Neural Information Processing Systems http://nips.cc/

Engineered proteins offer the potential to solve many problems in biomedicine, energy, and materials science, but creating designs that succeed is difficult in practice.

In the first, we used the latest version of Rosetta (3.10) to design Method Recovery (%) Speed (residues/s)Rosetta 3.10 fixbb 17.9 4.88 10 Thank you for these great suggestions. Thank you for this suggestion. (Figure 1). Benchmarking against Rosetta Please see our response to reviewer # 1.

Analyzing the structure and function of proteins is a key part of understanding biology at the molecular and cellular level. In addition, a major engineering challenge is to design new proteins in a principled and methodical way.

Integrating knowledge graphs (KGs) into the reasoning processes of large language models (LLMs) has emerged as a promising approach to mitigate hallucination. However, existing work in this area often relies on proprietary or extremely large models, limiting accessibility and scalability. In this study, we investigate the capabilities of existing integration methods for small language models (SLMs) in KG-based question answering and observe that their performance is often constrained by their limited ability to traverse and reason over knowledge graphs. To address this limitation, we propose leveraging simple and efficient exploration modules to handle knowledge graph traversal in place of the language model itself. Experiment results demonstrate that these lightweight modules effectively improve the performance of small language models on knowledge graph question answering tasks. Source code: https://github.com/yijie-cheng/SLM-ToG/.

Engineered proteins offer the potential to solve many problems in biomedicine, energy, and materials science, but creating designs that succeed is difficult in practice.

In the first, we used the latest version of Rosetta (3.10) to design

The 2024 Nobel prize in chemistry has been awarded to David Baker, Demis Hassabis and John Jumper for their work on understanding the structure of proteins, which play vital roles in all living organisms. Hassabis and Jumper, of Google DeepMind, developed an artificial intelligence that predicts the structure of proteins. Baker, at the University of Washington in Seattle, has been recognised for his work on designing new proteins. Proteins are the molecules that make life happen. All of the key machinery of life is made of proteins, from the muscles that power us and the molecules that read and copy DNA to the antibodies that protect us from infections.

Rosetta is one of the leading algorithms for protein structure prediction today. It is a Monte Carlo energy minimization method requiring many random restarts to find structures with low energy. In this paper we present a resampling technique for structure prediction of small alpha/beta proteins using Rosetta. From an ini- tial round of Rosetta sampling, we learn properties of the energy landscape that guide a subsequent round of sampling toward lower-energy structures. Rather than attempt to fit the full energy landscape, we use feature selection methods--both L1-regularized linear regression and decision trees--to identify structural features that give rise to low energy.

J.K. Rowling worries that women are being erased due to transgender policies; reaction from Fox Nation host Tammy Bruce. Gamers, journalists and influencers argued over whether to buy a highly anticipated "Harry Potter" themed video game online. "Hogwarts Legacy," an action role-playing game set in the "Harry Potter" universe, is one of the most anticipated games of the year. Preorders for it have shot up, making it the top-selling game on download platform Steam. But some pundits asked what the political implications of buying the game would be, accusing author J.K. Rowling of being "transphobic."