# New Algorithms for Cryogenic Electron Microscopy

> **NIH NIH R35** · YALE UNIVERSITY · 2023 · $418,750

## Abstract

Project Summary/Abstract
Cryogenic electron-microscopy (Cryo-EM) is a new and rapidly evolving methodology for structural biology. Its
success is due to advances in Direct Detector Cameras and new algorithms. This proposal seeks to develop
the next generation of algorithms focused on reconstructing the structure of small molecular weight proteins,
proteins with multiple conformational states, and developing algorithms that explain why resolution limits occur
in Cryo-EM.
The proposed research seeks to address important bottlenecks in the above problems. First, we seek to find
useful statistics to detect the so-called “Einstein-from-noise” problem. This problem affects the reconstruction
of small molecular weight proteins, giving catastrophically bad reconstructions. We propose to investigate this
phenomenon theoretically and computationally, so that it can be detected reliably. Second, we seek to develop
the next generation of algorithms for reconstructing multiple conformational states of a heterogeneous protein.
In particular, we seek algorithms which are stable and which give high resolution reconstructions that can be
organized in biologically meaningful ways. Finally, we seek to explore a new direction in Cryo-EM algorithms.
We propose to develop a methodology which explains what causes resolution limits in a Cryo-EM
reconstruction. Current methods can estimate the resolution of a reconstruction without providing any rationale
for its cause. The new methodology will enable users to use data and algorithm settings more effectively.
The proposed research builds on the P.I. previous NIGMS supported work on single particle reconstruction in
Cryo-EM.

## Key facts

- **NIH application ID:** 10543569
- **Project number:** 1R35GM148072-01
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Hemant D Tagare
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $418,750
- **Award type:** 1
- **Project period:** 2023-08-15 → 2028-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10543569

## Citation

> US National Institutes of Health, RePORTER application 10543569, New Algorithms for Cryogenic Electron Microscopy (1R35GM148072-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10543569. Licensed CC0.

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