paper-with-me

홈 › Papers

Common Complexes of Decompositions and Complex Balanced Equilibria of Chemical Reaction Networks

2021-09-13 · Lauro L. Fontanil, Eduardo R. Mendoza

A decomposition of a chemical reaction network (CRN) is produced by partitioning its set of reactions. The partition induces networks, called subnetworks, that are "smaller" than the given CRN which, at this point, can be called parent network. A complex is called a common complex if it occurs in at least two subnetworks in a decomposition. A decomposition is said to be incidence independent if the image of the incidence map of the parent network is the direct sum of the images of the subnetworks' incidence maps. It has been recently discovered that the complex balanced equilibria of the parent network and its subnetworks are fundamentally connected in an incidence independent decomposition. In this paper, we utilized the set of common complexes and a developed criterion to investigate decomposition's incidence independence properties. A framework was also developed to analyze decomposition classes with similar structure and incidence independence properties. We identified decomposition classes that can be characterized by their sets of common complexes and studied their incidence independence. Some of these decomposition classes occur in some biological and chemical models. Finally, a sufficient condition was obtained for the complex balancing of some power law kinetic (PLK) systems with incidence independent and complex balanced decompositions. This condition led to a generalization of the Defficiency Zero Theorem for some PLK systems.

📄 PDF Abstract BibTeX arXiv:2109.06645

Code (0)

등록된 구현이 없습니다.

Methods 이 논문이 사용한 방법론

CRN Conditional Relation Network, or CRN, is a building block to construct more sophisticated structures for representation and reasoning over video. CRN takes as input an…

Similar Papers 제목 키워드 기반

Uniqueness of feasible equilibria for mass action law (MAL) kinetic systems

2016-11-10

This paper studies the relations among system parameters, uniqueness, and stability of equilibria, for kinetic systems given in the form of polynomial ODEs. Such models are commonly used to describe the dynamics of nonne…

Deep Learning-Based Strategy for Macromolecules Classification with Imbalanced Data from Cellular Electron Cryotomography

2019-08-27 · Ziqian Luo, Xiangrui Zeng, Zhipeng Bao, Min Xu

Deep learning model trained by imbalanced data may not work satisfactorily since it could be determined by major classes and thus may ignore the classes with small amount of data. In this paper, we apply deep learning ba…

ClassificationDeep LearningElectron TomographyGeneral Classification

Generalized signals on simplicial complexes

2023-05-11 · Feng Ji, Xingchao Jian, Wee Peng Tay, Maosheng Yang

Topological signal processing (TSP) over simplicial complexes typically assumes observations associated with the simplicial complexes are real scalars. In this paper, we develop TSP theories for the case where observatio…

Don't be Afraid of Cell Complexes! An Introduction from an Applied Perspective

2025-06-11 · Josef Hoppe, Vincent P. Grande, Michael T. Schaub

Cell complexes (CCs) are a higher-order network model deeply rooted in algebraic topology that has gained interest in signal processing and network science recently. However, while the processing of signals supported on …

Weisfeiler Lehman Test on Combinatorial Complexes: Generalized Expressive Power of Topological Neural Networks

2026-05-01 · Jiawen Chen, Qi Shao, Zhiqiang Ge, Duxin Chen 외 arxiv

Topological neural networks have emerged as effective tools for modeling higher-order relational structures beyond pairwise graphs, including hypergraphs, simplicial complexes, and cell complexes. However, existing Weisf…