ArticleComputational and mathematical methods in medicine2014
Integrating gene expression and protein interaction data for signaling pathway prediction of Alzheimer's disease.
Article in Computational and mathematical methods in medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Deep Trans-Omic Network Fusion for Molecular Mechanism of Alzheimer's Disease.Journal of Alzheimer's disease : JAD · 2024Article
- Glial cell transcriptome analyses in 3xTg-AD mice: Effects of aging, disease progression, and anti-Aβ immunotherapy.Aging brain · 2023Article
- The Study of Sarcoma Microenvironment Heterogeneity Associated With Prognosis Based on an Immunogenomic Landscape Analysis.Frontiers in bioengineering and biotechnology · 2020Article
- Network Medicine for Alzheimer's Disease and Traditional Chinese Medicine.Molecules (Basel, Switzerland) · 2018Review
- Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.Alzheimer's research & therapy · 2017Article
- Differences of immune disorders between Alzheimer's disease and breast cancer based on transcriptional regulation.PloS one · 2017Article
- Computational Reconstruction of NFκB Pathway Interaction Mechanisms during Prostate Cancer.PLoS computational biology · 2016Article
- Prediction and Characterisation of the System Effects of Aristolochic Acid: A Novel Joint Network Analysis towards Therapeutic and Toxicological Mechanisms.Scientific reports · 2015Article
- Matrix Factorization-Based Prediction of Novel Drug Indications by Integrating Genomic Space.Computational and mathematical methods in medicine · 2015Article
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4 authors.
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Abstract
Discovering the signaling pathway and regulatory network would provide significant advance in genome-wide understanding of pathogenesis of human diseases. Despite the rich transcriptome data, the limitation for microarray data is unable to detect changes beyond transcriptional level and insufficient in reconstructing pathways and regulatory networks. In our study, protein-protein interaction (PPI) data is introduced to add molecular biological information for predicting signaling pathway of Alzheimer's disease (AD). Combining PPI with gene expression data, significant genes are selected by modified linear regression model firstly. Then, according to the biological researches that inflammation reaction plays an important role in the generation and deterioration of AD, NF- κ B (nuclear factor-kappa B), as a significant inflammatory factor, has been selected as the beginning gene of the predicting signaling pathway. Based on that, integer linear programming (ILP) model is proposed to reconstruct the signaling pathway between NF- κ B and AD virulence gene APP (amyloid precursor protein). The results identify 6 AD virulence genes included in the predicted inflammatory signaling pathway, and a large amount of molecular biological analysis shows the great understanding of the underlying biological process of AD.
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