AIMC Topic: Mice
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A Genome-Based Model to Predict the Virulence of Pseudomonas aeruginosa Isolates.
mBio
Aug 25, 2020
Variation in the genome of , an important pathogen, can have dramatic impacts on the bacterium's ability to cause disease. We therefore asked whether it was possible to predict the virulence of isolates based on their genomic content. We applied a m...
Artificial Intelligence Analysis of Magnetic Particle Imaging for Islet Transplantation in a Mouse Model.
Molecular imaging and biology
Aug 24, 2020
PURPOSE: Current approaches to quantification of magnetic particle imaging (MPI) for cell-based therapy are thwarted by the lack of reliable, standardized methods of segmenting the signal from background in images. This calls for the development of a...
DeepCINAC: A Deep-Learning-Based Python Toolbox for Inferring Calcium Imaging Neuronal Activity Based on Movie Visualization.
eNeuro
Aug 17, 2020
Two-photon calcium imaging is now widely used to infer neuronal dynamics from changes in fluorescence of an indicator. However, state-of-the-art computational tools are not optimized for the reliable detection of fluorescence transients from highly s...
Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography.
Journal of visualized experiments : JoVE
Aug 16, 2020
Brain metastases are the most lethal cancer lesions; 10-30% of all cancers metastasize to the brain, with a median survival of only ~5-20 months, depending on the cancer type. To reduce the brain metastatic tumor burden, gaps in basic and translation...
Predictive modeling of estrogen receptor agonism, antagonism, and binding activities using machine- and deep-learning approaches.
Laboratory investigation; a journal of technical methods and pathology
Aug 10, 2020
As defined by the World Health Organization, an endocrine disruptor is an exogenous substance or mixture that alters function(s) of the endocrine system and consequently causes adverse health effects in an intact organism, its progeny, or (sub)popula...
Revealing architectural order with quantitative label-free imaging and deep learning.
eLife
Jul 27, 2020
We report quantitative label-free imaging with phase and polarization (QLIPP) for simultaneous measurement of density, anisotropy, and orientation of structures in unlabeled live cells and tissue slices. We combine QLIPP with deep neural networks to ...
Deep learning-based behavioral analysis reaches human accuracy and is capable of outperforming commercial solutions.
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Jul 25, 2020
To study brain function, preclinical research heavily relies on animal monitoring and the subsequent analyses of behavior. Commercial platforms have enabled semi high-throughput behavioral analyses by automating animal tracking, yet they poorly recog...
lncRNA_Mdeep: An Alignment-Free Predictor for Distinguishing Long Non-Coding RNAs from Protein-Coding Transcripts by Multimodal Deep Learning.
International journal of molecular sciences
Jul 23, 2020
Long non-coding RNAs (lncRNAs) play crucial roles in diverse biological processes and human complex diseases. Distinguishing lncRNAs from protein-coding transcripts is a fundamental step for analyzing the lncRNA functional mechanism. However, the exp...
Predicting gene regulatory regions with a convolutional neural network for processing double-strand genome sequence information.
PloS one
Jul 23, 2020
With advances in sequencing technology, a vast amount of genomic sequence information has become available. However, annotating biological functions particularly of non-protein-coding regions in genome sequences without experiments is still a challen...
Label-Free Quantification of Pharmacokinetics in Skin with Stimulated Raman Scattering Microscopy and Deep Learning.
The Journal of investigative dermatology
Jul 22, 2020
The treatment of inflammatory skin conditions relies on a deep understanding of how drugs and tissue behave and interact. Although numerous methods have been developed that aim to follow and quantify topical drug pharmacokinetics, these tools can com...
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