Gene Set Analysis: Challenges, Opportunities, and Future Research
Farhad Maleki, Katie Ovens, Daniel J. Hogan, Anthony Kusalik
Abstract
Gene set analysis methods are widely used to provide insight into high-throughput gene expression data. There are many gene set analysis methods available. These methods rely on various assumptions and have different requirements, strengths and weaknesses. In this paper, we classify gene set analysis methods based on their components, describe the underlying requirements and assumptions for each class, and provide directions for future research in developing and evaluating gene set analysis methods.
Topics & Concepts
Set (abstract data type)Computer scienceStrengths and weaknessesClass (philosophy)Data setData miningData scienceComputational biologyBiologyArtificial intelligenceProgramming languageEpistemologyPhilosophyBioinformatics and Genomic NetworksGene expression and cancer classificationGene Regulatory Network Analysis