Cross-species modeling of plant genomes at single-nucleotide resolution using a pretrained DNA language model

A Milestone in Cross-Species Modeling of Plant Genomes: Creation and Breakthrough Application of the PlantCaduceus DNA Language Model I. Academic Background and Research Motivation In the past two decades, with the rapid development of high-throughput sequencing technology, over 1,000 plant genomes have been published, and this number is expected t...

Amortized Template Matching of Molecular Conformations from Cryoelectron Microscopy Images Using Simulation-Based Inference

Accelerating Single-Molecule Structure Identification with Simulation-Based Inference — Research Report on “Amortized Template Matching of Molecular Conformations from Cryoelectron Microscopy Images using Simulation-Based Inference” Research Background and Significance In the fields of molecular biology and structural biology, understanding how bio...

DeepRNA-Twist: Language-Model-Guided RNA Torsion Angle Prediction with Attention-Inception Network

1. Academic Background and Research Motivation With the rapid development of life sciences and bioinformatics, research into RNA molecular structure and function has become a hot topic. RNA is not merely a carrier of genetic information, but also plays critical roles in regulation, catalysis, and various physiological processes. The three-dimension...

An Enhanced Framework for Real-Time Dense Crowd Abnormal Behavior Detection Using YOLOv8

Academic Background With the increasing demand for public safety, especially during large-scale religious events such as the Hajj pilgrimage, abnormal behavior detection in dense crowds has become a critical issue. Existing detection methods often perform poorly under complex conditions such as occlusion, illumination variations, and uniform attire...

A Comprehensive Survey of Loss Functions and Metrics in Deep Learning

Deep Learning, as a crucial branch of artificial intelligence, has achieved significant progress in recent years across various fields such as computer vision and natural language processing. However, the success of deep learning largely depends on the choice of loss functions and performance metrics. Loss functions are used to measure the differen...

Challenges in Detecting Security Threats in WoT: A Systematic Literature Review

With the rapid development of the Internet of Things (IoT) and Web of Things (WoT), security issues have become increasingly prominent. In particular, the frequent occurrence of Denial of Service (DoS) attacks has made the security of WoT systems an urgent problem to be addressed. WoT achieves seamless connectivity between IoT devices and the inter...

Deep Learning-Based Multi-Modal Data Integration Enhancing Breast Cancer Disease-Free Survival Prediction

Breast cancer is one of the most common malignancies among women worldwide. Although early intervention and appropriate treatment have significantly improved patient survival rates, approximately 30% of cases still experience recurrence and distant metastasis, resulting in a 5-year survival rate of less than 23%. Traditional clinical prediction met...

Multi-Modal Interpretable Representation for Non-Coding RNA Classification and Class Annotation

Non-coding RNAs (ncRNAs) play critical roles in cellular processes and disease development. Although genome sequencing projects have revealed a vast number of non-coding genes, the functional classification of ncRNAs remains a complex and challenging issue. The diversity, complexity, and functionality of ncRNAs make them important subjects in biome...

DeepES: Deep Learning-Based Enzyme Screening for Identifying Orphan Enzyme Genes

Academic Background With the rapid advancement of sequencing technology, scientists have been able to obtain a vast amount of protein sequence data, including many enzyme sequences. However, despite the establishment of large enzyme databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and BRENDA, sequence information for many enzyme...

CryoTEN: Efficiently Enhancing Cryo-EM Density Maps Using Transformers

Academic Background Cryogenic Electron Microscopy (Cryo-EM) is a crucial experimental technique for determining the structures of macromolecules such as proteins. However, the effectiveness of Cryo-EM is often hindered by noise and missing density values caused by experimental conditions such as low contrast and conformational heterogeneity. Althou...