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Related Concept Videos

Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
Ribosomal RNA Synthesis02:53

Ribosomal RNA Synthesis

Ribosome synthesis is a highly complex and coordinated process involving more than 200 assembly factors. The synthesis and processing of ribosomal components occurs not only in the nucleolus but also in the nucleoplasm and the cytoplasm of eukaryotic cells.
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M-Cdk Drives Transition Into Mitosis02:15

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Checkpoints throughout the cell cycle serve as safeguards and gatekeepers, allowing the cell cycle to progress in favorable conditions and slow or halt it in problematic ones. This regulation is known as the cell cycle control system.
Cyclin-dependent kinases, or Cdks, work in concert with cyclins to control cell cycle transitions. M-Cdk, a complex of Cdk1 bound to M cyclin, is a well-known example of this coordinated control that drives the transition from the G2 to the M phase.
M cyclin...
Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
Ribosomal RNA Synthesis02:53

Ribosomal RNA Synthesis

Ribosome synthesis is a highly complex and coordinated process involving more than 200 assembly factors. The synthesis and processing of ribosomal components occurs not only in the nucleolus but also in the nucleoplasm and the cytoplasm of eukaryotic cells.
Ribosome biogenesis begins with the synthesis of 5S and 45S pre-rRNAs by distinct RNA polymerases. The primary transcripts are extensively processed and modified before they are bound and folded by ribosomal proteins and assembly factors,...
M-Cdk Drives Transition Into Mitosis02:15

M-Cdk Drives Transition Into Mitosis

Checkpoints throughout the cell cycle serve as safeguards and gatekeepers, allowing the cell cycle to progress in favorable conditions and slow or halt it in problematic ones. This regulation is known as the cell cycle control system.
Cyclin-dependent kinases, or Cdks, work in concert with cyclins to control cell cycle transitions. M-Cdk, a complex of Cdk1 bound to M cyclin, is a well-known example of this coordinated control that drives the transition from the G2 to the M phase.
M cyclin...

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Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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MIMYR: Generative modeling of missing tissue in spatial transcriptomics.

Ajinkya Deshpande1, Zhilei Bei2, Jian Ma3

  • 1Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.

Biorxiv : the Preprint Server for Biology
|December 15, 2025
PubMed
Summary
This summary is machine-generated.

MIMYR is a new computational framework that reconstructs missing spatial transcriptomics data. This method accurately fills in unmeasured tissue regions, improving the study of cellular interactions in health and disease.

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Area of Science:

  • Genomics
  • Computational Biology
  • Bioinformatics

Background:

  • Spatial transcriptomics reveals gene expression within tissue microenvironments.
  • Missing data in spatial transcriptomics limits analysis due to tissue damage or sample allocation.
  • Reconstructing missing data is crucial for comprehensive understanding of tissue organization.

Purpose of the Study:

  • Introduce MIMYR, a generative framework for reconstructing realistic spatial transcriptomics data.
  • Address the challenge of missing data in spatial transcriptomics datasets.
  • Enable high-fidelity spatial imputation from limited training data.

Main Methods:

  • MIMYR uses guided diffusion to predict cell locations.
  • Supervised classification assigns cell types.
  • A transformer model generates gene expression profiles conditioned on spatial and cellular context.

Main Results:

  • MIMYR accurately reconstructs missing regions in mouse brain data.
  • The framework generalizes across different experimental conditions, including gene panels and slicing orientations.
  • MIMYR captures Alzheimer's disease-associated transcriptional changes in unmeasured brain regions after finetuning.

Conclusions:

  • MIMYR enables the recovery of unmeasured tissue states in spatial transcriptomics.
  • The framework enhances the utility of spatial transcriptomics for investigating tissue spatial organization and dynamics.
  • MIMYR facilitates deeper investigations into cellular interactions in health and disease.