Niklas Kempynck

A subtype-specific gene regulatory program controls differential circuit integration of deep CA3 pyramidal neurons

The paper identifies ST18 as a regulator of deep CA3 pyramidal neuron identity, showing its role in restricting a superficial-like program and shaping circuit integration through molecular and electrophysiological changes.

Evolutionary transfer learning enables organism-wide inference of mammalian enhancer landscapes

The paper develops STEAM, an evolution-augmented deep learning model, to predict mammalian enhancer landscapes across species using comparative genomics and single-cell data.

CREsted: modeling genomic and synthetic cell type-specific enhancers across tissues and species

CREsted is a software package for modeling and designing cell type-specific enhancers using deep learning, validated across tissues and species.

A Cross-Species Enhancer-AAV Toolkit for Cell Type-Specific Targeting Across the Basal Ganglia

The paper develops a cross-species enhancer-AAV toolkit for targeting specific cell types in the basal ganglia across species, validated in mouse and macaque.

A consensus spinal cord cell type atlas across mouse, macaque, and human

The paper creates a cross-species spinal cord cell type atlas integrating data from mouse, macaque, and human, identifying conserved and species-specific features.

The evolution of gene regulation in mammalian cerebellum development

This study identifies conserved and diverged gene regulatory networks in mammalian cerebellum development using single-nucleus gene expression and chromatin accessibility data from six species.

HyDrop v2: Scalable atlas construction for training sequence-to-function models

The paper introduces HyDrop v2, a microfluidic system for generating large scATAC-seq atlases, and shows its data is comparable to commercial platforms for training sequence-to-function models.

Circuit specific specialization of human basal ganglia astrocytes

The paper defines major axes of human basal ganglia astrocyte specialization using a multimodal atlas and identifies enhancer code for targeted viral tools.

Cross-species consensus atlas of the primate basal ganglia

The paper creates a cross-species consensus atlas of primate basal ganglia cell types using multiomic data from human, macaque, and marmoset, identifying 61 conserved cell types and a novel hybrid medium spiny neuron type.

GAME: Genomic API for Model Evaluation

GAME provides a standardized framework for benchmarking genomics models across tasks, enabling consistent evaluation and community contributions.

Evaluating Methods for the Prediction of Cell Type-Specific Enhancers in the Mammalian Cortex

The paper evaluates computational methods for predicting cell type-specific enhancers in the mouse cortex using in vivo validation data and finds that open chromatin and sequence models improve prediction accuracy.

Enhancer-driven cell type comparison reveals similarities between the mammalian and bird pallium

The paper compares enhancer codes of cell types between mammalian neocortex and avian pallium using deep learning, finding higher divergence in excitatory neurons than other cell types.

Cell type directed design of synthetic enhancers

This study uses deep learning to design synthetic enhancers that target specific cell types in fruit flies and humans, revealing the enhancer code as optimal TF activator motifs and absence of repressor motifs.