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Improving Translational Accuracy

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

Improving Translational Accuracy

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

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Related Experiment Video

Updated: Jun 12, 2026

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

ATAT: Automated Tissue Alignment and Traversal in Spatial Transcriptomics with Self-Supervised Learning.

Steven Song^1,2, Emaan Mohsin³, Renyu Zhang¹

¹Department of Computer Science, University of Chicago, IL 60637, USA.

Biorxiv : the Preprint Server for Biology

|December 18, 2023

Summary

This summary is machine-generated.

Automated Tissue Alignment and Traversal (ATAT) streamlines spatial transcriptomics analysis by automating tissue sample alignment. This computational framework enhances gene expression modeling in complex biopsies, reducing reliance on manual annotation.

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Last Updated: Jun 12, 2026

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

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Published on: July 6, 2022

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Area of Science:

Computational Biology
Genomics
Histopathology

Background:

Spatial transcriptomics (ST) offers powerful RNA analysis in tissue biopsies but faces interpretation challenges due to complex tissue architectures.
Current ST analysis often requires extensive manual annotation by experts, limiting scalability and introducing potential biases.
Analyzing gene expression across diverse tissue morphologies, especially in gastrointestinal tract biopsies, remains a significant hurdle.

Conclusions:

ATAT provides a powerful, automated solution for spatial transcriptomics analysis, particularly for challenging tissue samples.
The framework alleviates the burden of manual annotation, making ST data interpretation more accessible and efficient.
ATAT enables deeper insights into transcriptional heterogeneity and biological processes within complex tissue microenvironments.