Alternative polyadenylation (APA) is a major driver of transcriptome diversity in human cells. Here, we use deep learning to predict APA from DNA sequence alone. We trained our model (APARENT, APA REgression NeT) on isoform expression data from over ...
BACKGROUND: Normal tissue samples are often employed as a control for understanding disease mechanisms, however, collecting matched normal tissues from patients is difficult in many instances. In cancer research, for example, the open cancer resource...
BACKGROUND: Intervertebral disc degeneration (IVDD) is a primary cause of chronic low back pain, significantly impacting quality of life and healthcare systems globally. Despite its prevalence, the molecular mechanisms underlying IVDD remain unclear,...
BACKGROUND: Glioblastoma (GBM) presents a significant clinical challenge due to its aggressive nature and extensive heterogeneity. Tumor purity, the proportion of malignant cells within a tumor, is an important covariate for understanding the disease...
MOTIVATION: Clustering cells into subpopulations is one of the most crucial tasks in single-cell RNA sequencing (scRNA-seq) data analysis, which provides support for biological research at cellular level. With the development of graph neural networks...
BACKGROUND: The molecular and genetic mechanisms underlying vascular calcification remain unclear. This study aimed to determine the differences in calcification marker-related gene expression in macrophages.
Platinum-based therapy is an integral part of the standard treatment for ovarian cancer. However, despite extensive research spanning several decades, the identification of dependable predictive biomarkers for platinum response in clinical practice h...
Hepatitis B Virus-associated membranous nephropathy (HBV-MN) significantly impacts renal health, particularly in areas with high HBV prevalence. Understanding the molecular mechanisms underlying HBV-MN is crucial for developing effective therapeutic ...
Correcting for confounding variables is often overlooked when computing RNA-RNA correlations, even though it can profoundly affect results. We introduce CorrAdjust, a method for identifying and correcting such hidden confounders. CorrAdjust selects a...
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