Amit Singer

The Inaugural Flatiron Institute Cryo-EM Conformational Heterogeneity Challenge

The paper presents a cryo-EM conformational heterogeneity challenge to evaluate and improve methods for analyzing molecular motions in heterogeneous samples.

Cryo-EM Heterogeneity Analysis using Regularized Covariance Estimation and Kernel Regression

The paper introduces RECOVAR, a method for analyzing cryo-EM data heterogeneity using regularized covariance estimation and kernel regression, achieving high-resolution conformational state reconstruction and interpretable results.

Bayesian Perspective for Orientation Determination in Cryo-EM with Application to Structural Heterogeneity Analysis

This paper introduces a Bayesian framework for orientation estimation in cryo-EM, showing it improves reconstruction accuracy and structural heterogeneity analysis.

Toward single particle reconstruction without particle picking: Breaking the detection limit

This paper proposes a method to reconstruct 3D structures from cryo-EM micrographs without detecting individual particles, aiming to improve detection of small molecules.

Synthesizing developmental trajectories

The paper develops a semi-supervised learning framework to integrate heterogeneous biological data and demonstrates its application in analyzing Drosophila pattern formation.