AIMC Topic: Signal Transduction
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Identification of herbal categories active in pain disorder subtypes by machine learning help reveal novel molecular mechanisms of algesia.
Pharmacological research
Apr 8, 2020
Chronic pain is highly prevalent and poorly controlled, of which the accurate underlying mechanisms need be further elucidated. Herbal drugs have been widely used for controlling various pain disorders. The systematic integration of pain herbal data ...
Weighted gene co-expression network analysis reveals specific modules and biomarkers in Parkinson's disease.
Neuroscience letters
Apr 8, 2020
BACKGROUND: Parkinson's disease (PD) ranks as the second most frequently occurring neurodegenerative disease. The precise pathogenic mechanism of this disease remains unknown. The aim of the present study was to identify the biomarkers in PD and clas...
Unveiling new disease, pathway, and gene associations via multi-scale neural network.
PloS one
Apr 6, 2020
Diseases involve complex modifications to the cellular machinery. The gene expression profile of the affected cells contains characteristic patterns linked to a disease. Hence, new biological knowledge about a disease can be extracted from these prof...
Triple-Negative Breast Cancer: A Review of Conventional and Advanced Therapeutic Strategies.
International journal of environmental research and public health
Mar 20, 2020
Triple-negative breast cancer (TNBC) cells are deficient in estrogen, progesterone and ERBB2 receptor expression, presenting a particularly challenging therapeutic target due to their highly invasive nature and relatively low response to therapeutics...
Lipidome-based rapid diagnosis with machine learning for detection of TGF-β signalling activated area in head and neck cancer.
British journal of cancer
Feb 5, 2020
BACKGROUND: Several pro-oncogenic signals, including transforming growth factor beta (TGF-β) signalling from tumour microenvironment, generate intratumoural phenotypic heterogeneity and result in tumour progression and treatment failure. However, the...
Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals.
eLife
Jan 27, 2020
Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict e...
Biophysical prediction of protein-peptide interactions and signaling networks using machine learning.
Nature methods
Jan 6, 2020
In mammalian cells, much of signal transduction is mediated by weak protein-protein interactions between globular peptide-binding domains (PBDs) and unstructured peptidic motifs in partner proteins. The number and diversity of these PBDs (over 1,800 ...
Machine Learning to Quantitate Neutrophil NETosis.
Scientific reports
Nov 15, 2019
We introduce machine learning (ML) to perform classification and quantitation of images of nuclei from human blood neutrophils. Here we assessed the use of convolutional neural networks (CNNs) using free, open source software to accurately quantitate...
Big Data Challenges Targeting Proteins in GPCR Signaling Pathways; Combining PTML-ChEMBL Models and [S]GTPγS Binding Assays.
ACS chemical neuroscience
Nov 4, 2019
G-protein-coupled receptors (GPCRs), also known as 7-transmembrane receptors, are the single largest class of drug targets. Consequently, a large amount of preclinical assays having GPCRs as molecular targets has been released to public sources like ...
A comparison of machine learning classifiers for dementia with Lewy bodies using miRNA expression data.
BMC medical genomics
Oct 30, 2019
BACKGROUND: Dementia with Lewy bodies (DLB) is the second most common subtype of neurodegenerative dementia in humans following Alzheimer's disease (AD). Present clinical diagnosis of DLB has high specificity and low sensitivity and finding potential...
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