Evolutionary Structure Modeling
PulseAugur coverage of Evolutionary Structure Modeling — every cluster mentioning Evolutionary Structure Modeling across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
-
OpenESM architecture outperforms GPTs in large-scale language modeling
Researchers have introduced OpenESM, a novel architecture for large-scale language modeling that integrates energy steering with token generation. This approach optimizes a latent state over an energy landscape before g…
-
SoftGene framework uses protein language models for gene set annotation
Researchers have developed SoftGene, a new framework that enhances gene set annotation using protein language models and a hybrid prompting scheme. This approach integrates protein sequence information with auxiliary co…
-
New PepLLM framework offers structured analysis of protein-peptide binding interfaces
Researchers have developed PepLLM, a new framework designed to analyze protein-peptide binding interfaces. Unlike previous methods that focused on classification or prediction, PepLLM generates structured, machine-reada…
-
Peking University releases open-source Claude Science alternative, OpenAI4S
Researchers from Peking University and Yuan Kong AI Agent Lab have released OpenAI4S, an open-source scientific research agent that mimics the capabilities of Anthropic's closed-source Claude Science. This new agent, av…
-
AI's "Bitter Lesson" Applies to Protein Structure Prediction, Researcher Says
Alex Rives, a researcher at Chan Zuckerberg Biohub, discussed Evolutionary Structure Modeling (ESM) on the Latent Space Podcast. He highlighted how the "bitter lesson" in AI, which emphasizes scaling up models and data,…
-
New framework AnnotateMissense predicts missense variant pathogenicity
Researchers have developed AnnotateMissense, a new framework for predicting the pathogenicity of missense genetic variants. This system integrates a wide array of data, including population frequency, evolutionary conse…
-
AMIEOD framework enhances object detection in low-light scenes
Researchers have developed AMIEOD, a novel framework designed to enhance object detection in low-illumination environments. This system jointly optimizes image enhancement and object detection tasks, leveraging a Multi-…
-
PRIME framework models proteins using physics-informed multiscale hierarchies
Researchers have developed PRIME, a novel framework for learning protein representations by modeling proteins as a nested family of five physically grounded structural graphs. This approach explicitly models hierarchica…