[HTML][HTML] Methods and applications for single-cell and spatial multi-omics
K Vandereyken, A Sifrim, B Thienpont… - Nature Reviews Genetics, 2023 - nature.com
The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome
from single cells is transforming our understanding of cell biology in health and disease. In …
from single cells is transforming our understanding of cell biology in health and disease. In …
[HTML][HTML] Current progress and open challenges for applying deep learning across the biosciences
Deep Learning (DL) has recently enabled unprecedented advances in one of the grand
challenges in computational biology: the half-century-old problem of protein structure …
challenges in computational biology: the half-century-old problem of protein structure …
On the opportunities and risks of foundation models
AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
[HTML][HTML] Integration of spatial and single-cell data across modalities with weakly linked features
Although single-cell and spatial sequencing methods enable simultaneous measurement of
more than one biological modality, no technology can capture all modalities within the same …
more than one biological modality, no technology can capture all modalities within the same …
scJoint integrates atlas-scale single-cell RNA-seq and ATAC-seq data with transfer learning
Single-cell multiomics data continues to grow at an unprecedented pace. Although several
methods have demonstrated promising results in integrating several data modalities from …
methods have demonstrated promising results in integrating several data modalities from …
Benchmarking algorithms for single-cell multi-omics prediction and integration
Y Hu, S Wan, Y Luo, Y Li, T Wu, W Deng, C Jiang… - Nature …, 2024 - nature.com
The development of single-cell multi-omics technology has greatly enhanced our
understanding of biology, and in parallel, numerous algorithms have been proposed to …
understanding of biology, and in parallel, numerous algorithms have been proposed to …
[HTML][HTML] Single cell cancer epigenetics
M Casado-Pelaez, A Bueno-Costa, M Esteller - Trends in Cancer, 2022 - cell.com
Bulk sequencing methodologies have allowed us to make great progress in cancer
research. Unfortunately, these techniques lack the resolution to fully unravel the epigenetic …
research. Unfortunately, these techniques lack the resolution to fully unravel the epigenetic …
scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks
Single-cell assay for transposase-accessible chromatin using sequencing (scATAC) shows
great promise for studying cellular heterogeneity in epigenetic landscapes, but there remain …
great promise for studying cellular heterogeneity in epigenetic landscapes, but there remain …
[HTML][HTML] Cobolt: integrative analysis of multimodal single-cell sequencing data
B Gong, Y Zhou, E Purdom - Genome biology, 2021 - Springer
A growing number of single-cell sequencing platforms enable joint profiling of multiple omics
from the same cells. We present Cobolt, a novel method that not only allows for analyzing …
from the same cells. We present Cobolt, a novel method that not only allows for analyzing …
Artificial intelligence and machine learning approaches using gene expression and variant data for personalized medicine
S Vadapalli, H Abdelhalim, S Zeeshan… - Briefings in …, 2022 - academic.oup.com
Precision medicine uses genetic, environmental and lifestyle factors to more accurately
diagnose and treat disease in specific groups of patients, and it is considered one of the …
diagnose and treat disease in specific groups of patients, and it is considered one of the …