We introduce ChromActivity, a computational framework for predicting and annotating regulatory activity across the genome through integration of multiple epigenomic maps and various functional characterization datasets. ChromActivity generates genome...
SUMMARY: In single-cell transcriptomics, inconsistent cell type annotations due to varied naming conventions and hierarchical granularity impede data integration, machine learning applications, and meaningful evaluations. To address this challenge, w...
Spatial transcriptomics technology has revolutionized our understanding of cellular systems by capturing RNA transcript levels in their original spatial context. Single-cell spatial transcriptomics (scST) offers single-cell resolution expression leve...
BACKGROUND: Alterations of metabolism, including changes in mitochondrial metabolism as well as glutathione (GSH) metabolism are a well appreciated hallmark of many cancers. Mitochondrial GSH (mGSH) transport is a poorly characterized aspect of GSH m...
MOTIVATION: Leveraging deep learning for the representation learning of Gene Ontology (GO) and Gene Ontology Annotation (GOA) holds significant promise for enhancing downstream biological tasks such as protein-protein interaction prediction. Prior ap...
The organization of subcellular components in a cell is critical for its function and studying cellular processes, protein-protein interactions, identifying potential drug targets, network analysis, and other systems biology mechanisms. Determining p...
MOTIVATION: Progress in sequencing technology has led to determination of large numbers of protein sequences, and large enzyme databases are now available. Although many computational tools for enzyme annotation were developed, sequence information i...
BACKGROUND AND OBJECTIVE: The Gene Ontology (GO) project has been pivotal in providing a structured framework for characterizing genes and annotating them to specific biological concepts. While traditional gene annotation primarily focuses on mapping...
SUMMARY: Currently available and frequently used tools for annotating antibiotic resistance genes (ARGs) in genomes and metagenomes provide results using inconsistent nomenclature. This makes the comparison of different ARG annotation outputs challen...
MOTIVATION: Understanding the protein sequence-function relationship is essential for advancing protein biology and engineering. However, <1% of known protein sequences have human-verified functions. While deep-learning methods have demonstrated prom...