Eviatar Yemini

The paper analyzes C. elegans neural activity in response to bacterial stimuli, showing that hyperbolic embedding better describes neural dynamics than Euclidean space.

The paper compares whole-brain neural activity between sexes of C. elegans in response to various chemical stimuli, finding widespread sexual dimorphism in sensory neurons.

The paper integrates bulk and single-cell RNA-seq data from C. elegans neurons to improve transcript detection and differential gene analysis.

WormID-Bench evaluates methods for neuron detection, identification, and tracking in C. elegans using a multi-laboratory dataset, highlighting the need for improved computational approaches.

The paper harmonizes whole-brain imaging datasets from multiple labs to enable automated neuron identification and identifies factors influencing neuron positioning in C. elegans.

This study investigates the role of hlh-2, the C. elegans homolog of Daughterless/E, in neurogenesis and finds that its effects are restricted rather than universal across different neuron lineages.

This paper introduces an automated alignment method and pipeline to create a more accurate 3D atlas of C. elegans neurons, improving neuron labeling confidence.

The paper integrates bulk and single-cell RNA-seq data from C. elegans neurons to improve transcript detection and differential gene analysis.

The paper uses NeuroPAL to visualize and analyze the differentiation of male-specific neurons in C. elegans, showing coordinated terminal differentiation in the fourth larval stage.

The paper provides a comprehensive gene expression profile of all 302 neurons in the C. elegans nervous system and identifies cis-regulatory elements and adhesion proteins involved in synaptic specificity.

The paper shows that bHLH transcription factors regulate lineage convergence in C. elegans neurons by controlling terminal selector gene expression.

The paper introduces NeuroPAL, a multicolor transgene for neuronal identification in C. elegans, and demonstrates its use in mapping neurotransmitter receptors, cell fate changes, and brain activity.

This paper introduces a deformable non-negative matrix factorization method to extract neural signals from moving animals, outperforming traditional methods on simulated and real data.

The paper re-evaluates the connectome of the C. elegans pharyngeal nervous system using serial EM reconstruction, revealing a more detailed structure and sensory-motor characteristics.