25 papers · ranked by Valyu relevance
Leyu Han, Wenfeng Du, Zhuang Xia, Boqing Gao + 2 more
'Ana Paula Piedade'] The integrated process of design and fabrication is invariably of particular interest and important to improve the quality and reduce the production cycle for structural joints, which are key components for connecting members and transferring loads in structural systems. In this work, using the…
Samuel H. King, Claudia L. Driscoll, David B. Li, Daniel Guo + 4 more
Many important biological functions arise not from single genes, but from complex interactions encoded by entire genomes. Genome language models have emerged as a promising strategy for designing biological systems, but their ability to generate functional sequences at the scale of whole genomes has remained untested.…
Ardavan Bidgoli, Pedro Veloso
Generative systems have a signifcant potential to synthesize innovative design alternatives. Still, most of the common systems that have been adopted in design require the designer to explicitly defne the specifcations of the procedures and, in some cases, the design space. In contrast, a generative system could…
Anthony J Vetturini, Jonathan Cagan, Rebecca E Taylor
Recent advances in computer-aided design tools have helped rapidly advance the development of wireframe DNA origami nanostructures. Specifically, automated tools now exist that can convert an input polyhedral mesh into a DNA origami nanostructure, greatly reducing the design difficulty for wireframe DNA origami…
Brian Hie, Salvatore Candido, Zeming Lin, Ori Kabeli + 4 more
Combining a basic set of building blocks into more complex forms is a universal design principle. Most protein designs have proceeded from a manual bottom-up approach using parts created by nature, but top-down design of proteins is fundamentally hard due to biological complexity. We demonstrate how the modularity and…
Justin D. Weisz, Jessica He, Michael Müller, Gabriela Hoefer + 2 more
Enable the user to influence the generative process and work collaboratively with the AI system - Help the user craft effective outcome specifications. Assist the user in prompting effectively to produce outputs that fit their needs. - Provide generic input parameters. Let the user control generic aspects of the…
Ethan Herron, Jaydeep Rade, Anushrut Jignasu, Baskar Ganapathysubramanian + 3 more
One of the main pillars of the engineering design process is the conceptualization step, which includes design ideation and exploration. Typically, this process involves sketching, which is required to flesh out feasible designs, even after the invention of CAD. In line with all other technologies, considerable effort…
Mads Bering Christiansen, Ahmad Rafsanjani, Jonas Jørgensen
Artificial Intelligence (AI) has rapidly become a widespread design aid through the recent proliferation of generative AI tools. In this work we use generative AI to explore soft robotics designs, specifically Soft Biomorphism, an aesthetic design paradigm emphasizing the inherent biomorphic qualities of soft robots to…
Diego Navarro-Mateu, Ana Cocho-Bermejo
Parametric design in architecture is often pigeonholed by its own definition and computational complexity. This article explores the generative capacity to integrate patterns and flows analogous to evolutionary developmental biology (Evo-Devo) strategies to develop emergent proto-architecture. Through the use of…
Yuheng Chen, Alexander Montes McNeil, Taehyuk Park, Blake A. Wilson + 15 more
Photonic device development (PDD) has achieved remarkable success in designing and implementing new devices for controlling light across various wavelengths, scales, and applications, including telecommunications, imaging, sensing, and quantum information processing. PDD is an iterative, five-step process that consists…
Shahroz Khan, Panagiotis Kaklis, Kosa Goucher-Lambert
Typical parametric approaches restrict the exploration of diverse designs by generating variations based on a baseline design. In contrast, generative models provide a solution by leveraging existing designs to create compact yet diverse generative design spaces (GDSs). However, the effectiveness of current exploration…
Megan Stanley, Marwin Segler
Computational techniques, including virtual screening, de novo design, and generative models, play an increasing role in expediting DMTA cycles for modern molecular discovery. However, computationally proposed molecules must be synthetically feasible for laboratory testing. In this perspective, we offer a succinct…
Francesca Grisoni, Berend Huisman, Alexander Button, Michael Moret + 3 more
Automation of the molecular design-make-test-analyze cycle speeds up the identification of hit and lead compounds for drug discovery. Using deep learning for computational molecular design and a customized microfluidics platform for on-chip compound synthesis, liver X receptor (LXR) agonists were generated from…
Rui Zhou, Yanxia Zhang, Chenyang Yuan, Frank Permenter + 3 more
Precise Engineering Design Synthesis Authors: ['Rui Zhou' 'Yanxia Zhang' 'Chenyang Yuan' 'Frank Permenter' 'Nikos Aréchiga' 'Matt Klenk' 'Faez Ahmed'] This paper introduces a generative model designed for multimodal control over text-to-image foundation generative AI models such as Stable Diffusion, specifically…
Jonathon B. Ferrell, Jacob M. Remington, Colin M. Van Oort, Mona Sharafi + 6 more
Antimicrobial peptides (AMPs) are peptides with promising applications for healthcare, veterinary, and agriculture industries. Despite prior success in AMP design using physics- or knowledge-based approaches, there is still a critical need to create new methodologies to design peptides with a low false positive rate…
Debjyoti Bhattacharya, Harrison Cassady, Michael Hickner, Wesley Reinhart
The design of small molecules is crucial for technological applications ranging from drug discovery to energy storage. Due to the vast design space available to modern synthetic chemistry, the community has increasingly sought to use data-driven and machine learning approaches to navigate this space. Although…
Authors not listed
The vastness of chemical space presents a long-standing challenge for the exploration of new compounds with pre-determined properties. In materials science, crystal structure prediction has become a mature tool for mapping from composition to structure based on global optimisation techniques. Generative artificial…
N.K. Dudek, D. Precup
Synthetic biology holds great promise for bioengineering applications such as environmental bioremediation, probiotic formulation, and production of renewable biofuels. Humans’ capacity to design biological systems from scratch is limited by their sheer size and complexity. We introduce a framework for training a…
Camilo Cruz Gambardella, Jon McCormack
The use of evolutionary methods in design and art is increasing in diversity and popularity. Approaches to using these methods for creative production typically focus either on optimisation or exploration. In this paper we introduce an evolutionary system for design that combines these two approaches, enabling users to…
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…
Qi Zhang, Chang Liu, Stephen Wu, Ryo Yoshida
In the last few years, de novo molecular design using machine learning has made great technical progress but its practical deployment has not been as successful. This is mostly owing to the cost and technical difficulty of synthesizing such computationally designed molecules. To overcome such barriers, various methods…
Brianna Greenstein, Danielle Elsey, Geoffrey Hutchison
Genetic algorithms (GAs) are a powerful tool to search large chemical spaces for inverse molecular design. However, GAs have multiple hyperparameters that have not been thoroughly investigated for chemical space searches. In this work, we examine the general effects of a number of hyperparameters, such as population…
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…
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…
Frederick Starkey, Filippo Menolascina
Synthetic Biology aims to rationally engineer biological systems. Current methods often employ an initial human designed circuit topology and utilise iterative approaches, e.g. directed evolution, to fine-tune part function. This approach can be extremely time consuming and resource intensive whilst often reaching…