ReviewBriefings in bioinformatics2016
A roadmap to multifactor dimensionality reduction methods.
Review in Briefings in bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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Who cites it
35 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Transferring entropy to the realm of GxG interactions.Briefings in bioinformatics · 2018Pooled it
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- Molecular Pathogenesis of Joint Hypermobility: The Role of Intergenic Interactions.Medical sciences (Basel, Switzerland) · 2025Article
- Network medicine-based epistasis detection in complex diseases: ready for quantum computing.Nucleic acids research · 2024Article
- A Novel Detection Method for High-Order SNP Epistatic Interactions Based on Explicit-Encoding-Based Multitasking Harmony Search.Interdisciplinary sciences, computational life sciences · 2024Article
- Exploring Genetic Interactions in Colombian Women with Polycystic Ovarian Syndrome: A Study on SNP-SNP Associations.International journal of molecular sciences · 2024Article
- Cluster effect for SNP-SNP interaction pairs for predicting complex traits.Scientific reports · 2024Article
- Maternal Age at Menarche Genes Determines Fetal Growth Restriction Risk.International journal of molecular sciences · 2024Article
- Network medicine-based epistasis detection in complex diseases: ready for quantum computing.medRxiv : the preprint server for health sciences · 2023Article
- The role of a multicentre data repository in ocular inflammation: The Ocular Autoimmune Systemic Inflammatory Infectious Study (OASIS).Eye (London, England) · 2023Review
- Association ofFrontiers in neurology · 2023Article
- A Novel Multitasking Ant Colony Optimization Method for Detecting Multiorder SNP Interactions.Interdisciplinary sciences, computational life sciences · 2022Article
- Genetic variants associated with metabolic dysfunction-associated fatty liver disease in western China.Journal of clinical laboratory analysis · 2022Article
- Effect of L3MBTL3/PTPN9 polymorphisms on risk to alcohol-induced ONFH in Chinese Han population.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2022Article
- Examining SNP-SNP interactions and risk of clinical outcomes in colorectal cancer using multifactor dimensionality reduction based methods.Frontiers in genetics · 2022Article
- Spatial rank-based multifactor dimensionality reduction to detect gene-gene interactions for multivariate phenotypes.BMC bioinformatics · 2021Article
- Association between ABHD1 and DOK6 polymorphisms and susceptibility to Hirschsprung disease in Southern Chinese children.Journal of cellular and molecular medicine · 2021Article
- Optimized permutation testing for information theoretic measures of multi-gene interactions.BMC bioinformatics · 2021Article
- Performance of model-based multifactor dimensionality reduction methods for epistasis detection by controlling population structure.BioData mining · 2021Article
- Empowering individual trait prediction using interactions for precision medicine.BMC bioinformatics · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Complex diseases are defined to be determined by multiple genetic and environmental factors alone as well as in interactions. To analyze interactions in genetic data, many statistical methods have been suggested, with most of them relying on statistical regression models. Given the known limitations of classical methods, approaches from the machine-learning community have also become attractive. From this latter family, a fast-growing collection of methods emerged that are based on the Multifactor Dimensionality Reduction (MDR) approach. Since its first introduction, MDR has enjoyed great popularity in applications and has been extended and modified multiple times. Based on a literature search, we here provide a systematic and comprehensive overview of these suggested methods. The methods are described in detail, and the availability of implementations is listed. Most recent approaches offer to deal with large-scale data sets and rare variants, which is why we expect these methods to even gain in popularity.
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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.