Computational Methods in Systems Biology: 20th International Conference, CMSB 2022, Bucharest, Romania, September 14–16, 2022, Proceedings

Preface
Organization
Invited Talks
Targeting and Controlling Protein-Protein Interaction Networks in Disease
Boolean Networks as a Link Between Knowledge, Data, and Quantitative Models
How to Infer Accurate Gene Regulatory Networks From Gene Expression
Sequence Space and Deep Learning to Better Understand Proteins
GRO: A Multicell Bacterial Simulator
Contents
Chemical Reaction Networks
Algebraic Biochemistry: A Framework for Analog Online Computation in Cells
1 Introduction
1.1 Related Work
2 Definitions and Main Theorem
2.1 Chemical Reaction Networks
2.2 Stabilization
2.3 Algebraic Curves and Algebraic Functions
3 Proof
4 Compilation Pipeline for Generating Stabilizing CRNs
4.1 Polynomialization
4.2 Stabilization
4.3 Quadratization
4.4 Lazy Dual-Rail Encoding
4.5 CRN Generation
5 Examples
6 Conclusion and Perspectives
References
Abstract Simulation of Reaction Networks via Boolean Networks
1 Introduction
2 Preliminaries
3 Arithmetic Expressions
4 Chemical Reaction Networks
5 First-Order Logic
6 Sign Abstraction of ODE Trajectories
7 Abstract Interpretation of ODEs
8 Boolean Networks with Non-deterministic Updates
9 Abstract Simulation of Reaction Networks
10 Thresholds
11 Application to Biomodel's Reaction Networks
12 Conclusion and Future Work
References
Abstraction-Based Segmental Simulation of Chemical Reaction Networks
1 Introduction
2 Preliminaries
3 The Plan: A Technical Overview
4 Segmental Simulation via Abstract States
4.1 Computing and Assembling Segments via Abstract States
4.2 Densely Concrete Simulations
4.3 Introduced Inaccuracy
5 From Segmental Simulations to Abstract Simulations
5.1 Segmental Abstraction of CTMC and Abstract Simulation
5.2 From Abstract Simulations Back to Concrete Predictions
6 Experimental Evaluation
7 Conclusion and Future Directions
References
Qualitative Dynamics of Chemical Reaction Networks: An Investigation Using Partial Tropical Equilibrations
1 Introduction
2 Definitions and Methods
2.1 Tropical Geometry Concepts
2.2 Partial Tropical Equilibrations and Slow-Fast Decompositions
2.3 Multiple Timescale Decompositions
2.4 Coarse Graining
3 Case Study: A Cell Cycle Model
3.1 Tropical Scaling of the Cell Cycle Model
3.2 Calculation of the Partial Tropical Equilibrations
3.3 Symbolic Dynamics by Tropicalization
3.4 Model Reduction Using Partial Tropical equilibrations
4 Conclusion and Future Work
References
Boolean Networks
Prioritization of Candidate Genes Through Boolean Networks
1 Introduction
2 Methods
2.1 Reproducible Inference of a Cell-Line Specific Boolean Network
2.2 Detection of Master Regulators in a Specific Disease-Context
3 Results
3.1 Networks Obtained from the Inference Procedure
3.2 Recommended Master Regulator Candidates
4 Discussion
A Building the Boolean Network
A.1 State-of-the-Art in Boolean Network Inference
A.2 Step (A): Building an Undirected Unsigned Graph
A.3 Step (A): Gene Perturbation Experiments
A.4 Step (B): Binarization of Experiments into Binary Profiles
A.5 Step (B): Implementation of Topological Constraints
A.6 Step (B): Implementation of Experimental Constraints
A.7 Step (C): Inference Solutions and Model Selection
B Summary of Tools in Network Identification
C Robustness on a Larger Set of 50 Solutions
D Tables
D.1 Experimental Profiles From LINCS L1000
D.2 Parameters
E Implementation of the Influence Maximization Algorithm
E.1 Iteration of Attractor States
E.2 Choice of Initial States
F Additional Results
References
Variable Stabilisation in Boolean Monotonic Model Pools
1 Introduction
2 Preliminaries
3 Methods
3.1 Theory
3.2 Algorithms and Implementation
4 Results
5 Discussion
References
Variable-Depth Simulation of Most Permissive Boolean Networks
1 Introduction
2 Background
2.1 Boolean Networks and Dynamics
2.2 Sub-hypercubes and Closures
2.3 The Most Permissive Update Mode
3 Simulation Algorithm
3.1 Main Principle
3.2 Algorithm
3.3 Correctness, Complexity, and Parametrization
3.4 Sampling Reachable Attractors
4 Evaluation
4.1 Toy Examples
4.2 Models from Literature with Different Mutation Conditions
5 Discussion
A Proofs
A.1 Proof of Lemma 1
A.2 Proof of Lemma 2
References
Minimal Trap Spaces of Logical Models are Maximal Siphons of Their Petri Net Encoding
1 Introduction
2 Preliminaries
2.1 Traps Spaces
2.2 Petri Net Encoding of Boolean Models
2.3 Siphons
3 Minimal Trap Spaces as Maximal Conflict-Free Siphons
4 Answer Set Programming-Based Method
5 Motivating Example
6 Evaluation
6.1 PyBoolNet Repository
6.2 Selected Models
7 Conclusion
References
Continuous and Hybrid Models
Stability Versus Meta-stability in a Skin Microbiome Model
1 Introduction
2 Initial ODE Model with 13 Parameters
3 Using Published Experimental Data to Define Relations Between Model Parameters by Steady-State Reasoning
3.1 Parameter Values Inferred from Mono-culture Experiment Data
3.2 Parameter Relations Inferred from Experimental Data on AMP
3.3 Parameter Relations Inferred from Co-culture Data
4 Reduced Model with 5 Parameters
4.1 Simulations at the Time Scale of the Experiments
4.2 Parameter Sensitivity and Robustness Analyses
4.3 Meta-stability Revealed by Simulation on a Long Time Scale
5 Conditions Favoring the Pathogenic Population
5.1 Skin Surface pH Elevation
5.2 Reduced Production of Skin AMPs
6 Conclusion
References
Exact Linear Reduction for Rational Dynamical Systems
1 Introduction
2 Preliminaries and Prior Results
2.1 Preliminaries on Lumping
2.2 Overview of the CLUE Algorithm for Polynomial Dynamics ch10Ovchinnikov2020
3 Algorithm for Rational Dynamical Systems
3.1 Straightforward Extension of Algorithm 1
3.2 The Main Algorithm Based on Evaluation-Interpolation
3.3 Generating ``Sufficiently Many'' Evaluations
3.4 Improving the Efficiency of Algorithm 3
4 Implementation and Performance
4.1 Performance of Algorithm 3
4.2 Comparing Algorithm 2 and Algorithm 3
5 Examples
5.1 Michaelis-Menten Kinetics with Competing Substrates
5.2 Nerve Growth Factor Signaling
6 Conclusions
References
Limit Cycle Analysis of a Class of Hybrid Gene Regulatory Networks
1 Introduction
2 Hybrid Gene Regulatory Networks
3 Limit Cycle Analysis
3.1 Identification of Closed Trajectories
3.2 Stability Analysis
4 Application
4.1 HGRNs of Negative Feedback Loop in 3 Dimensions
4.2 HGRN of Cell Cycle in 5 Dimensions
5 Conclusion
References
Machine Learning
Bayesian Learning of Effective Chemical Master Equations in Crowded Intracellular Conditions
1 Introduction
2 Connecting Different Mathematical Descriptions of Stochastic Kinetics Using Bayesian Optimization
2.1 Cellular Automata
2.2 The Chemical Master Equation and the SSA
2.3 Bayesian Optimisation
3 Applications
3.1 Michaelis-Menten Reaction in Crowded Conditions
3.2 Gene Network with Negative Feedback
4 Conclusions
A Wasserstein Distance (WD)
B CA Rules Modelling Enzyme Kinetics in Crowded Conditions
C Supplementary Tables
References
Probabilistic Multivariate Early Warning Signals
1 Introduction
2 Methods
2.1 Autocorrelation Based EWS
2.2 The Probabilistic Time-Varying Vector Autoregressive-1 Process
2.3 Simulation Model
3 Results
3.1 Simulation Benchmark
3.2 Sensitivity Analysis
4 Discussion
References
Software
MobsPy: A Meta-species Language for Chemical Reaction Networks
1 Introduction
2 MobsPy Syntax and Simulator
3 Genetic Circuits with MobsPy: The CRISPRlator
4 Conclusions
A Comparison of Meta-reactions and Reactions for the Tree Model
References
Automated Generation of Conditional Moment Equations for Stochastic Reaction Networks
1 Introduction
2 Theory
3 Usage
4 Case Study
5 Discussion
References
An Extension of ERODE to Reduce Boolean Networks By Backward Boolean Equivalence
1 Introduction
2 Preliminaries
3 ERODE
4 An Illustration of BBE Reduction
5 Importing and Exporting Capabilities
6 Conclusion
References
eBCSgen 2.0: Modelling and Analysis of Regulated Rule-Based Systems
1 Introduction
2 Regulated Biochemical Space Language
3 Implementation
4 Evaluation
5 Conclusion
References
Author Index