Principles and challenges of modeling temporal and spatial omics data

B Velten, O Stegle - Nature Methods, 2023 - nature.com
Studies with temporal or spatial resolution are crucial to understand the molecular dynamics
and spatial dependencies underlying a biological process or system. With advances in high …

Understanding tumour endothelial cell heterogeneity and function from single-cell omics

Q Zeng, M Mousa, AS Nadukkandy, L Franssens… - Nature Reviews …, 2023 - nature.com
Anti-angiogenic therapies (AATs) are used to treat different types of cancers. However, their
success is limited owing to insufficient efficacy and resistance. Recently, single-cell omics …

Alignment of spatial genomics data using deep Gaussian processes

A Jones, FW Townes, D Li, BE Engelhardt - Nature Methods, 2023 - nature.com
Spatially resolved genomic technologies have allowed us to study the physical organization
of cells and tissues, and promise an understanding of local interactions between cells …

Biological research and self-driving labs in deep space supported by artificial intelligence

LM Sanders, RT Scott, JH Yang, AA Qutub… - Nature Machine …, 2023 - nature.com
Abstract Space biology research aims to understand fundamental spaceflight effects on
organisms, develop foundational knowledge to support deep space exploration and …

HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics

X Yuan, Y Ma, R Gao, S Cui, Y Wang, B Fa… - Nature …, 2024 - nature.com
Identifying spatially variable genes (SVGs) is crucial for understanding the spatiotemporal
characteristics of diseases and tissue structures, posing a distinctive challenge in spatial …

The covariance environment defines cellular niches for spatial inference

D Haviv, J Remšík, M Gatie, C Snopkowski… - Nature …, 2024 - nature.com
A key challenge of analyzing data from high-resolution spatial profiling technologies is to
suitably represent the features of cellular neighborhoods or niches. Here we introduce the …

Single-cell and single-nuclei RNA sequencing as powerful tools to decipher cellular heterogeneity and dysregulation in neurodegenerative diseases

R Cuevas-Diaz Duran, JC González-Orozco… - Frontiers in Cell and …, 2022 - frontiersin.org
Neurodegenerative diseases affect millions of people worldwide and there are currently no
cures. Two types of common neurodegenerative diseases are Alzheimer's (AD) and …

Unraveling non-genetic heterogeneity in cancer with dynamical models and computational tools

M Pillai, E Hojel, MK Jolly, Y Goyal - Nature Computational Science, 2023 - nature.com
Individual cells within an otherwise genetically homogenous population constantly undergo
fluctuations in their molecular state, giving rise to non-genetic heterogeneity. Such diversity …

Machine learning-based prediction and inverse design of 2D metamaterial structures with tunable deformation-dependent Poisson's ratio

J Tian, K Tang, X Chen, X Wang - Nanoscale, 2022 - pubs.rsc.org
With the aid of recent efficient and prior knowledge-free machine learning (ML) algorithms,
extraordinary mechanical properties such as negative Poisson's ratio have extensively …

Computational methods for single-cell multi-omics integration and alignment

S Stanojevic, Y Li, A Ristivojevic… - Genomics, Proteomics …, 2022 - academic.oup.com
Recently developed technologies to generate single-cell genomic data have made a
revolutionary impact in the field of biology. Multi-omics assays offer even greater …