Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Epi-SSA: A novel epistasis detection method based on a multi-objective sparrow search algorithm.

PloS one - 1 Jan 2024

Sun Liyan, Bian Jingwen, Xin Yi, Jiang Linqing, Zheng Linxuan

Abstract excerpt

Genome-wide association studies typically considers epistatic interactions as a crucial factor in exploring complex diseases. However, the current methods primarily concentrate on the detection of two-order epistatic interactions, with flaws in accuracy. In this work, we introduce a novel method called Epi-SSA, which can be better utilized to detect high-order epistatic interactions. Epi-SSA draws inspiration...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Algorithms
Share to Computer Simulation
Share to Epistasis, Genetic

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genome-Wide Association Study

Share to Models, Genetic

Share to Polymorphism, Single Nucleotide

Source

Open in PubMed Open full text

Identifiers

PMID: 39446852
DOI: 10.1371/journal.pone.0311223
PMCID: PMC11500897

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Epi-SSA: A novel epistasis detection method based on a multi-objective sparrow search algorithm.PMID 39446852Read ↗

Performance analysis of novel methods for detecting epistasis.Semantic proximity Read ↗

FDHE-IW: A Fast Approach for Detecting High-Order Epistasis in Genome-Wide Case-Control StudiesSemantic proximity Read ↗

EpiMOGA: An Epistasis Detection Method Based on a Multi-Objective Genetic Algorithm.Semantic proximity Read ↗

Evaluation of Existing Methods for High-Order Epistasis Detection.Semantic proximity Read ↗

SEEI: spherical evolution with feedback mechanism for identifying epistatic interactions.Semantic proximity Read ↗

GEP-EpiSeeker: a gene expression programming-based method for epistatic interaction detection in genome-wide association studies.Semantic proximity Read ↗

A novel two-stage approach for epistasis detection in genome-wide case-control studies.Semantic proximity Read ↗

Analysis of Gene-Gene Interactions.Semantic proximity Read ↗

Detection of SNP epistasis effects of quantitative traits using an extended Kempthorne model.Semantic proximity Read ↗

A Novel Detection Method for High-Order SNP Epistatic Interactions Based on Explicit-Encoding-Based Multitasking Harmony Search.Semantic proximity Read ↗

Evaluating the detection ability of a range of epistasis detection methods on simulated data for pure and impure epistatic models.Semantic proximity Read ↗

Fast and Accurate Exhaustive Higher-Order Epistasis Search with BitEpiSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.