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Autocatalytic chemical networks play a predominant role in a large number of natural systems such as in metabolic pathways and in ecological networks. Despite recent efforts, the precise impact of thermodynamic constraints on these networks…

Chemical Physics · Physics 2024-06-14 Armand Despons , Yannick de Decker , David Lacoste

Molecule synthesis through machine learning is one of the fundamental problems in drug discovery. Current data-driven strategies employ one-step retrosynthesis models and search algorithms to predict synthetic routes in a top-bottom manner.…

Machine Learning · Computer Science 2024-06-05 Songtao Liu , Hanjun Dai , Yue Zhao , Peng Liu

The emergence of self-sustaining autocatalytic networks in chemical reaction systems has been studied as a possible mechanism for modelling how living systems first arose. It has been known for several decades that such networks will form…

Molecular Networks · Quantitative Biology 2020-11-24 Stuart Kauffman , Mike Steel

This paper points out some key drawbacks of today's modeling and control underlying hierarchical electric power system operations and planning as the hidden roadblocks on the way to decarbonization. We suggest that these can be overcome by…

Systems and Control · Electrical Eng. & Systems 2022-07-19 Marija Ilic , Rupamathi Jaddivada

Innovation in synthetic biology often still depends on large-scale experimental trial-and-error, domain expertise, and ingenuity. The application of rational design engineering methods promise to make this more efficient, faster, cheaper…

Molecular Networks · Quantitative Biology 2021-08-18 Robyn P. Araujo , Sean T. Vittadello , Michael P. H. Stumpf

The description of activated relaxation of glassy systems in the multidimensional configurational space is a long-standing open problem. We develop a phenomenological description of the out-of-equilibrium dynamics of a model with a rough…

Disordered Systems and Neural Networks · Physics 2014-10-09 Chiara Cammarota , Enzo Marinari

A reliable prediction of 3D protein structures from sequence data remains a big challenge due to both theoretical and computational difficulties. We have previously shown that our kinetostatic compliance method (KCM) implemented into the…

Computational Engineering, Finance, and Science · Computer Science 2017-12-27 Pouya Tavousi , Morad Behandish , Horea T. Ilies , Kazem Kazerounian

Recently, barrier certificates have been introduced to prove the safety of continuous or hybrid dynamical systems. A barrier certificate needs to exhibit some barrier function, which partitions the state space in two subsets: the safe…

Dynamical Systems · Mathematics 2015-06-22 A Djaballah , Alexandre Chapoutot , Michel Kieffer , O Bouissou

In this paper we present a new method for determining optimal designs for enzyme inhibition kinetic models, which are used to model the influence of the concentration of a substrate and an inhibition on the velocity of a reaction. The…

Methodology · Statistics 2017-09-18 Kirsten Schorning , Holger Dette , Katrin Kettelhake , Tilman Möller

The recently introduced Thermodynamic Binding Networks (TBN) model was developed with the purpose of studying self-assembling systems by focusing on their thermodynamically favorable final states, and ignoring the kinetic pathways through…

Emerging Technologies · Computer Science 2018-02-09 Cameron Chalk , Jacob Hendricks , Matthew J. Patitz , Michael Sharp

Biological regulatory networks depend upon chemical interactions to process information. Engineering such molecular computing systems is a major challenge for synthetic biology and related fields. The chemical reaction network (CRN) model…

Emerging Technologies · Computer Science 2020-09-23 Cameron Chalk , Niels Kornerup , Wyatt Reeves , David Soloveichik

Chemical kinetics and reaction engineering consists of the phenomenological framework for the disentanglement of reaction mechanisms, optimization of reaction performance and the rational design of chemical processes. Here, we utilize…

Machine Learning · Computer Science 2021-12-10 Gabriel S. Gusmão , Adhika P. Retnanto , Shashwati C. da Cunha , Andrew J. Medford

Coarse-grained modeling in molecular simulations serves not only to extend accessible time and length scales beyond atomistic limits, but also to reduce high-dimensional chemical data to low-dimensional representations that expose the…

Chemical Physics · Physics 2026-05-19 Michael N. Sakano , Alejandro Strachan

We present a unified framework for folding kinetics of proteins and RNA. The basis for this framework relies on the notion of topological frustration, which gives rise to several competing basins of attraction (CBA) in addition to the…

Soft Condensed Matter · Physics 2009-09-25 D. Thirumalai , D. K. Klimov , S. A. Woodson

Hybrid quantum/classical techniques can flexibly couple ab initio simulations to an empirical or elastic medium to model materials systems that cannot be contained in small periodic supercells. However, due to electronic non-locality a…

Materials Science · Physics 2018-03-09 Thomas D. Swinburne , James R. Kermode

Predicting enzyme kinetic parameters quantifies how efficiently an enzyme catalyzes a specific substrate under defined biochemical conditions. Canonical parameters such as the turnover number ($k_\text{cat}$), Michaelis constant…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Fei Wang , Xinye Zheng , Kun Li , Yanyan Wei , Yuxin Liu , Ganpeng Hu , Tong Bao , Jingwen Yang

The evolution of chemical reaction networks is often analyzed through kinetic models and energy landscapes, but these approaches fail to capture the deeper structural constraints governing complexity growth. In chemical reaction networks,…

Molecular Networks · Quantitative Biology 2025-04-22 Anderson M. Rodriguez

We use a free energy functional theory to elucidate general properties of heterogeneously ordering, fast folding proteins, and we test our conclusions with lattice simulations. We find that both structural and energetic heterogeneity can…

Disordered Systems and Neural Networks · Physics 2009-10-31 Steven S. Plotkin , Jose N. Onuchic

Environmentally-powered computer systems operate on renewable energy harvested from their environment, such as solar or wind, and stored in batteries. While harvesting environmental energy has long been necessary for small-scale embedded…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-05-02 Noman Bashir , Yasra Chandio , David Irwin , Fatima M. Anwar , Jeremy Gummeson , Prashant Shenoy

The identification of the limiting factors in the dynamical behavior of complex systems is an important interdisciplinary problem which often can be traced to the spectral properties of an underlying network. By deriving a general relation…

Disordered Systems and Neural Networks · Physics 2007-07-03 Adilson E. Motter