Refining interaction search through signed iterative Random Forests

BioRxiv : the Preprint Server for Biology
Karl KumbierBin Yu


Advances in supervised learning have enabled accurate prediction in biological systems governed by complex interactions among biomolecules. However, state-of-the-art predictive algorithms are typically "black-boxes," learning statistical interactions that are difficult to translate into testable hypotheses. The iterative Random Forest (iRF) algorithm took a step towards bridging this gap by providing a computationally tractable procedure to identify the stable, high-order feature interactions that drive the predictive accuracy of Random Forests (RF). Here we refine the interactions identified by iRF to explicitly map responses as a function of interacting features. Our method, signed iRF (s-iRF), describes subsets of rules that frequently occur on RF decision paths. We refer to these "rule subsets" as signed interactions. Signed interactions share not only the same set of interacting features but also exhibit similar thresholding behavior, and thus describe a consistent functional relationship between interacting features and responses. We describe stable and predictive importance metrics (SPIMs) to rank signed interactions in terms of their stability, predictive accuracy, and strength of interaction. For each SPIM, we define n...Continue Reading


Dec 5, 2018·Karl KumbierJames Brown

Related Concepts

Enzyme Stability
Gene Expression
Spatial Distribution
Random Drug Testing

Related Feeds

BioRxiv & MedRxiv Preprints

BioRxiv and MedRxiv are the preprint servers for biology and health sciences respectively, operated by Cold Spring Harbor Laboratory. Here are the latest preprint articles (which are not peer-reviewed) from BioRxiv and MedRxiv.

CREs: Gene & Cell Therapy

Gene and cell therapy advances have shown promising outcomes for several diseases. The role of cis-regulatory elements (CREs) is crucial in the design of gene therapy vectors. Here is the latest research on CREs in gene and cell therapy.