ArticleBMC bioinformatics2018
An integrative network-based approach to identify novel disease genes and pathways: a case study in the context of inflammatory bowel disease.
Article in BMC bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed.
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- Bioinformatics Prediction for Network-Based Integrative Multi-Omics Expression Data Analysis in Hirschsprung Disease.Biomolecules · 2024Article
- Gene Identification in Inflammatory Bowel Disease via a Machine Learning Approach.Medicina (Kaunas, Lithuania) · 2023Article
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- Entropy-Based Graph Clustering of PPI Networks for Predicting Overlapping Functional Modules of Proteins.Entropy (Basel, Switzerland) · 2021Article
- Inference of an Integrative, Executable Network for Rheumatoid Arthritis Combining Data-Driven Machine Learning Approaches and a State-of-the-Art Mechanistic Disease Map.Journal of personalized medicine · 2021Article
- A system biology approach based on metabolic biomarkers and protein-protein interactions for identifying pathways underlying schizophrenia and bipolar disorder.Scientific reports · 2021Article
- PotentialPeerJ · 2021Article
- Network Biology Approaches to Achieve Precision Medicine in Inflammatory Bowel Disease.Frontiers in genetics · 2021Review
- Bile Acids Impair Vaccine Response in Children With Biliary Atresia.Frontiers in immunology · 2021Article
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- Identification of early stage recurrence endometrial cancer biomarkers using bioinformatics tools.Oncology reports · 2020Observational
- Discovery of inflammatory bowel disease-associated miRNAs using a novel bipartite clustering approach.BMC medical genomics · 2020Article
- Association between matrix Gla protein and ulcerative colitis according to DNA microarray data.Gastroenterology report · 2020Article
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Authors and funding
7 authors.
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Abstract
backgroundThere are different and complicated associations between genes and diseases. Finding the causal associations between genes and specific diseases is still challenging. In this work we present a method to predict novel associations of genes and pathways with inflammatory bowel disease (IBD) by integrating information of differential gene expression, protein-protein interaction and known disease genes related to IBD.
resultsWe downloaded IBD gene expression data from NCBI's Gene Expression Omnibus, performed statistical analysis to determine differentially expressed genes, collected known IBD genes from DisGeNet database, which were used to construct a IBD related PPI network with HIPPIE database. We adapted our graph-based clustering algorithm DPClusO to cluster the disease PPI network. We evaluated the statistical significance of the identified clusters in the context of determining the richness of IBD genes using Fisher's exact test and predicted novel genes related to IBD. We showed 93.8% of our predictions are correct in the context of other databases and published literatures related to IBD.
conclusionsFinding disease-causing genes is necessary for developing drugs with synergistic effect targeting many genes simultaneously. Here we present an approach to identify novel disease genes and pathways and discuss our approach in the context of IBD. The approach can be generalized to find disease-associated genes for other diseases.
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