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Single-Cell Analysis

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Synthetic single cell RNA sequencing data from small pilot studies using deep generative models.

Scientific reports
Deep generative models, such as variational autoencoders (VAEs) or deep Boltzmann machines (DBMs), can generate an arbitrary number of synthetic observations after being trained on an initial set of samples. This has mainly been investigated for imag...

ChrNet: A re-trainable chromosome-based 1D convolutional neural network for predicting immune cell types.

Genomics
Cells from our immune system detect and kill pathogens to protect our body against various diseases. However, current methods for determining cell types have some major limitations, such as being time-consuming and with low throughput, etc. Immune ce...

Artificial Intelligence in Bulk and Single-Cell RNA-Sequencing Data to Foster Precision Oncology.

International journal of molecular sciences
Artificial intelligence, or the discipline of developing computational algorithms able to perform tasks that requires human intelligence, offers the opportunity to improve our idea and delivery of precision medicine. Here, we provide an overview of a...

Iterative single-cell multi-omic integration using online learning.

Nature biotechnology
Integrating large single-cell gene expression, chromatin accessibility and DNA methylation datasets requires general and scalable computational approaches. Here we describe online integrative non-negative matrix factorization (iNMF), an algorithm for...

Artificial neural network model for predicting changes in ion channel conductance based on cardiac action potential shapes generated via simulation.

Scientific reports
Many studies have revealed changes in specific protein channels due to physiological causes such as mutation and their effects on action potential duration changes. However, no studies have been conducted to predict the type of protein channel abnorm...

Single Cell RNA-Seq and Machine Learning Reveal Novel Subpopulations in Low-Grade Inflammatory Monocytes With Unique Regulatory Circuits.

Frontiers in immunology
Subclinical doses of LPS (SD-LPS) are known to cause low-grade inflammatory activation of monocytes, which could lead to inflammatory diseases including atherosclerosis and metabolic syndrome. Sodium 4-phenylbutyrate is a potential therapeutic compou...

Potential applications of deep learning in single-cell RNA sequencing analysis for cell therapy and regenerative medicine.

Stem cells (Dayton, Ohio)
When used in cell therapy and regenerative medicine strategies, stem cells have potential to treat many previously incurable diseases. However, current application methods using stem cells are underdeveloped, as these cells are used directly regardle...

Fast and precise single-cell data analysis using a hierarchical autoencoder.

Nature communications
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 ...

A Reliable Machine Learning Approach applied to Single-Cell Classification in Acute Myeloid Leukemia.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Machine Learning research applied to the medical field is increasing. However, few of the proposed approaches are actually deployed in clinical settings. One reason is that current methods may not be able to generalize on new unseen instances which d...

Manipulation of Single Neural Stem Cells and Neurons in Brain Slices using Robotic Microinjection.

Journal of visualized experiments : JoVE
A central question in developmental neurobiology is how neural stem and progenitor cells form the brain. To answer this question, one needs to label, manipulate, and follow single cells in the brain tissue with high resolution over time. This task is...