[HTML][HTML] Big data and deep learning for RNA biology
H Hwang, H Jeon, N Yeo, D Baek - Experimental & Molecular Medicine, 2024 - nature.com
The exponential growth of big data in RNA biology (RB) has led to the development of deep
learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL …
learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL …
A dynamical perspective: moving towards mechanism in single-cell transcriptomics
RJ Maizels - … Transactions of the Royal Society B, 2024 - royalsocietypublishing.org
As the field of single-cell transcriptomics matures, research is shifting focus from
phenomenological descriptions of cellular phenotypes to a mechanistic understanding of the …
phenomenological descriptions of cellular phenotypes to a mechanistic understanding of the …
Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities
Gene regulation plays a critical role in the cellular processes that underlie human health and
disease. The regulatory relationship between transcription factors (TFs), key regulators of …
disease. The regulatory relationship between transcription factors (TFs), key regulators of …
[HTML][HTML] Single-cell analysis of chromatin accessibility in the adult mouse brain
Recent advances in single-cell technologies have led to the discovery of thousands of brain
cell types; however, our understanding of the gene regulatory programs in these cell types is …
cell types; however, our understanding of the gene regulatory programs in these cell types is …
[HTML][HTML] Inferring gene regulatory networks from single-cell multiome data using atlas-scale external data
Existing methods for gene regulatory network (GRN) inference rely on gene expression data
alone or on lower resolution bulk data. Despite the recent integration of chromatin …
alone or on lower resolution bulk data. Despite the recent integration of chromatin …
[HTML][HTML] GRouNdGAN: GRN-guided simulation of single-cell RNA-seq data using causal generative adversarial networks
We introduce GRouNdGAN, a gene regulatory network (GRN)-guided reference-based
causal implicit generative model for simulating single-cell RNA-seq data, in silico …
causal implicit generative model for simulating single-cell RNA-seq data, in silico …
[HTML][HTML] Gene regulatory network reconstruction: harnessing the power of single-cell multi-omic data
Inferring gene regulatory networks (GRNs) is a fundamental challenge in biology that aims
to unravel the complex relationships between genes and their regulators. Deciphering these …
to unravel the complex relationships between genes and their regulators. Deciphering these …
MICA: a multi-omics method to predict gene regulatory networks in early human embryos
G Alanis-Lobato, TE Bartlett, Q Huang… - Life Science …, 2024 - life-science-alliance.org
Recent advances in single-cell omics have transformed characterisation of cell types in
challenging-to-study biological contexts. In contexts with limited single-cell samples, such as …
challenging-to-study biological contexts. In contexts with limited single-cell samples, such as …
Microfluidic Impedance Cytometry Enabled One‐Step Sample Preparation for Efficient Single‐Cell Mass Spectrometry
Single‐cell mass spectrometry (MS) is significant in biochemical analysis and holds great
potential in biomedical applications. Efficient sample preparation like sorting (ie, separating …
potential in biomedical applications. Efficient sample preparation like sorting (ie, separating …
Integrating single-cell multi-omics and prior biological knowledge for a functional characterization of the immune system
PSL Schäfer, D Dimitrov, EJ Villablanca… - Nature …, 2024 - nature.com
The immune system comprises diverse specialized cell types that cooperate to defend the
host against a wide range of pathogenic threats. Recent advancements in single-cell and …
host against a wide range of pathogenic threats. Recent advancements in single-cell and …