24 papers · ranked by Valyu relevance
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…
Cecilia Trivellin, Lisbeth Olsson, Peter Rugbjerg
Stable cell performance in a fluctuating environment is essential for sustainable bioproduction and synthetic cell functionality; however, microbial robustness is rarely quantified. Here, we describe a high-throughput strategy for quantifying robustness of multiple cellular functions and strains in a perturbation…
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…
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…
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…
Yongbo Ni, Yingxia Ou, Yupeng Li, Na Zhang
The stability and safety of products will be reduced if product structures are vulnerable to failures of key components. Existing methods for improving product structural robustness mainly focus on some key components, but they cannot provide designers with universal and explicit structure optimization strategies. From…
Mattias Forsgren, Benjamin Mandl, Gustav Karreskog Rehbinder
When should we expect behavioural phenomena to be robust? We argue that many phenomena of interest to behavioural scientists, by their very nature, involve manipulations of stimulus characteristics. If there exist contingencies between those stimulus characteristics and outcomes, the former will consequently constitute…
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
Traditionally, the analysis of physical and dynamical systems has focused on the question of how would a system, starting from an initial condition, evolve in time, and whether it would settle on a specific pattern, or regime . Motivated by observations in the natural and engineering sciences , a complementary question…
E. David Klonsky
Some wish to mandate preregistration as a response to the replication crisis, while I and others caution that such mandates inadvertently cause harm and distract from more critical reforms. In this article, after briefly critiquing a recently published defense of preregistration mandates, I propose a three-part vision…
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…
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…
L Salvatore, R Pierik, K Kajala, K.H ten Tusscher
Scientific progress relies on reproducibility, replicability, and robustness of research outcomes. After briefly discussing these terms and their significance for reliable scientific discovery, we argue for the importance of investigating robustness of outcomes to experimental protocol variations. We highlight…
Sina Stocker, Johannes Gasteiger, Florian Becker, Stephan Günnemann + 1 more
Graph neural networks (GNNs) have emerged as a powerful machine learning approach for the prediction of molecular properties. In particular, recently proposed advanced GNN models promise quantum chemical accuracy at a fraction of the computational cost. While the capabilities of such advanced GNNs have been extensively…
Nate B. Hardy
Simple models, in which genetic robustness is expressed as the probability that a mutation is neutral, appear to offer disparate views of the relationship between robustness and evolvability. If we assume robustness trades off with evolvability, but let environmental and mutational robustness vary across genotypes, we…
Alexander Muacevic, John R Adler, Thomas F Heston
Statistical significance is widely used to evaluate research findings but has limitations around reproducibility. Measures of statistical fragility aim to quantify robustness against violations of assumptions. However, dependence on sample size and single unit changes restricts indices like the unit fragility index and…
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
Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…
Authors not listed
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
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…
Hung-wei Lin, Sruthi M. Krishna Moorthy, Andrew Hector, Roberto Salguero-Gómez
Resilience is a central concept in ecology and environmental policy, yet its meaning and quantification remain inconsistent across subfields. Clarifying how resilience is defined and measured across the subfields of ecology is therefore a critical step towards delivering coordinated efforts to strengthen resilience…