A Programmable Environment for Shape Optimization and Shapeshifting Problems

Research on Programmable Shape Optimization and Deformation Problems: Development and Application of the Morpho Environment Academic Background Soft materials play a crucial role in the fields of science and engineering, particularly in areas such as soft robotics, structured fluids, biological materials, and particulate media. These materials unde...

Approaching Coupled-Cluster Accuracy for Molecular Electronic Structures with Multi-Task Learning

Machine Learning Boosts Quantum Chemistry: Predicting Molecular Electronic Structures Approaching Coupled-Cluster Accuracy Academic Background In physics, chemistry, and materials science, computational methods are key tools for uncovering the mechanisms behind diverse physical phenomena and accelerating materials design. However, quantum chemistry...

A Spatiotemporal Style Transfer Algorithm for Dynamic Visual Stimulus Generation

Research Report on the Spatiotemporal Style Transfer Algorithm for Dynamic Visual Stimulus Generation Academic Background The encoding and processing of visual information has been a significant focus in the fields of neuroscience and vision science. With the rapid development of deep learning techniques, investigating the similarities between arti...

Mapping the Gene Space at Single-Cell Resolution with Gene Signal Pattern Analysis

Mapping the Gene Space at Single-Cell Resolution: A Study on Gene Signal Pattern Analysis (GSPA) Academic Background Single-cell RNA sequencing (scRNA-seq) technology has made significant progress in biological research in recent years, particularly in revealing the organizational structure of the cellular state space. However, although many comput...

Spatial Modeling Algorithms for Reactions and Transport in Biological Cells

Research on Spatial Modeling Algorithms for Cellular Signaling Reactions and Transport Background Biological cells achieve their functions through complex biochemical reaction networks. These networks exhibit significant spatiotemporal dynamics, with pronounced spatial compartmentalization across different regions and subcellular structures. Howeve...

A Simulated Annealing Algorithm for Randomizing Weighted Networks

Research on Weighted Network Randomization Based on Simulated Annealing Algorithm Background Introduction In the field of neuroscience, connectomics is an important branch for studying the structure and function of brain neural networks. With the development of modern imaging technologies, researchers are able to acquire a wealth of biologically me...

A Scalable Framework for Learning the Geometry-Dependent Solution Operators of Partial Differential Equations

Introduction In recent years, solving partial differential equations (PDEs) using numerical methods has played a significant role in various fields such as engineering and medicine. These methods have shown remarkable effectiveness in applications like topology and design optimization as well as clinical prognostication. However, the high computati...

Comprehensive Prediction and Analysis of Human Protein Essentiality Based on a Pretrained Large Language Model

Comprehensive Prediction and Analysis of Human Protein Essentiality Based on a Pretrained Large Language Model Academic Background Human Essential Proteins (HEPs) are crucial for individual survival and development. However, experimental methods for identifying HEPs are often costly, time-consuming, and labor-intensive. Additionally, existing compu...

A Deep Learning Approach for Rational Ligand Generation with Toxicity Control

Latest Research on Deep Learning Applied to Target Protein Ligand Generation: Proposal and Validation of the DeepBlock Framework Background and Research Problem In the drug discovery process, finding ligand molecules that bind to specific proteins has always been a core objective. However, current virtual screening methods are often limited by the ...

Enabling efficient analysis of biobank-scale data with genotype representation graphs

Research Based on Genotype Representation Graph (GRG): A New Framework to Enhance Biobank-Scale Data Analysis Efficiency Academic Background and Research Motivation With the rapid advancement of sequencing technologies, the collection of large-scale genomic data has become increasingly common, especially in the field of human disease association st...