Discovering epistasis interactions in Alzheimer's disease using deep learning model

Hamid, Marwa Mostafa Abd El; Omar, Yasser M. K.; Shaheen, Mohamed; Mabrouk, Mai S.

doi:10.1016/j.genrep.2022.101673

Cited by 5 publications

(2 citation statements)

References 22 publications

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“…[ 30 ] This study used database mining and network pharmacology to comprehend the molecular targets and mechanisms of Madhuca longifolia against AD. [ 31 ] Network pharmacology is a comprehensive method that blends bioinformatics, chemoinformatics, network biology, and classical pharmacology. It is based on the analysis of network models and systems biology.…”

Section: Discussionmentioning

confidence: 99%

Network Pharmacology Unveils Potential Targets of Madhuca longifolia in Treating Alzheimer’s Disease: An Advanced Strategy in Drug Discovery

Khare,

Barot,

Singh

et al. 2024

Preprint

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Madhuca longifolia, also known to as the butternut tree or Mahua, is an evergreen species that belongs to the Sapotaceae family. Its remarkable height is roughly 17 metres. This tree, which is native to Nepal, Sri Lanka, and India, is well-known for having a wide range of chemical components, which are responsible for its numerous therapeutic benefits. In order to address Alzheimer's disease (AD), this study uses a network pharmacology technique to identify the active ingredients and molecular mechanisms of Madhuca longifolia. By applying prescreening of active constituents, target prediction, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis, our study found that Madhuca longifolia is related with eight active ingredients and 272 common gene targets. Network analysis demonstrated how Madhuca longifolia can prevent AD by modifying important signalling networks, which may be one of the molecular mechanisms driving the plant's effectiveness against the disease. This thorough investigation provides a strong basis for future research and development efforts by advancing our understanding of Madhuca longifolia's medicinal potential in Alzheimer's disease.

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Section: Discussionmentioning

confidence: 99%

Network Pharmacology Unveils Potential Targets of Madhuca longifolia in Treating Alzheimer’s Disease: An Advanced Strategy in Drug Discovery

Khare,

Barot,

Singh

et al. 2024

Preprint

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“…Convolutional neural networks (CNN) have been used to extract the most informative features to classify Alzheimer's disease patients [26]. There have been some attempts to apply deep neural networks in the SNP dataset with promising performance [27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning Framework for Complex Disease Risk Prediction Using Genomic Variations

Alzoubi

Alzubi

Ramzan

2023

Sensors

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Genome-wide association studies have proven their ability to improve human health outcomes by identifying genotypes associated with phenotypes. Various works have attempted to predict the risk of diseases for individuals based on genotype data. This prediction can either be considered as an analysis model that can lead to a better understanding of gene functions that underlie human disease or as a black box in order to be used in decision support systems and in early disease detection. Deep learning techniques have gained more popularity recently. In this work, we propose a deep-learning framework for disease risk prediction. The proposed framework employs a multilayer perceptron (MLP) in order to predict individuals’ disease status. The proposed framework was applied to the Wellcome Trust Case-Control Consortium (WTCCC), the UK National Blood Service (NBS) Control Group, and the 1958 British Birth Cohort (58C) datasets. The performance comparison of the proposed framework showed that the proposed approach outperformed the other methods in predicting disease risk, achieving an area under the curve (AUC) up to 0.94.

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Network Pharmacology Reveals Key Targets and Pathways of Madhuca longifolia for Potential Alzheimer’s Disease Treatment

Khare,

Barot,

Singh

et al. 2024

Cell Biochem Biophys

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Discovering epistasis interactions in Alzheimer's disease using deep learning model

Cited by 5 publications

References 22 publications

Network Pharmacology Unveils Potential Targets of Madhuca longifolia in Treating Alzheimer’s Disease: An Advanced Strategy in Drug Discovery

Network Pharmacology Unveils Potential Targets of Madhuca longifolia in Treating Alzheimer’s Disease: An Advanced Strategy in Drug Discovery

Deep Learning Framework for Complex Disease Risk Prediction Using Genomic Variations

Network Pharmacology Reveals Key Targets and Pathways of Madhuca longifolia for Potential Alzheimer’s Disease Treatment

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