AIMC Topic: Mouse Embryonic Stem Cells
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Supervised and unsupervised deep learning-based approaches for studying DNA replication spatiotemporal dynamics.
Communications biology
Feb 26, 2025
In eukaryotic cells, DNA replication is organised both spatially and temporally, as evidenced by the stage-specific spatial distribution of replication foci in the nucleus. Despite the genetic association of aberrant DNA replication with numerous hum...
Cheetah: A Computational Toolkit for Cybergenetic Control.
ACS synthetic biology
Apr 27, 2021
Advances in microscopy, microfluidics, and optogenetics enable single-cell monitoring and environmental regulation and offer the means to control cellular phenotypes. The development of such systems is challenging and often results in bespoke setups ...
Fast and precise single-cell data analysis using a hierarchical autoencoder.
Nature communications
Feb 15, 2021
A primary challenge in single-cell RNA sequencing (scRNA-seq) studies comes from the massive amount of data and the excess noise level. To address this challenge, we introduce an analysis framework, named single-cell Decomposition using Hierarchical ...
Determinants of Base Editing Outcomes from Target Library Analysis and Machine Learning.
Cell
Jun 12, 2020
Although base editors are widely used to install targeted point mutations, the factors that determine base editing outcomes are not well understood. We characterized sequence-activity relationships of 11 cytosine and adenine base editors (CBEs and AB...
A novel machine learning based approach for iPS progenitor cell identification.
PLoS computational biology
Dec 26, 2019
Identification of induced pluripotent stem (iPS) progenitor cells, the iPS forming cells in early stage of reprogramming, could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult ...
Critical texture pattern feature assessment for characterizing colonies of induced pluripotent stem cells through machine learning techniques.
Computers in biology and medicine
Jan 31, 2018
The objectives of this study are to assess various automated texture features obtained from the segmented colony regions of induced pluripotent stem cells (iPSCs) and confirm their potential for characterizing the colonies using different machine lea...
Domain-specific AI segmentation of IMPDH2 rod/ring structures in mouse embryonic stem cells.
BMC biology
May 12, 2025
BACKGROUND: Inosine monophosphate dehydrogenase 2 (IMPDH2) is an enzyme that catalyses the rate-limiting step of guanine nucleotides. In mouse embryonic stem cells (ESCs), IMPDH2 forms large multi-protein complexes known as rod-ring (RR) structures t...
Quantitative Analysis of Differentiation Activity for Mouse Embryonic Stem Cells by Deep Learning for Cell Center Detection using Three-Dimensional Confocal Fluorescence Microscopy Images.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2023
Accurate single cell segmentation provides means to monitor the behavior of single cell within a population of cells. Time-lapse fluorescence images are used to reveal heterogeneous nature of single mouse embryonic stem cell (ESC) colony and monitor ...
Deep and accurate detection of m6A RNA modifications using miCLIP2 and m6Aboost machine learning.
Nucleic acids research
Sep 20, 2021
N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based appr...
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