Decoding enhancer complexity with machine learning and high-throughput discovery

GD Smith, WH Ching, P Cornejo-Páramo, ES Wong - Genome biology, 2023 - Springer
Enhancers are genomic DNA elements controlling spatiotemporal gene expression. Their
flexible organization and functional redundancies make deciphering their sequence-function …

Mechanisms of binding specificity among bHLH transcription factors

X de Martin, R Sodaei, G Santpere - International Journal of Molecular …, 2021 - mdpi.com
The transcriptome of every cell is orchestrated by the complex network of interaction
between transcription factors (TFs) and their binding sites on DNA. Disruption of this network …

Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression

PC Wilson, Y Muto, H Wu, A Karihaloo… - Nature …, 2022 - nature.com
The proximal tubule is a key regulator of kidney function and glucose metabolism. Diabetic
kidney disease leads to proximal tubule injury and changes in chromatin accessibility that …

Cell-type-directed design of synthetic enhancers

II Taskiran, KI Spanier, H Dickmänken, N Kempynck… - Nature, 2024 - nature.com
Transcriptional enhancers act as docking stations for combinations of transcription factors
and thereby regulate spatiotemporal activation of their target genes. It has been a long …

[HTML][HTML] Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation

C Bravo Gonzalez-Blas, I Matetovici, H Hillen… - Nature Cell …, 2024 - nature.com
In the mammalian liver, hepatocytes exhibit diverse metabolic and functional profiles based
on their location within the liver lobule. However, it is unclear whether this spatial variation …

Chromatin accessibility in the Drosophila embryo is determined by transcription factor pioneering and enhancer activation

KJ Brennan, M Weilert, S Krueger, A Pampari, H Liu… - Developmental cell, 2023 - cell.com
Chromatin accessibility is integral to the process by which transcription factors (TFs) read out
cis-regulatory DNA sequences, but it is difficult to differentiate between TFs that drive …

Decoding gene regulation in the fly brain

J Janssens, S Aibar, II Taskiran, JN Ismail, AE Gomez… - Nature, 2022 - nature.com
The Drosophila brain is a frequently used model in neuroscience. Single-cell transcriptome
analysis,,,,–, three-dimensional morphological classification and electron microscopy …

Evaluating deep learning for predicting epigenomic profiles

S Toneyan, Z Tang, PK Koo - Nature machine intelligence, 2022 - nature.com
Deep learning has been successful at predicting epigenomic profiles from DNA sequences.
Most approaches frame this task as a binary classification relying on peak callers to define …

Dirichlet flow matching with applications to dna sequence design

H Stark, B Jing, C Wang, G Corso, B Berger… - arXiv preprint arXiv …, 2024 - arxiv.org
Discrete diffusion or flow models could enable faster and more controllable sequence
generation than autoregressive models. We show that na\" ive linear flow matching on the …

Predictive analyses of regulatory sequences with EUGENe

A Klie, D Laub, JV Talwar, H Stites, T Jores… - Nature Computational …, 2023 - nature.com
Deep learning has become a popular tool to study cis-regulatory function. Yet efforts to
design software for deep-learning analyses in regulatory genomics that are findable …