Cancer remains one of the leading causes of death globally. Despite significant advancements in immunotherapy in recent years, such as the successful application of chimeric antigen receptor T-cell (CAR-T) therapy and antibody-drug conjugates (ADCs), the effective identification of cancer-specific surface protein targets remains a major challenge i...

Immune cells undergo cytokine-driven polarization in response to various stimuli, which alters their transcriptional profiles and functional states. This dynamic process plays a central role in immune responses in both health and disease. However, there has been a lack of systematic methods to assess cytokine-driven polarization in single-cell RNA ...

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...

Academic Background and Problem Introduction In the field of education today, Public Speaking Anxiety (PSA) is a widespread phenomenon, especially among non-native language learners. This anxiety not only affects learners’ ability to express themselves but may also hinder their personal development. To help learners overcome this issue, researchers...

Academic Background In the fields of machine learning and neural networks, continual learning is an important research direction. The goal of continual learning is to enable models to continuously learn new knowledge across a series of tasks while avoiding forgetting previously acquired knowledge. However, existing continual learning methods face a...

Theory and Application of Complex Quantized Minimum Error Entropy with Fiducial Points: Breakthroughs in Model Regression Academic Background In the fields of machine learning and signal processing, the presence of non-Gaussian noise often adversely affects model performance. Although the traditional Mean Squared Error (MSE) is theoretically and co...