AIMC Topic: Mice
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Real-time, automatic, open-source sleep stage classification system using single EEG for mice.
Scientific reports
May 27, 2021
We developed a real-time sleep stage classification system with a convolutional neural network using only a one-channel electro-encephalogram source from mice and universally available features in any time-series data: raw signal, spectrum, and zeitg...
Hierarchical progressive learning of cell identities in single-cell data.
Nature communications
May 14, 2021
Supervised methods are increasingly used to identify cell populations in single-cell data. Yet, current methods are limited in their ability to learn from multiple datasets simultaneously, are hampered by the annotation of datasets at different resol...
Low-dimensional learned feature spaces quantify individual and group differences in vocal repertoires.
eLife
May 14, 2021
Increases in the scale and complexity of behavioral data pose an increasing challenge for data analysis. A common strategy involves replacing entire behaviors with small numbers of handpicked, domain-specific features, but this approach suffers from ...
Deep learning predicts gene expression as an intermediate data modality to identify susceptibility patterns in Mycobacterium tuberculosis infected Diversity Outbred mice.
EBioMedicine
May 14, 2021
BACKGROUND: Machine learning sustains successful application to many diagnostic and prognostic problems in computational histopathology. Yet, few efforts have been made to model gene expression from histopathology. This study proposes a methodology w...
An Artificial-Intelligence-Discovered Functional Ingredient, NRT_N0G5IJ, Derived from , Decreases HbA1c in a Prediabetic Population.
Nutrients
May 13, 2021
The prevalence of prediabetes is rapidly increasing, and this can lead to an increased risk for individuals to develop type 2 diabetes and associated diseases. Therefore, it is necessary to develop nutritional strategies to maintain healthy glucose l...
Overcoming false-positive gene-category enrichment in the analysis of spatially resolved transcriptomic brain atlas data.
Nature communications
May 11, 2021
Transcriptomic atlases have improved our understanding of the correlations between gene-expression patterns and spatially varying properties of brain structure and function. Gene-category enrichment analysis (GCEA) is a common method to identify func...
Pseudocell Tracer-A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombination.
PLoS computational biology
May 3, 2021
Single cell RNA sequencing (scRNAseq) can be used to infer a temporal ordering of cellular states. Current methods for the inference of cellular trajectories rely on unbiased dimensionality reduction techniques. However, such biologically agnostic or...
Mice, Inbred C57BL
Gene Expression
B-Lymphocytes
Supervised Machine Learning
RNA-Seq
Mice
Computational Biology
Signal Transduction
Basic-Leucine Zipper Transcription Factors
Immunoglobulin Class Switching
NF-kappa B p50 Subunit
STAT6 Transcription Factor
Databases, Nucleic Acid
Models, Immunological
Receptors, Cytokine
Recombination, Genetic
Neural Networks, Computer
Immunoglobulin G
Interleukin-4
Computer Simulation
Animals
Single-Cell Analysis
A Deep Learning Framework for Spatiotemporal Ultrasound Localization Microscopy.
IEEE transactions on medical imaging
Apr 30, 2021
Ultrasound Localization Microscopy (ULM) can resolve the microvascular bed down to a few micrometers. To achieve such performance, microbubble contrast agents must perfuse the entire microvascular network. Microbubbles are then located individually a...
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 ...
Automated biomarker candidate discovery in imaging mass spectrometry data through spatially localized Shapley additive explanations.
Analytica chimica acta
Apr 26, 2021
The search for molecular species that are differentially expressed between biological states is an important step towards discovering promising biomarker candidates. In imaging mass spectrometry (IMS), performing this search manually is often impract...
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