25 papers · ranked by Valyu relevance
Zi Jia Ng, Britney Foster, Troya L. Ellis, Sophie P. Barnes + 5 more
Data literacy enables members of a school to evaluate the credibility of the information they encounter, meaningfully interpret the findings in context, and empower stakeholders to make data-based decisions that can promote student success. However, schools are often not equipped to readily interpret, critically…
Graham Dove, Martina Balestra, David Mann, Oded Nov
Applications in a range of domains, including route planning and well-being, offer advice based on the social information available in prior users' aggregated activity. When designing these applications, is it better to offer: a) advice that if strictly adhered to is more likely to result in an individual successfully…
Samangi Wadinambiarachchi, Jenny Waycott, Yvonne Rogers, Greg Wadley
As designers become familiar with generative AI, a new concept is emerging: agentic AI. While generative AI produces output in response to prompts, agentic AI systems promise to perform mundane tasks autonomously, potentially freeing designers to focus on what they love: being creative. But how do designers feel about…
Dalia Almaghaslah, Abdulrhman Alsayari, Susan Letvak
Purpose: The current study was conducted to evaluate academic advising services in a pharmacy college in Saudi Arabia. This will result in developing solutions to overcome the identified challenges. Methods: Design thinking method uses five steps: empathising, defining, ideating, prototypes and testing. Results…
Nicholas Wolczynski, Maytal Saar‐Tsechansky, Tong Wang
Expert decision-makers (DMs) in high-stakes AI-assisted decision-making (AIaDM) settings receive and reconcile recommendations from AI systems before making their final decisions. We identify distinct properties of these settings which are key to developing AIaDM models that effectively benefit team performance. First…
Nicholas Wolczynski, Maytal Saar‐Tsechansky, Tong Wang
Are Necessary to Reliably Benefit Experts and Organizations Authors: ['Nicholas Wolczynski' 'Maytal Saar‐Tsechansky' 'Tong Wang'] Despite advances in AI's performance and interpretability, AI advisors can undermine experts' decisions and increase the time and effort experts must invest to make decisions. Consequently…
Gali Noti, Yiling Chen
Artificial intelligence (AI) systems are increasingly used for providing advice to facilitate human decision making in a wide range of domains, such as healthcare, criminal justice, and finance. Motivated by limitations of the current practice where algorithmic advice is provided to human users as a constant element in…
Carla Molins-Pitarch, Jonas Krebs, David Brena
The transdisciplinary ChromDesign project explored and demonstrated the power of Design research for developing new tools for visualizing and communicating complex concepts in molecular biology to diverse audiences.
Terry T.-K. Huang, Emily A. Callahan, Emily R. Haines, Cole Hooley + 4 more
Many public health challenges are characterized by complexity that reflects the dynamic systems in which they occur. Such systems involve multiple interdependent factors, actors, and sectors that influence health, and are a primary driver of challenges of insufficient implementation, sustainment, and scale of…
Felipe Engelberger, Jonathan D. Zakary, Georg Künze
Recent developments in machine learning have greatly facilitated the design of proteins with improved properties. However, accurately assessing the contributions of an individual or multiple amino acid mutations to overall protein stability to select the most promising mutants remains a challenge. Knowing the specific…
Vladimir Porokhin, Anne M. Brown, Soha Hassoun
Biological engineering aims to enhance biological systems by designing proteins with improved catalytic properties or ligands with enhanced function. Typically, applications permit designing proteins, e.g., an enzyme in a biodegradation reaction, or ligands e.g., a drug for a target receptor, but not both. Yet, some…
S. Panda
Design assistants are frameworks, tools or applications intended to facilitate both the creative and technical facets of design processes. Large language models (LLMs) are AI systems engineered to analyze and produce text resembling human language, leveraging extensive datasets. This study introduces a framework…
Iiris Sundin, Alexey Voronov, Haoping Xiao, Kostas Papadopoulos + 5 more
A de novo molecular design workflow can be used together with technologies such as reinforcement learning to navigate the chemical space. A bottleneck in the workflow that remains to be solved is how to integrate human feedback in the exploration of the chemical space to optimize molecules. A human drug designer still…
Authors not listed
Effective visualization of complex synthesis routes is critical for computeraided synthesis planning (CASP), yet current solutions are limited in scope, integration flexibility, and chemical intuition. We introduce RouteWise, a versatile, containerized web application designed to address these unmet needs. Its modular…
Thomas Scott, Christian Alan Paul Smethurst, Yvonne Westermaier, Moriz Mayer + 22 more
Given the role of human intuition in current drug design efforts, crowd-sourced 'citizen scientist' games have the potential to greatly expand the pool of potential drug designers. Here, we introduce ‘Drugit', the small molecule design mode of the online ‘citizen science’ game Foldit. We demonstrate its utility for…
Lucas P. Merlicek, Jannik Neumann, Abbie Lear, Vivian Degiorgi + 4 more
The ability to create new-to-nature enzymes would substantially advance bioengineering, medicine, and the chemical industry. Despite recent breakthroughs in protein design and structure prediction, designing biocatalysts with activities rivaling those of natural enzymes remains challenging. Here, we present AI.zymes, a…
Anna Matuszyńska, Oliver Ebenhöh, Matias D. Zurbriggen, Daniel C. Ducat + 1 more
Synthetic biology designs and constructs new biological parts, devices and systems with predetermined functionalities. With the unlimited ability to synthesise any DNA and RNA and transfer it to almost any organism, we are at the dawn of a new era in which biology is being recreated in ways never before possible. It…
GRAEME BLAIR, JASPER COOPER, ALEXANDER COPPOCK, MACARTAN HUMPHREYS
Researchers need to select high-quality research designs and communicate those designs clearly to readers. Both tasks are difficult. We provide a framework for formally “declaring” the analytically relevant features of a research design in a demonstrably complete manner, with applications to qualitative, quantitative…
Simeon D. Castle, Michiel Stock, Thomas E. Gorochowski
Careful consideration of how we approach design is crucial to all areas of biotechnology. However, choosing or developing an effective design methodology is not always easy as biology, unlike most areas of engineering, is able to adapt and evolve. Here, we put forward that design and evolution follow a similar cyclic…
Miguel Á. Valderrama-Gómez, Jason G. Lomnitz, Rick A. Fasani, Michael A. Savageau
Mechanistic models of biochemical systems provide a rigorous kinetics-based description of various biological phenomena. They are indispensable to elucidate biological design principles and to devise and engineer systems with novel functionalities. To date, mathematical analysis and characterization of these models…
Kathleen S. Dreyer, Anh V. Nguyen, Gauri G. Bora, Lauren E. Redus + 6 more
Genetic programs can direct living systems to perform diverse, pre-specified functions. As the library of parts available for building such programs continues to expand, computation-guided design is increasingly helpful and necessary. Predictive models aid the challenging design process, but iterative simulation and…
Anamaria Crisan, Jennifer L. Gardy, Tamara Munzner
Data visualization is an important tool for exploring and communicating findings from genomic and health datasets. Yet, without a systematic way of understanding the design space of data visualizations, researchers do not have a clear sense of what kind of visualizations are possible, or how to distinguish between good…
Authors not listed
Experimental design plays an important role in efficiently acquiring informative data for system characterization and deriving robust conclusions under resource limitations. Recent advancements in high-throughput experimentation coupled with machine learning have notably improved experimental procedures. While Bayesian…
Tatsuya Yoshizawa, Shoichi Ishida, Tomohiro Sato, Masateru Ohta + 2 more
Molecular design using data-driven generative models has emerged as a promising technology, impacting various fields such as drug discovery and the development of functional materials. However, this approach is often susceptible to optimization failure due to reward hacking, where prediction models fail to accurately…
Authors not listed
Cyclic peptides become attractive therapeutic candidates due to their diverse biological activities. However, existing deep learning-based sequence design models, such as ProteinMPNN, are primarily optimized using cross-entropy loss and often overlook the unique topological constraints of cyclic peptides. This limits…