ArticleHeredity2014
Cuckoo search epistasis: a new method for exploring significant genetic interactions.
Article in Heredity, 2014. 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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Who cites it
16 citing papers in PubMed, 49 citations in OpenAlex.
- AI-driven drug design: a comprehensive review.Journal of computer-aided molecular design · 2026Review
- A Novel Detection Method for High-Order SNP Epistatic Interactions Based on Explicit-Encoding-Based Multitasking Harmony Search.Interdisciplinary sciences, computational life sciences · 2024Article
- SEEI: spherical evolution with feedback mechanism for identifying epistatic interactions.BMC genomics · 2024Article
- Article
- A Novel Multitasking Ant Colony Optimization Method for Detecting Multiorder SNP Interactions.Interdisciplinary sciences, computational life sciences · 2022Article
- Multi-Objective Artificial Bee Colony Algorithm Based on Scale-Free Network for Epistasis Detection.Genes · 2022Article
- GADGETS: a genetic algorithm for detecting epistasis using nuclear families.Bioinformatics (Oxford, England) · 2022Article
- GEP-EpiSeeker: a gene expression programming-based method for epistatic interaction detection in genome-wide association studies.BMC genomics · 2021Article
- Nodes with the highest control power play an important role at the final level of cooperation in directed networks.Scientific reports · 2021Article
- A propagation-based seed-centric local community detection for multilayer environment: The case study of colon adenocarcinoma.PloS one · 2021Article
- FDHE-IW: A Fast Approach for Detecting High-Order Epistasis in Genome-Wide Case-Control Studies.Genes · 2018Article
- Niche harmony search algorithm for detecting complex disease associated high-order SNP combinations.Scientific reports · 2017Article
- Article
- CINOEDV: a co-information based method for detecting and visualizing n-order epistatic interactions.BMC bioinformatics · 2016Article
- FHSA-SED: Two-Locus Model Detection for Genome-Wide Association Study with Harmony Search Algorithm.PloS one · 2016Article
- An Improved Opposition-Based Learning Particle Swarm Optimization for the Detection of SNP-SNP Interactions.BioMed research international · 2015Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The advent of high-throughput sequencing technology has resulted in the ability to measure millions of single-nucleotide polymorphisms (SNPs) from thousands of individuals. Although these high-dimensional data have paved the way for better understanding of the genetic architecture of common diseases, they have also given rise to challenges in developing computational methods for learning epistatic relationships among genetic markers. We propose a new method, named cuckoo search epistasis (CSE) for identifying significant epistatic interactions in population-based association studies with a case-control design. This method combines a computationally efficient Bayesian scoring function with an evolutionary-based heuristic search algorithm, and can be efficiently applied to high-dimensional genome-wide SNP data. The experimental results from synthetic data sets show that CSE outperforms existing methods including multifactorial dimensionality reduction and Bayesian epistasis association mapping. In addition, on a real genome-wide data set related to Alzheimer's disease, CSE identified SNPs that are consistent with previously reported results, and show the utility of CSE for application to genome-wide data.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.