Pose Estimation, Temperature, Noise, and Biological Temperature Sensors via Cryo-EM

Pose Estimation, Temperature, Noise, and Biological Temperature Sensors via Cryo-EM

Institute for Pure & Applied Mathematics (IPAM) via YouTube Direct link

A quick introduction to Manifold Embedding.

12 of 15

12 of 15

A quick introduction to Manifold Embedding.

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Pose Estimation, Temperature, Noise, and Biological Temperature Sensors via Cryo-EM

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  1. 1 Intro
  2. 2 What is a biological temperature sensor?
  3. 3 A THERMODYNAMIC FRAMEWORK FOR TRP CHANNEL TEMPERATURE SENSING
  4. 4 3D point cloud matching vs. 3D point cloud to 2D projection matching
  5. 5 Why quaternions?
  6. 6 A discontinuity when going from rotation matrix to quaternion space!
  7. 7 Part II: Analytical solution to the 3D pose estimation problem.
  8. 8 The Determinant Ratio Matrix (DRAM) Approach
  9. 9 Summary: Improved framework for quaternion pose estimation.
  10. 10 An interlude about noise.
  11. 11 Cryo-EM allows access to a conformational distribution.
  12. 12 A quick introduction to Manifold Embedding.
  13. 13 Belief propagation in Manifold Embedding.
  14. 14 Manifold Embedding: Apo TRPV1 dataset
  15. 15 An apoferritin for heterogeneity?

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