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...
Research Background Gene Regulatory Networks (GRNs) are crucial tools for understanding the complex biological processes within cells. They reveal the interactions between Transcription Factors (TFs) and target genes, thereby controlling gene transcription and regulating cellular behavior. With the advancement of single-cell RNA sequencing (scRNA-s...
In proteomics research, mass spectrometry (MS) is widely used to analyze changes in protein abundance and structure. However, protein quantification faces a critical challenge: many proteins share the same peptides (shared peptides), meaning these peptides appear in the sequences of multiple proteins. Traditional methods typically rely solely on un...
The advent of single-cell RNA sequencing (scRNA-seq) technology has provided unprecedented resolution for studying gene expression dynamics during cell development and differentiation. However, due to the complexity of biological processes, cell developmental trajectories under different conditions are often asymmetric, posing challenges for data i...
Single-cell RNA sequencing (scRNA-seq) technology enables high-throughput transcriptomic profiling at single-cell resolution, significantly advancing research in cell biology. However, a notable limitation of scRNA-seq is that it requires tissue dissociation, resulting in the loss of the original spatial location information of cells within tissues...
With the increasing availability of large-scale population biobanks, the potential of Whole Genome Sequencing (WGS) data in human health and disease research has been significantly enhanced. However, the massive computational and storage demands of WGS data pose significant challenges to research institutions, especially those with limited funding ...
Background Introduction In recent years, circular RNAs (circRNAs), as a novel class of non-coding RNA molecules, have played a significant role in the occurrence, development, and treatment of diseases. Due to their unique circular structure, circRNAs are resistant to degradation by nucleases, making them potential biomarkers and therapeutic target...
Single-cell RNA sequencing (scRNA-seq) technology has been widely applied in biological and medical research in recent years. It can reveal the transcriptomic information of individual cells, helping scientists better understand cellular heterogeneity and complexity. However, a common issue in scRNA-seq data is “dropout events,” which result in man...
Academic Background Drug-Target Interaction (DTI) prediction is a critical step in drug discovery, significantly reducing the cost and time of experimental screening. However, despite the advancements in deep learning that have improved the accuracy of DTI prediction, existing methods still face two major challenges: lack of generalizability and ne...
Anxiety Disorder Identification and Biomarker Detection Based on Subspace-Enhanced Hypergraph Neural Network Academic Background Anxiety Disorders (ADs) are prevalent mental health issues globally, affecting approximately 7.3% of the population. Patients with anxiety disorders typically exhibit excessive fear, worry, and related behavioral abnormal...