Background and Significance Object re-identification (Re-ID) is an essential task in computer vision aimed at identifying specific objects across different times and scenes. Driven by deep learning, particularly convolutional neural networks (CNNs), this field has made significant strides. However, the emergence of vision transformers has opened ne...
Deep Learning-Driven Protein Design: Generating Functional Protein Sequences Using Conditional Diffusion Models Proteins are at the core of life sciences research and applications, offering countless possibilities due to their diversity and functional complexity. With advancements in deep learning technologies, protein design has reached a new pinn...
Benchmarking Gene Set Scoring Tools for Single-Cell ATAC-seq Data Authors: Xi Wang, Qiwei Lian, Haoyu Dong, Shuo Xu, Yaru Su, Xiaohui Wu Affiliations: Pasteurien College (Soochow University Medical College), Department of Automation, Xiamen University, School of Mathematics and Computer Science, Fuzhou University Corresponding Author: xhwu@suda.edu...
Protein Structure Prediction: Challenges, Progress, and Shifts in Research Paradigms Protein structure prediction is an important interdisciplinary research topic that has attracted researchers from various fields including biochemistry, medicine, physics, mathematics, and computer science. Researchers have adopted multiple research paradigms to so...
Smart Independent Component Analysis (SMART ICA): An Innovative Method for Extracting Accurate Brain Functional Networks Background Introduction In brain science research, Functional Networks (FNs) show great potential for understanding human brain function by exploring the integration and interaction relationships between different brain regions. ...
Computational Modeling of Prefrontal-Cingulate Coupling: Exploring Its Role in Balancing Emotion and Cognition Academic Background In recent years, emotional processing and cognitive control, which are crucial for maintaining normal social behavior and executive function, have attracted widespread attention. This study explores how the balance betw...
Academic Report Research Background In recent years, there has been growing interest in individual differences within the fields of psychology and cognitive neuroscience. However, many studies face a replication crisis, particularly evident in research exploring brain-behavior correlations. A key element for replicable individual differences resear...
Background Introduction In the human visual system, the understanding and navigation of natural scenes are exceptionally outstanding in terms of both complexity and efficiency. This process requires the transformation of incoming sensory information into visual features ranging from low-level to high-level, such as edges, object parts, and objects ...
Innovative Fusion in Neuron Classification: Shared Information from Human and Mouse Electrophysiological Data The scientific community has long faced significant challenges in neuron classification. Accurate classification of neurons is crucial for understanding brain function in both healthy and diseased states. This study, led by Ofek Ophir, Orit...
MRQA: Addressing the Widespread Problem of MRI Protocol Non-Compliance Background In recent years, large-scale neuroimaging datasets have played a crucial role in studying brain-behavior relationships, such as the Alzheimer’s Disease Neuroimaging Initiative (ADNI), Human Connectome Project (HCP), and Adolescent Brain Cognitive Development (ABCD) st...