Identifying the regulatory effects of noncoding variants presents a significant challenge. Recently, the accumulation of epigenomic profiling data in wheat has provided an opportunity to model the functional impacts of these variants. In this study, ...
The identification of cancer driver genes is crucial for understanding the complex processes involved in cancer development, progression, and therapeutic strategies. Multi-omics data and biological networks provided by numerous databases enable the a...
microRNAs (miRNAs) are central post-transcriptional gene expression regulators in healthy and diseased states. Despite decades of effort, deciphering miRNA targets remains challenging, leading to an incomplete miRNA interactome and partially elucidat...
The selection of biomarker panels in omics data, challenged by numerous molecular features and limited samples, often requires the use of machine learning methods paired with wrapper feature selection techniques, like genetic algorithms. They test va...
Identifying phage-host interactions (PHIs) is a crucial step in developing phage therapy, which is the promising solution to addressing the issue of antibiotic resistance in superbugs. However, the lifestyle of phages, which strongly depends on their...
Reusing massive collections of publicly available biomedical data can significantly impact knowledge discovery. However, these public samples and studies are typically described using unstructured plain text, hindering the findability and further reu...
Cell type annotation is a critical step in analyzing single-cell RNA sequencing (scRNA-seq) data. A large number of deep learning (DL)-based methods have been proposed to annotate cell types of scRNA-seq data and have achieved impressive results. How...
Advances in three-dimensional (3D) genomics have revealed the spatial characteristics of chromatin interactions in gene expression regulation, which is crucial for understanding molecular mechanisms in biological processes. High-throughput technologi...
The interactions between transcription factors (TFs) and the target genes could provide a basis for constructing gene regulatory networks (GRNs) for mechanistic understanding of various biological complex processes. From gene expression data, particu...
Ribosome profiling (Ribo-seq) provides transcriptome-wide insights into protein synthesis dynamics, yet its analysis poses challenges, particularly for nonbioinformatics researchers. Large language model-based chatbots offer promising solutions by le...
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