AIMC Topic: Autophagy
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Generalising from conventional pipelines using deep learning in high-throughput screening workflows.
Scientific reports
Jul 6, 2022
The study of complex diseases relies on large amounts of data to build models toward precision medicine. Such data acquisition is feasible in the context of high-throughput screening, in which the quality of the results relies on the accuracy of the ...
Exploring Molecular Descriptors and Fingerprints to Predict mTOR Kinase Inhibitors using Machine Learning Techniques.
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Mammalian Target of Rapamycin (mTOR) is a Ser/Thr protein kinase, and its role is integral to the autophagy pathway in cancer. Targeting mTOR for therapeutic interventions in cancer through autophagy pathway is challenging due to the dual roles of au...
Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning.
PLoS computational biology
Feb 22, 2021
Phenotypic profiling of large three-dimensional microscopy data sets has not been widely adopted due to the challenges posed by cell segmentation and feature selection. The computational demands of automated processing further limit analysis of hard-...
Using Reactome to build an autophagy mechanism knowledgebase.
Autophagy
Jun 2, 2020
The 21st century has revealed much about the fundamental cellular process of autophagy. Autophagy controls the catabolism and recycling of various cellular components both as a constitutive process and as a response to stress and foreign material inv...
A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules.
Scientific reports
Jan 22, 2020
High-throughput screening and gene signature analyses frequently identify lead therapeutic compounds with unknown modes of action (MoAs), and the resulting uncertainties can lead to the failure of clinical trials. We developed an approach for uncover...
Machine learning with autophagy-related proteins for discriminating renal cell carcinoma subtypes.
Scientific reports
Jan 20, 2020
Machine learning techniques have been previously applied for classification of tumors based largely on morphological features of tumor cells recognized in H&E images. Here, we tested the possibility of using numeric data acquired from software-based ...
DeepPhagy: a deep learning framework for quantitatively measuring autophagy activity in .
Autophagy
Jun 20, 2019
Seeing is believing. The direct observation of GFP-Atg8 vacuolar delivery under confocal microscopy is one of the most useful end-point measurements for monitoring yeast macroautophagy/autophagy. However, manually labelling individual cells from larg...
Degradation of TRPML1 in Neurons Reduces Neuron Survival in Transient Global Cerebral Ischemia.
Oxidative medicine and cellular longevity
Dec 18, 2018
Postcardiac arrest syndrome yields poor neurological outcomes, but the mechanisms underlying this condition remain poorly understood. Autophagy plays an important role in neuronal apoptosis induced by ischemia. However, whether autophagy is involved ...
Exploring autophagy with Gene Ontology.
Autophagy
Feb 17, 2018
Autophagy is a fundamental cellular process that is well conserved among eukaryotes. It is one of the strategies that cells use to catabolize substances in a controlled way. Autophagy is used for recycling cellular components, responding to cellular ...
Large-scale inference of gene function through phylogenetic annotation of Gene Ontology terms: case study of the apoptosis and autophagy cellular processes.
Database : the journal of biological databases and curation
Dec 26, 2016
We previously reported a paradigm for large-scale phylogenomic analysis of gene families that takes advantage of the large corpus of experimentally supported Gene Ontology (GO) annotations. This 'GO Phylogenetic Annotation' approach integrates GO ann...
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