AIMC Topic: Caenorhabditis elegans
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Deep learning-enabled analysis reveals distinct neuronal phenotypes induced by aging and cold-shock.
BMC biology
Sep 23, 2020
BACKGROUND: Access to quantitative information is crucial to obtain a deeper understanding of biological systems. In addition to being low-throughput, traditional image-based analysis is mostly limited to error-prone qualitative or semi-quantitative ...
Accurate prediction of DNA N-methylcytosine sites via boost-learning various types of sequence features.
BMC genomics
Sep 11, 2020
BACKGROUND: DNA N4-methylcytosine (4mC) is a critical epigenetic modification and has various roles in the restriction-modification system. Due to the high cost of experimental laboratory detection, computational methods using sequence characteristic...
Discriminating between sleep and exercise-induced fatigue using computer vision and behavioral genetics.
Journal of neurogenetics
Aug 19, 2020
Following prolonged swimming, cycle between active swimming bouts and inactive quiescent bouts. Swimming is exercise for and here we suggest that inactive bouts are a recovery state akin to fatigue. It is known that cGMP-dependent kinase (PKG) acti...
Prediction of Protein-Protein Interactions with Local Weight-Sharing Mechanism in Deep Learning.
BioMed research international
Jun 13, 2020
Protein-protein interactions (PPIs) are important for almost all cellular processes, including metabolic cycles, DNA transcription and replication, and signaling cascades. The experimental methods for identifying PPIs are always time-consuming and ex...
Small-worldness favours network inference in synthetic neural networks.
Scientific reports
Feb 10, 2020
A main goal in the analysis of a complex system is to infer its underlying network structure from time-series observations of its behaviour. The inference process is often done by using bi-variate similarity measures, such as the cross-correlation (C...
MMPdb and MitoPredictor: Tools for facilitating comparative analysis of animal mitochondrial proteomes.
Mitochondrion
Jan 20, 2020
Data on experimentally-characterized animal mitochondrial proteomes (mt-proteomes) are limited to a few model organisms and are scattered across multiple databases, impeding a comparative analysis. We developed two resources to address these problems...
WormBot, an open-source robotics platform for survival and behavior analysis in C. elegans.
GeroScience
Nov 14, 2019
Caenorhabditis elegans is a popular organism for aging research owing to its highly conserved molecular pathways, short lifespan, small size, and extensive genetic and reverse genetic resources. Here we describe the WormBot, an open-source robotic im...
Three-dimensional virtual refocusing of fluorescence microscopy images using deep learning.
Nature methods
Nov 4, 2019
We demonstrate that a deep neural network can be trained to virtually refocus a two-dimensional fluorescence image onto user-defined three-dimensional (3D) surfaces within the sample. Using this method, termed Deep-Z, we imaged the neuronal activity ...
The Helitron family classification using SVM based on Fourier transform features applied on an unbalanced dataset.
Medical & biological engineering & computing
Aug 17, 2019
Helitrons are mobile sequences which belong to the class 2 of eukaryotic transposons. Their specificity resides in their mechanism of transposition: the rolling circle mechanism. They play an important role in remodeling proteomes due to their abilit...
Convergent Temperature Representations in Artificial and Biological Neural Networks.
Neuron
Jul 31, 2019
Discoveries in biological neural networks (BNNs) shaped artificial neural networks (ANNs) and computational parallels between ANNs and BNNs have recently been discovered. However, it is unclear to what extent discoveries in ANNs can give insight into...
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