analysis to capture & predict local tissue context at single-cell level. biorxiv.org/content/10.110…
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linzhang retweeted
Cell segmentation remains a significant challenge for imaging-based spatial transcriptomics (ST). CelloType, a transformer-based deep learning model, achieves accurate cell segmentation and classification on multiplexed fluorescence and ST imaging data. nature.com/articles/s4159…
linzhang retweeted
Our paper on comparative transcriptomics of the retina is finally out! Feeling happy, content and grateful! nature.com/articles/s4158…
linzhang retweeted
Another preprint! Remarkable conservation of retina cell types in the lamprey, a jawless vertebrate, vs. jawed peers, despite long phylogenetic distance. Kudos to Junqiang, @linzhang88 , et al! A fun collaboration with @APSampath3 , Gordon Fain. biorxiv.org/content/10.110…
linzhang retweeted
The first preprint from the Peng lab! We used scRNA-seq and scATAC-seq to understand the postnatal development of the fovea in the marmoset retina. This work was led by @linzhang88 with great contributions from Martina @uclacaltechmstp , Junqiang, et al! biorxiv.org/content/10.110…
linzhang retweeted
Evolutionary and Developmental Specialization of Foveal Cell Types in the Marmoset biorxiv.org/cgi/content/sh… #biorxiv_neursci
linzhang retweeted
Evolutionary and Developmental Specialization of Foveal Cell Types in the Marmoset biorxiv.org/cgi/content/sh… #bioRxiv
linzhang retweeted
Most recent work from the lab #AlaMorshedian #GordonFain in collaboration with @UIArtemyevLab. Reproducibility of the rod photoreceptor response depends critically on concentration of the phosphodiesterase effector enzyme jneurosci.org/content/early/…
linzhang retweeted
After 3.5+ years of perseverance, our dynamo paper is finally online in Cell today! Dynamo is an innovative and powerful framework of reconstructing continuous vector fields for mechanistic and predictive modeling of single cell fate transitions. Link: cell.com/cell/fulltext/…
linzhang retweeted
Our work on comparison of light evoked function in cone photoreceptors of human stem cell derived retinal organoids with their primate counterpart is now online @CellStemCell. (1/2) cell.com/cell-stem-cell…
linzhang retweeted
Our latest manuscript is out in @NatureComms today! Grad student @victoriahonnell found distinct modules within a super-enhancer that are necessary for proper cell fate specification in the developing #retina @StJudeResearch #developmentalbiology nature.com/articles/s4146…
linzhang retweeted
Pleased to share Sarah Bradshaw's Review: Hagfish to Illuminate the Developmental and Evolutionary Origins of the Vertebrate Retina frontiersin.org/article/10.338… Hearty thanks to @NSERC_CRSNG & beautiful @BamfieldMSC marine station for supports.
linzhang retweeted
Excited to announce that my first, first-author paper “Single-cell ATAC-seq of fetal human retina and stem-cell-derived retinal organoids shows changing chromatin landscapes during cell fate acquisition” is out now in Cell Reports! cell.com/cell-reports/f… 1/7
linzhang retweeted
Very nice new paper: cell.com/cell-reports/f… Congrats @ThomasReh4 @isortliz and @akshaya_srid!!
linzhang retweeted
1/9 After a weekend of incredible football, I am starting my week with a short tutorial on new preprint from a team led by the awesome @FranklinHolme found here biorxiv.org/cgi/content/sh…
linzhang retweeted
Excited to introduce our latest preprint on the transcriptional programs mediating RGC survival and axon regeneration. Fantastic experience working with the amazing @anne_jac83, Wenjun, @b_inbal, and others on this collaborative team!
linzhang retweeted
Our collaboration with Prof. Larry Zipursky’s group on postnatal development of the visual cortex is now published! sciencedirect.com/science/articl…
linzhang retweeted
Led by @saketkc, we analyzed 59 scRNA-seq datsets across depths, technologies, and systems - to evaluate and compare statistical error models for normalization, preprocessing, and variable gene selection. Now out in @GenomeBiology: genomebiology.biomedcentral.com/articles/10.11…
linzhang retweeted
Honored that our scArches paper made cover @NatureBiotech! It allows you to project (or query) single cell expression data onto existing reference atlases without need for full data integration by leveraging transfer learning. nature.com/articles/s4158… github.com/theislab/scarc…
linzhang retweeted
MEFISTO is out in Nature Methods - a framework for dimension reduction and integration of multi-modal omics data with temporal or spatial resolution. Paper at nature.com/articles/s4159…, highlights in the thread below. (1/7)
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