A Modified Orthogonal Matching Pursuit for Construction of Sparse Probabilistic Boolean Networks
Guiyun Xiao, Zheng-Jian Bai, Wai-Ki Ching

TL;DR
This paper introduces a modified orthogonal matching pursuit algorithm to efficiently construct sparse probabilistic Boolean networks from transition matrices, aiding gene regulatory network modeling.
Contribution
The paper presents a novel modified orthogonal matching pursuit method specifically designed for inverse construction of sparse probabilistic Boolean networks.
Findings
The algorithm can successfully recover sparse probabilistic Boolean networks under certain conditions.
Numerical results demonstrate the effectiveness of the proposed method.
The approach improves existing techniques in constructing gene regulatory network models.
Abstract
Probabilistic Boolean Networks play a remarkable role in the modelling and control of gene regulatory networks. In this paper, we consider the inverse problem of constructing a sparse probabilistic Boolean network from the prescribed transition probability matrix. We propose a modified orthogonal matching pursuit for solving the inverse problem. We provide some conditions under which the proposed algorithm can recover a sparse probabilistic Boolean network. We also report some numerical results to illustrate the effectiveness of the proposed algorithm.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGene Regulatory Network Analysis · Receptor Mechanisms and Signaling · Probabilistic and Robust Engineering Design
