AIMC Topic: Molecular Sequence Annotation
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ProtNote: a multimodal method for protein-function annotation.
Bioinformatics (Oxford, England)
May 6, 2025
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...
GeOKG: geometry-aware knowledge graph embedding for Gene Ontology and genes.
Bioinformatics (Oxford, England)
Mar 29, 2025
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...
uHAF: a unified hierarchical annotation framework for cell type standardization and harmonization.
Bioinformatics (Oxford, England)
Mar 29, 2025
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...
DeepES: deep learning-based enzyme screening to identify orphan enzyme genes.
Bioinformatics (Oxford, England)
Mar 4, 2025
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...
MMnc: multi-modal interpretable representation for non-coding RNA classification and class annotation.
Bioinformatics (Oxford, England)
Mar 4, 2025
MOTIVATION: As the biological roles and disease implications of non-coding RNAs continue to emerge, the need to thoroughly characterize previously unexplored non-coding RNAs becomes increasingly urgent. These molecules hold potential as biomarkers an...
AtSubP-2.0: An integrated web server for the annotation of Arabidopsis proteome subcellular localization using deep learning.
The plant genome
Mar 1, 2025
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...
stAI: a deep learning-based model for missing gene imputation and cell-type annotation of spatial transcriptomics.
Nucleic acids research
Feb 27, 2025
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...
UniProt: the Universal Protein Knowledgebase in 2025.
Nucleic acids research
Jan 6, 2025
The aim of the UniProt Knowledgebase (UniProtKB; https://www.uniprot.org/) is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this publication, we describe o...
ASpdb: an integrative knowledgebase of human protein isoforms from experimental and AI-predicted structures.
Nucleic acids research
Jan 6, 2025
Alternative splicing is a crucial cellular process in eukaryotes, enabling the generation of multiple protein isoforms with diverse functions from a single gene. To better understand the impact of alternative splicing on protein structures, protein-p...
scGO: interpretable deep neural network for cell status annotation and disease diagnosis.
Briefings in bioinformatics
Nov 22, 2024
Machine learning has emerged as a transformative tool for elucidating cellular heterogeneity in single-cell RNA sequencing. However, a significant challenge lies in the "black box" nature of deep learning models, which obscures the decision-making pr...
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