AIMC Topic: Cell Lineage

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Temporally discordant chromatin accessibility and DNA demethylation define short- and long-term enhancer regulation during cell fate specification.

Cell reports
Chromatin and DNA modifications mediate the transcriptional activity of lineage-specifying enhancers, but recent work challenges the dogma that joint chromatin accessibility and DNA demethylation are prerequisites for transcription. To understand thi...

Deep learning-based enhancement of fluorescence labeling for accurate cell lineage tracing during embryogenesis.

Bioinformatics (Oxford, England)
MOTIVATION: Automated cell lineage tracing throughout embryogenesis plays a key role in the study of regulatory control of cell fate differentiation, morphogenesis and organogenesis in the development of animals, including nematode Caenorhabditis ele...

Epitome: predicting epigenetic events in novel cell types with multi-cell deep ensemble learning.

Nucleic acids research
The accumulation of large epigenomics data consortiums provides us with the opportunity to extrapolate existing knowledge to new cell types and conditions. We propose Epitome, a deep neural network that learns similarities of chromatin accessibility ...

Deep neural net tracking of human pluripotent stem cells reveals intrinsic behaviors directing morphogenesis.

Stem cell reports
Lineage tracing is a powerful tool in developmental biology to interrogate the evolution of tissue formation, but the dense, three-dimensional nature of tissue limits the assembly of individual cell trajectories into complete reconstructions of devel...

Label-free optical hemogram of granulocytes enhanced by artificial neural networks.

Optics express
An outstanding challenge for immunology is the classification of immune cells in a label-free fashion with high speed. For this purpose, optical techniques such as Raman spectroscopy or digital holographic microscopy have been used successfully to id...

SuperCT: a supervised-learning framework for enhanced characterization of single-cell transcriptomic profiles.

Nucleic acids research
Characterization of individual cell types is fundamental to the study of multicellular samples. Single-cell RNAseq techniques, which allow high-throughput expression profiling of individual cells, have significantly advanced our ability of this task....

Quantitative Modelling of the Waddington Epigenetic Landscape.

Methods in molecular biology (Clifton, N.J.)
C.H. Waddington introduced the epigenetic landscape as a metaphor to represent cellular decision-making during development. Like a population of balls rolling down a rough hillside, developing cells follow specific trajectories (valleys) and eventual...

Deep learning of the splicing (epi)genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision.

Nucleic acids research
Alternative splicing (AS) is a genetically and epigenetically regulated pre-mRNA processing to increase transcriptome and proteome diversity. Comprehensively decoding these regulatory mechanisms holds promise in getting deeper insights into a variety...