27 papers · ranked by Valyu relevance
Yifei Dong, Zhanyi Sun, Lujie Yang, Manuel Baum + 4 more
Humans and animals exhibit remarkable robustness in physical manipulation, yet robots remain far behind. Progress toward human-level manipulation robustness is hindered by the absence of a unified and systematic understanding: different subfields frame robustness in distinct ways, often leaving the concept ambiguous…
David Jensen, Brian LaMacchia, Ufuk Topcu, Pamela Wiśniewski
Algorithmic robustness refers to the sustained performance of a computational system in the face of change in the nature of the environment in which that system operates or in the task that the system is meant to perform. For example, we might say that an autonomous vehicle's control system is robust if it continues to…
Anish Hebbar, Ankush Moger, Kishore Hari, Mohit Kumar Jolly
Epithelial-Mesenchymal plasticity (EMP) is a key arm of cancer metastasis and is observed across many contexts. Cells undergoing EMP can reversibly switch between three classes of phenotypes: Epithelial (E), Mesenchymal (M), and Hybrid E/M. While a large number of multistable regulatory networks have been identified to…
Mustafa Khammash
In his splendid article “Can a biologist fix a radio? - or, what I learned while studying apoptosis,” Y. Lazebnik argues that when one uses the right tools, similarity between a biological system, like a signal transduction pathway, and an engineered system, like a radio, may not seem so superficial. Here I advance…
Mae Woods, Miriam Leon, Ruben Perez-Carrasco, Chris P. Barnes
The engineering of transcriptional networks presents many challenges due to the inherent uncertainty in the system structure, changing cellular context and stochasticity in the governing dynamics. One approach to address these problems is to design and build systems that can function across a range of conditions; that…
Nasimul Noman, Taku Monjo, Pablo Moscato, Hitoshi Iba + 1 more
'Alberto de la Fuente'] Design and implementation of robust network modules is essential for construction of complex biological systems through hierarchical assembly of ‘parts’ and ‘devices’. The robustness of gene regulatory networks (GRNs) is ascribed chiefly to the underlying topology. The automatic designing…
Alexander Kott, Tarek Abdelzaher
When using the term "complex, multi-genre networks" we refer to networks that combine several distinct genres – networks of physical resources, communication networks, information networks, and social and cognitive networks. As illustrated in Fig. 1, a complex network may utilize a physical resource network (e.g., a…
Milan Česka, David Šafránek, Sven Dražan, Luboš Brim + 1 more
'Holger Fröhlich'] We propose a new framework for rigorous robustness analysis of stochastic biochemical systems that is based on probabilistic model checking techniques. We adapt the general definition of robustness introduced by Kitano to the class of stochastic systems modelled as continuous time Markov Chains in…
Kenneth A Barr, John Reinitz, Ovidiu Radulescu
Organisms must ensure that expression of genes is directed to the appropriate tissues at the correct times, while simultaneously ensuring that these gene regulatory systems are robust to perturbation. This idea is captured by a mathematical concept called r-robustness, which says that a system is robust to a…
Petter Holme, Matej Oresic
Study Metabolic Robustness and Network Modularity Authors: ['Petter Holme' 'Matej Oresic'] Background Several studies have mentioned network modularity-that a network can easily be decomposed into subgraphs that are densely connected within and weakly connected between each other-as a factor affecting metabolic…
Steven A. Frank
Robustness protects organisms in two ways. Homeostatic buffering lowers the variation of traits caused by internal or external perturbations. Tolerance reduces the consequences of bad situations, such as extreme phenotypes or infections. This article shows that both types of robustness increase the heritability of…
Alexander Muacevic, John R Adler, Thomas F Heston
Background Current reporting standards treat p-values, effect sizes, and confidence intervals as complete evidence, but this is only partial: it quantifies significance and magnitude, not classification stability (fragility) or distance from therapeutic neutrality (robustness). This study validates the p-fr-nb…
Daniele Proverbio, Stefano Boccaletti
This Special Issue received five contributions, well representative of the diverse focus associated with the topics of robustness and resilience: developing methods to assess them, or using these concepts to enhance some properties of interest; and focusing more on the development of formal or heuristic methods and…
Kee-Myoung Nam, Benjamin M. Gyori, Silviana V. Amethyst, Daniel J. Bates + 1 more
Biological systems are acknowledged to be robust to perturbations but a rigorous understanding of this has been elusive. In a mathematical model, perturbations often exert their effect through parameters, so sizes and shapes of parametric regions offer an integrated global estimate of robustness. Here, we explore this…
Attila Krajcsi
In the behavioral sciences, robust phenomena having large effect sizes and related statistical power may be unreliable. This relation is in contrast to the view that both statistical power and reliability depend similarly on measurement error. In this view, robust but unreliable phenomena can be considered as a…
Robert Veres, Zoltán László
Stability is a key attribute of complex food webs that has been for a long time in the focus of studies. It remained an intriguing question how large and complex food webs are persisting if smaller and simple ones tend to be more stable at least from a mathematic perspective. Presuming that with the increasing size of…
Andrea Tocchetti, Lorenzo Corti, Agathe Balayn, Mireia Yurrita + 3 more
'Philip Lippmann' 'Marco Brambilla' 'Jie Yang'] Despite the impressive performance of Artificial Intelligence (AI) systems, their robustness remains elusive and constitutes a key issue that impedes large-scale adoption. Robustness has been studied in many domains of AI, yet with different interpretations across domains…
Alice C. Schwarze, Jie Jiang, J. Wray, Mason A. Porter
Networks are useful descriptions of the structure of many complex systems. Unsurprisingly, it is thus important to analyze the robustness of networks in many scientific disciplines. In applications in communication, logistics, finance, ecology, biomedicine, and many other fields, researchers have studied the robustness…
James M Whitacre, Axel Bender
A generic mechanism - networked buffering - is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap…
Authors not listed
Metastable states and the conformational transitions in between them are key to understanding dynamical behaviour and function of large-scale molecular systems. By combining basic dimensionality reduction techniques with a state-of-the art approximation of the Koopman operator associated to molecular dynamics…
Authors not listed
Computational simulations of biomolecules provide a wealth of information about the thermodynamic landscape of biologically important systems, kinetics of important cellular processes, and the biophysical basis of life. Despite the ubiquity of molecular simulations in biophysical literature, major challenges persist…
Alexander Plunkett, Kaan Temiz, Chad Warren, Valea Wisniewski + 5 more
Self-assembly of nano-building blocks has emerged as a key tool to direct the arrangement and the collective properties of nanomaterials. Nevertheless, the lack of control over larger length scales when nanomaterials are processed typically leads to defects which scale with the dimensions of the specimen. This…
Authors not listed
Computer-aided synthesis planning aims to identify viable synthetic routes from a target compound to readily available building blocks by iteratively decomposing molecules into smaller precursors. Self-play search algorithms, trained with simulated experience, reach state-of-the-art performance. However, these methods…
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Realizing the promise of artificial intelligence (AI) to accelerate scientific progress and deliver technological impact depends on how effectively AI can be integrated into real-world decision- making processes. As Peter Norvig states, “Somewhat remarkably, almost all AI research until very recently has assumed that…
Authors not listed
Sequence-defined oligomers offer programmable molecular architectures with potential in data storage, authentication, and anticounterfeiting. However, their deployment in real-world materials has been constrained by their low scale, limited thermal resilience and the need for specialized analytical methods. Here we…
Authors not listed
Process chemistry creates scalable routes for new lead molecules and is a crucial but laborious stage in pharmaceutical and agrochemical development cycles. We have built an automated process chemistry platform that tackles late-stage process development. The modular workflow integrates both industry-standard tools and…
Authors not listed
The global drive towards net-zero has accelerated the adoption of carbon fibre reinforced polymers (CFRP) for lightweight structures in various sectors such as aerospace, automotive, energy and biomedical. Mechanical machining of CFRP is often necessary to meet dimensional or assembly-related requirements. However…