A5035046638- Gene Regulatory Network Analysis
- Cell Image Analysis Techniques
- Receptor Mechanisms and Signaling
- Bioinformatics and Genomic Networks
- Computational Drug Discovery Methods
- Microbial Metabolic Engineering and Bioproduction
University of Surrey
2022
The ability to direct a probabilistic Boolean network (PBN) the desired state is important applications such as targeted therapeutics in cancer biology. Reinforcement learning (RL) has been proposed framework that solves discrete-time optimal control problem cast Markov decision process. We focus on an integrative powered by model-free deep RL method can address different flavors of (e.g., with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML"...
Gene regulatory networks represent collections of regulators that interact with each other and molecules to govern gene expression. Biological signalling model how signals are transmitted activities coordinated in the cell. The study structure such complex diseases as cancer can provide insights into they function, consequently, suggest suitable treatment approaches. Here, we explored topological characteristics example a mitogen-activated protein kinase (MAPK) network derived from published...
The ability to direct a Probabilistic Boolean Network (PBN) desired state is important applications such as targeted therapeutics in cancer biology. Reinforcement Learning (RL) has been proposed framework that solves discrete-time optimal control problem cast Markov Decision Process. We focus on an integrative powered by model-free deep RL method can address different flavours of the (e.g., with or without inputs; attractor subset space target domain). agnostic distribution probabilities for...
A bstract The ability to direct a Probabilistic Boolean Network (PBN) desired state is important applications such as targeted therapeutics in cancer biology. Reinforcement Learning (RL) has been proposed framework that solves discrete-time optimal control problem cast Markov Decision Process. We focus on an integrative powered by model-free deep RL method can address different flavours of the (e.g., with or without inputs; attractor subset space target domain). agnostic distribution...