AIMC Topic: Endoplasmic Reticulum
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VGG-UNet/VGG-SegNet Supported Automatic Segmentation of Endoplasmic Reticulum Network in Fluorescence Microscopy Images.
Scanning
Jun 8, 2022
This research work aims to implement an automated segmentation process to extract the endoplasmic reticulum (ER) network in fluorescence microscopy images (FMI) using pretrained convolutional neural network (CNN). The threshold level of the raw FMT i...
Super resolution microscopy and deep learning identify Zika virus reorganization of the endoplasmic reticulum.
Scientific reports
Dec 1, 2020
The endoplasmic reticulum (ER) is a complex subcellular organelle composed of diverse structures such as tubules, sheets and tubular matrices. Flaviviruses such as Zika virus (ZIKV) induce reorganization of ER membranes to facilitate viral replicatio...
Machine-learning assisted confocal imaging of intracellular sites of triglycerides and cholesteryl esters formation and storage.
Analytica chimica acta
May 3, 2020
All living systems are maintained by a constant flux of metabolic energy and, among the different reactions, the process of lipids storage and lipolysis is of fundamental importance. Current research has focused on the investigation of lipid droplets...
ilastik: interactive machine learning for (bio)image analysis.
Nature methods
Sep 30, 2019
We present ilastik, an easy-to-use interactive tool that brings machine-learning-based (bio)image analysis to end users without substantial computational expertise. It contains pre-defined workflows for image segmentation, object classification, coun...
An Approach to Differentiate Cell Painted ER and Cytoplasm Using Zernike Moment Descriptor and Multilayer Perceptron.
Studies in health technology and informatics
Jun 29, 2022
Differentiation of cell organelle characteristics from microscopic images is a challenging task due to its intricate structural details. In this work, an attempt has been made to categorize Endoplasmic Reticulum (ER) and cytoplasm using orthogonal Ze...
DM3Loc: multi-label mRNA subcellular localization prediction and analysis based on multi-head self-attention mechanism.
Nucleic acids research
May 7, 2021
Subcellular localization of messenger RNAs (mRNAs), as a prevalent mechanism, gives precise and efficient control for the translation process. There is mounting evidence for the important roles of this process in a variety of cellular events. Computa...
mRNALoc: a novel machine-learning based in-silico tool to predict mRNA subcellular localization.
Nucleic acids research
Jul 2, 2020
Recent evidences suggest that the localization of mRNAs near the subcellular compartment of the translated proteins is a more robust cellular tool, which optimizes protein expression, post-transcriptionally. Retention of mRNA in the nucleus can regul...
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