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Clint Miller Profile
Clint Miller

@clintomics

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Human genomicist, Assoc Prof @UVA. Deconvolving complex cardiovascular diseases using systems genetics and single-cell omics.

Charlottesville, VA
Joined April 2013
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@clintomics
Clint Miller
6 months
Latest news feature in @NatureBiotech on recent developments in spatial biology to unravel disease mechanisms, with insights from experts in field @aruthak @NeBanovich @AI4Pathology @PDulaiMD Jasmine Plummer, Amanda Orr etc
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nature.com
Nature Biotechnology - As the next generation of spatial transcriptomics tools hits the market, researchers are uncovering previously unknown interactions that could transform clinical research.
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@atvbahajournals
ATVB: An AHA Journal
8 months
The 9p21 risk locus — the first and most impactful CAD genetic risk factor in humans — drives VSMCs to adopt an osteochondrogenic state, promoting calcification @clintomics @valelosardo https://t.co/CbZnzspnPh
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@valelosardo
Valentina Lo Sardo
8 months
Thrilled to share the🥇paper from the lab @atvbahajournals. Here we continue to unravel the mysteries of the 9p21.3 CAD locus showing it drives VSMC transition into an osteochondrogenic state, promoting calcification. @clintomics @UWMadisonCRB
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ahajournals.org
BACKGROUND: Genome-wide association studies have identified common genetic variants at ≈300 human genomic loci linked to coronary artery disease susceptibility. Among these genomic regions, the most...
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@atheroexpress
Athero-Express
8 months
🚀 Thrilled to announce our latest #preprint on intraplaque haemorrhage (IPH) quantification and molecular 🧬characterisation of carotid plaques using deep learning. A thread 🧵👇🏽
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@jsauce7
Jeff Saucerman
9 months
Trump's slashing of NIH indirects blocked for now in 22 states but not VA. Will the "peoples protector" Attorney General @JasonMiyaresVA stand up for Virginia researchers and doctors and their work to cure cancer, heart disease, diabetes, and more?
@kyledcheney
Kyle Cheney
9 months
JUST IN: A federal judge in Massachusetts has blocked the Trump administration's rate change to NIH grants.
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@clintomics
Clint Miller
10 months
Huge congrats to PhD student @John_S_IV for successfully defending his thesis today! Thanks to the committee and everyone for their support. @shefflab @uva_bims @MedicineUVA
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@clintomics
Clint Miller
10 months
New model for multimodal spatial omics analysis, MISO, performs feature extraction, clustering and handles large-scale omics data. Includes extensive benchmarking and application to various cancer types. ⁦@DrMingyaoLi⁩ ⁦@naturemethods
nature.com
Nature Methods - MISO (MultI-modal Spatial Omics) integrates two or more spatial omics modalities, despite differences in data quality and spatial resolution for improved feature extraction and...
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@clintomics
Clint Miller
10 months
New expression foundation model, GET, predicts gene expression in unseen cell types and context specific TF interaction networks - pretrained on chromatin accessibility data from 213 human adult and fetal cell types. @nature @ericxing @RabadanColumbia
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nature.com
Nature - A foundation model learns transcriptional regulatory syntax from chromatin accessibility and sequence data across a range of cell types to predict gene expression and transcription factor...
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@clintomics
Clint Miller
10 months
New generative model, IMPA, predicts cell morphology responses to genetic and drug perturbations, enhancing phenotypic screening and drug discovery. Corrects batch effects and models unseen perturbations. @NatureComms @mo_lotfollahi @fabian_theis https://t.co/qRAyIMugX7
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nature.com
Nature Communications - Predicting morphological impacts of perturbations using computational methods can aid treatment discovery. Here, authors present IMPA, a generative model that predicts...
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@clintomics
Clint Miller
10 months
R package: https://t.co/jWOs74viIi Code: https://t.co/tnRw1053Dm Python implementation:
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@clintomics
Clint Miller
10 months
New single-cell analysis framework, LEMUR, disentangles covariates and latent cell states from multi-condition data to predict counterfactual gene expression and identify cell neighborhoods with similar DEGs without clustering. https://t.co/Dktxxek5C7 @NatureGenet @wolfgangkhuber
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nature.com
Nature Genetics - Latent embedding multivariate regression models multi-condition single-cell RNA-seq using a continuous latent space, enabling data integration, per-cell gene expression prediction...
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@clintomics
Clint Miller
11 months
Very grateful and humbled to receive promotion to tenure @MedicineUVA! Huge thanks to my supportive mentors, colleagues, family, and talented trainees who continue to inspire me along this journey. Here’s to the work ahead!
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@shitov_happens
Vladimir Shitov
11 months
The number of cells in single-cell transcriptomics studies grew exponentially over the years. But what about the number of donors? Let me tell you the story of my contribution to the fantastic paper of @SikkemaLisa and @KHrovatin. Read the paper: https://t.co/ZsqWm5XX0p 1/12
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nature.com
Nature Methods - This Review provides a comprehensive and detailed discussion about how to build and use single-cell atlases.
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@clintomics
Clint Miller
11 months
For simulation tasks scDesign3 outperformed scFMs in simulating reference based scRNA-seq datasets @SongDongyuan @jsb_ucla
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@clintomics
Clint Miller
11 months
As expected the performance of scFMs is highly task specific..they perform well in certain tasks after fine tuning, eg cell annotation, but worse in gene regulatory networks.
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@clintomics
Clint Miller
11 months
Nice benchmarking study of 10 different foundation models for single cell data analysis..important best practices, limitations and insights to guide future applications @HongyuZhao2 https://t.co/M2dhzUnXKC
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@StephenQuake
Stephen Quake
11 months
Virtual cell models have the potential to transform biological research. Today @ChanZuckerberg released an initial set of models, including scGenePT and SubCell, designed to be easy to run and build upon. This is a really exciting time in biology.
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chanzuckerberg.com
We’re making it easier for biologists and machine learning researchers to collaborate with cell models that are easy-to-use + build upon to accelerate the next big breakthrough.
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@clintomics
Clint Miller
1 year
New method CellANOVA recovers lost biological signals and evaluates global and gene level distortions introduced from common single-cell batch correction algorithms ⁦@NatureBiotech https://t.co/EI15Gx07NR
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github.com
CellANOVA: Cell State Space Analysis of Variance for signal recovery in single cell batch integration - Janezjz/cellanova
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@junedh_amrute
Junedh M. Amrute
1 year
We use Multiome and HiC to build a comprehensive single cell variant to enhancer to gene map for coronary artery disease. Join effort with @PaulChungrohLee and IttaiEres in Nate Stitziel Lab and in collaboration with @Amgen @WUSTLmed https://t.co/bM6RPUcUEW
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medrxiv.org
Although genome wide association studies (GWAS) in large populations have identified hundreds of variants associated with common diseases such as coronary artery disease (CAD), most disease-associa...
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