Inference on the structure of gene regulatory networks

TL;DR

This paper provides a comprehensive theoretical analysis of inferring gene regulatory network structures, classifying 20 scenarios based on data types and methods, and proposing new inference techniques where applicable.

Contribution

It introduces a classification of inference scenarios, reviews existing methods, and develops new mathematical approaches for scenarios with unaddressed inference possibilities.

Findings

Identifies 20 inference scenarios based on data and methods.

Proposes new inference methods for previously unaddressed scenarios.

Proves impossibility of inference in certain scenarios.

Abstract

In this paper, we conduct theoretical analyses on inferring the structure of gene regulatory networks. Depending on the experimental method and data type, the inference problem is classified into 20 different scenarios. For each scenario, we discuss the problem that with enough data, under what assumptions, what can be inferred about the structure. For scenarios that have been covered in the literature, we provide a brief review. For scenarios that have not been covered in literature, if the structure can be inferred, we propose new mathematical inference methods and evaluate them on simulated data. Otherwise, we prove that the structure cannot be inferred.