Minh Vu

ORCID: 0000-0003-4154-5659
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About
Contact & Profiles
Research Areas
  • Single-cell and spatial transcriptomics
  • Neuroinflammation and Neurodegeneration Mechanisms
  • Cell Image Analysis Techniques
  • Gene Regulatory Network Analysis
  • Neural dynamics and brain function
  • Epigenetics and DNA Methylation
  • Advanced Text Analysis Techniques
  • Biomedical Text Mining and Ontologies
  • Neurogenesis and neuroplasticity mechanisms
  • Topic Modeling

Salk Institute for Biological Studies
2020-2023

Abstract Neuronal cell types are classically defined by their molecular properties, anatomy and functions. Although recent advances in single-cell genomics have led to high-resolution characterization of type diversity the brain 1 , neuronal often studied out context anatomical properties. To improve our understanding relationship between features that define cortical neurons, here we combined retrograde labelling with single-nucleus DNA methylation sequencing link neural epigenomic...

10.1038/s41586-021-03223-w article EN cc-by Nature 2021-10-06

Abstract Single-cell analyses parse the brain’s billions of neurons into thousands ‘cell-type’ clusters residing in different brain structures 1 . Many cell types mediate their functions through targeted long-distance projections allowing interactions between specific types. Here we used epi-retro-seq 2 to link single-cell epigenomes and for 33,034 dissected from 32 regions projecting 24 targets (225 source-to-target combinations) across whole mouse brain. We highlight uses these data...

10.1038/s41586-023-06823-w article EN cc-by Nature 2023-12-13

Summary Neuronal cell types are classically defined by their molecular properties, anatomy, and functions. While recent advances in single-cell genomics have led to high-resolution characterization of type diversity the brain, neuronal often studied out context anatomical properties. To better understand relationship between features defining cortical neurons, we combined retrograde labeling with single-nucleus DNA methylation sequencing link epigenomic properties projections. We examined...

10.1101/2020.04.01.019612 preprint EN cc-by-nc-nd bioRxiv (Cold Spring Harbor Laboratory) 2020-04-03

Providing textual concept-based explanations for neurons in deep neural networks (DNNs) is of importance understanding how a DNN model works. Prior works have associated concepts with based on examples or pre-defined set concepts, thus limiting possible to what the user expects, especially discovering new concepts. Furthermore, defining requires manual work from user, either by directly specifying them collecting examples. To overcome these, we propose leverage multimodal large language...

10.48550/arxiv.2406.08572 preprint EN arXiv (Cornell University) 2024-06-12

Abstract Single-cell genetic and epigenetic analyses parse the brain’s billions of neurons into thousands “cell-type” clusters, each residing in different brain structures. Many these cell types mediate their unique functions by virtue targeted long-distance axonal projections to allow interactions between specific types. Here we have used Epi-Retro-Seq link single epigenomes associated for 33,034 dissected from 32 source regions projecting 24 targets (225 →target combinations) across whole...

10.1101/2023.05.01.538832 preprint EN cc-by-nc bioRxiv (Cold Spring Harbor Laboratory) 2023-05-01
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