activity
20242026
most citedArtificial Intelligence for Food Innovation

3 citations · 3 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CE20263 cited

Artificial Intelligence for Food Innovation

Bianca Datta, Markus J. Buehler, Yvonne Chow +14

Global food systems must deliver nutritious, sustainable foods while sharply reducing environmental impact. Yet, food innovation remains slow, empirical, and fragmented. Artificial…

cs.AI2025

Swarms of Large Language Model Agents for Protein Sequence Design with Experimental Validation

Fiona Y. Wang, Di Sheng Lee, David L. Kaplan +1

Designing proteins de novo with tailored structural, physicochemical, and functional properties remains a grand challenge in biotechnology, medicine, and materials science, due to…

q-bio.BM2025

High-throughput Screening of the Mechanical Properties of Peptide Assemblies

Sarah K. Yorke, Zhenze Yang, Aviad Levin +4

Peptides are recognized for their varied self-assembly behaviors, forming a wide array of structures and geometries, such as spheres, fibers, and hydrogels, each presenting a uniqu…

q-bio.BM2025

Agentic End-to-End De Novo Protein Design for Tailored Dynamics Using a Language Diffusion Model

Bo Ni, Markus J. Buehler

Proteins are dynamic molecular machines whose biological functions, spanning enzymatic catalysis, signal transduction, and structural adaptation, are intrinsically linked to their…

cond-mat.soft2024

Learning the rules of peptide self-assembly through data mining with large language models

Zhenze Yang, Sarah K. Yorke, Tuomas P. J. Knowles +1

Peptides are ubiquitous and important biologically derived molecules, that have been found to self-assemble to form a wide array of structures. Extensive research has explored the…