Efficient Storage and Regression Computation for Population-Scale Genome Sequencing Studies

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 ...

Predicting circRNA–Disease Associations with Shared Units and Multi-Channel Attention Mechanisms

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...

ACImpute: A Constraint-Enhancing Smooth-Based Approach for Imputing Single-Cell RNA Sequencing Data

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...

APNet: An Explainable Sparse Deep Learning Model to Discover Differentially Active Drivers of Severe COVID-19

Academic Background The COVID-19 pandemic has had a significant impact on global public health systems. Although the pandemic has somewhat subsided, its complex immunopathological mechanisms, long-term sequelae (such as “long COVID”), and the potential for similar threats in the future continue to drive in-depth research. Severe COVID-19 cases are ...

SP-DTI: Subpocket-Informed Transformer for Drug–Target Interaction Prediction

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...

Synergistic Combination of Perphenazine and Temozolomide Suppresses Patient-Derived Glioblastoma Tumorspheres

Academic Background Glioblastoma (GBM) is a highly malignant primary brain tumor. Despite current standard treatments such as surgical resection, radiotherapy, and chemotherapy, the prognosis remains extremely poor, with a median survival of only 14.6 months. Traditional treatments often fail to completely eradicate the tumor and are prone to recur...

Glutamate Dehydrogenase 1-Catalytic Glutaminolysis Feedback Activates EGFR/PI3K/AKT Pathway and Reprograms Glioblastoma Metabolism

Academic Background Glioblastoma (GBM) is one of the most aggressive and heterogeneous central nervous system tumors, with an extremely poor prognosis. Despite the emergence of novel therapies such as anti-angiogenic treatments and immunotherapy in recent years, the survival period of GBM patients remains very limited. GBM cells exhibit unique meta...

EVA1-Antibody Drug Conjugate as a Novel Therapeutic Strategy for Eliminating Glioblastoma-Initiating Cells

Background Introduction Glioblastoma (GBM) is one of the most aggressive brain cancers, with a median survival of approximately 15 months. Despite the use of multimodal treatments including surgery, chemotherapy, and radiotherapy, the overall survival rate of GBM patients has not significantly improved over the past few decades. Recent studies have...

ROR1 Facilitates Glioblastoma Growth via Stabilizing GRB2 to Promote c-fos Expression in Glioma Stem Cells

Academic Background Glioblastoma (GBM) is the most common and aggressive primary brain tumor, with significant treatment challenges and a poor prognosis. Despite advancements in surgery, chemotherapy, and radiotherapy, the 5-year survival rate for GBM patients remains below 4%. The recurrence and therapeutic resistance of GBM are primarily attribut...

Glioma–Astrocyte Connexin43 Confers Temozolomide Resistance Through Activation of the E2F1/ERCC1 Axis

Study on Connexin43-Mediated Temozolomide Resistance in Glioma through Activation of the E2F1/ERCC1 Axis Academic Background Glioma is the most common and fatal tumor of the central nervous system, with temozolomide (TMZ) being the standard treatment. However, TMZ therapy often leads to tumor recurrence and drug resistance, severely limiting its ef...