Evaluation of Large Language Models for Discovery of Gene Set Function

Exploration of Gene Set Function Discovery Using Large Language Models: GPT-4 Excels Academic Background In functional genomics, gene set enrichment analysis is a critical methodology for understanding gene functions and their associated biological processes. However, existing enrichment analyses rely heavily on curated gene function databases, suc...

Overcoming the Preferred-Orientation Problem in Cryo-EM with Self-Supervised Deep Learning

Overcoming the Preferred-Orientation Problem in Single-Particle Cryo-EM: An Innovative Solution through Deep Learning Background Introduction In recent years, single-particle cryogenic electron microscopy (Single-Particle Cryo-EM) has become a core technique in structural biology due to its ability to resolve the atomic-resolution structures of bio...

Multiscale Footprints Reveal the Organization of Cis-Regulatory Elements

Multiscale Footprints Reveal the Role of Cis-Regulatory Elements in Cell Differentiation and Aging Background Introduction The regulation of gene expression is a key mechanism in cell fate determination and disease development, and cis-regulatory elements (CREs) play a crucial role in this process. CREs dynamically regulate gene expression by bindi...

Artificial Intelligence and Terrestrial Point Clouds for Forest Monitoring

Artificial Intelligence and Terrestrial LiDAR Point Clouds in Forest Monitoring: Academic Report Academic Background With the increasing importance of global climate change and forest resource management, precision forestry has become a key direction in modern forest management. Precision forestry relies on high-precision forest data collection and...

Multimodal Deep Learning Improves Recurrence Risk Prediction in Pediatric Low-Grade Gliomas

Application of Deep Learning in Postoperative Recurrence Prediction for Pediatric Low-Grade Gliomas Background Pediatric Low-Grade Gliomas (PLGGs) are one of the most common types of brain tumors in children, accounting for 30%-50% of all central nervous system tumors in children. Although the prognosis of PLGGs is relatively favorable, the risk of...

Learning Meshing from Delaunay Triangulation for 3D Shape Representation

Learning Meshing from Delaunay Triangulation for 3D Shape Representation Academic Background Surface reconstruction from point clouds is a long-standing problem in computer vision and graphics. Traditional implicit methods, such as Poisson surface reconstruction, compute an implicit function and extract the surface using the Marching Cubes algorith...