SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies

By Can Yang, Zengyou He, Xiang Wan, Qiang Yang, H. Xue, Weichuan Yu. 2009

208 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

1. Zexian Zeng
2. Richard E. Neapolitan
3. Xia Jiang

In Molecular Biology

1. Zexian Zeng
2. Richard E. Neapolitan
3. Xia Jiang

Citations in the corpus

• A Survey of Transfer and Multitask Learning in Bioinformatics (2011, unknown): “A combination of statistical and machine learning methods has been exploited in this area [17, 18].”
• Discovering causal interactions using Bayesian network scoring and information gain (2016, methodology): “…substantially outperformed nine epistasis learning methods including MBS [29], LEAP [31], logistic regression [18], MDR [33] combined with a heuristic search, full interaction modeling [21], information gain alone [22], SNP Harvester [23], BEAM [27], and a technique that uses maximum entropy [28].”