7 papers · ranked by Valyu relevance
Alp Tartici, Mihajlo Stojkovic, Anru Tian, Michael C. Jewett + 2 more
Protein engineering has important implications in the bioeconomy, enabling applications in materials, medicine, and energy. A key challenge is designing protein sequences that have a specific form and function. Protein inverse folding seeks to address this challenge by identifying amino acid sequences compatible with a…
Yiming Xue, Xiaojian Liu, Weimin Zhu, Shengfan Wang + 2 more
While protein-RNA interactions are fundamental to post-transcriptional processes, achieving a holistic understanding of their regulatory logic remains challenging. Current computational models often treat binding affinity, interface mapping, and RNA design as isolated tasks, thereby failing to provide a unified…
Kaining Liu, Qiuting Qian, Ying Chi
Protein generators increasingly produce conformational ensembles and trajectories as faster alternatives to molecular dynamics (MD). Yet agreement with an equilibrium ensemble does not reveal how conformations interconvert. We show that ensemble evidence can survive even when temporal dynamics are destroyed. Randomly…
Francesco Carli, Polina Rusina, Lun Ai, Leonie Küchenhoff + 7 more
Language models and agents are increasingly used in biomedicine, but current benchmarks reward correct answers even when the underlying reasoning is flawed. Here we introduce Karenina, an open-source framework that turns expert knowledge into multi-dimensional evaluations of questions, conversations and autonomous…
Amélie Barozet, Vincent Cabeli, Jean Ogier du Terrail, Alexey Rukhovich + 6 more
The development of climate-resilient crops would be greatly accelerated by models able to reason directly over plant genomic sequences and to pinpoint trait-associated regions or loci. Anticipating the impact of DNA base changes (variants) remains challenging, and understanding regulatory mechanisms is still an active…
Kunyu Wang, Jon Paul Janet, Alessandro Tibo
Three-dimensional molecular generative models have emerged that produce de novo molecules both unconditionally and conditionally, e.g., within protein pockets. However, steering those models in a specific region of the chemical space that satisfies a set of desired properties remains challenging. In this study, we…
Yilan Wu, Dun Jack Fu, Yukun Zhou, Siegfried K Wagner + 2 more
Background Large language model (LLM) agents capable of generating and executing statistical code from natural language may broaden access to clinical data analysis, yet which pipeline stages they perform reliably and which require expert oversight remain poorly defined. Objective This study aimed to evaluate the…