AIMC Topic: Computational Biology
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PICNIC accurately predicts condensate-forming proteins regardless of their structural disorder across organisms.
Nature communications
Dec 11, 2024
Biomolecular condensates are membraneless organelles that can concentrate hundreds of different proteins in cells to operate essential biological functions. However, accurate identification of their components remains challenging and biased towards p...
Integration of bulk/scRNA-seq and multiple machine learning algorithms identifies PIM1 as a biomarker associated with cuproptosis and ferroptosis in abdominal aortic aneurysm.
Frontiers in immunology
Dec 11, 2024
BACKGROUND: Abdominal aortic aneurysm (AAA) is a serious life-threatening vascular disease, and its ferroptosis/cuproptosis markers have not yet been characterized. This study was aiming to identify markers associated with ferroptosis/cuproptosis in ...
An exploration into the diagnostic capabilities of microRNAs for myocardial infarction using machine learning.
Biology direct
Dec 10, 2024
BACKGROUND: MicroRNAs (miRNAs) have shown potential as diagnostic biomarkers for myocardial infarction (MI) due to their early dysregulation and stability in circulation after MI. Moreover, they play a crucial role in regulating adaptive and maladapt...
Integrating machine learning, bioinformatics and experimental verification to identify a novel prognostic marker associated with tumor immune microenvironment in head and neck squamous carcinoma.
Frontiers in immunology
Dec 10, 2024
Head and neck squamous carcinoma (HNSC), characterized by a high degree of malignancy, develops in close association with the tumor immune microenvironment (TIME). Therefore, identifying effective targets related to HNSC and TIME is of paramount impo...
circ2DGNN: circRNA-Disease Association Prediction via Transformer-Based Graph Neural Network.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Investigating the associations between circRNA and diseases is vital for comprehending the underlying mechanisms of diseases and formulating effective therapies. Computational prediction methods often rely solely on known circRNA-disease data, indire...
Hierarchical Hypergraph Learning in Association- Weighted Heterogeneous Network for miRNA- Disease Association Identification.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
MicroRNAs (miRNAs) play a significant role in cell differentiation, biological development as well as the occurrence and growth of diseases. Although many computational methods contribute to predicting the association between miRNAs and diseases, the...
An End-to-End Knowledge Graph Fused Graph Neural Network for Accurate Protein-Protein Interactions Prediction.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Protein-protein interactions (PPIs) are essential to understanding cellular mechanisms, signaling networks, disease processes, and drug development, as they represent the physical contacts and functional associations between proteins. Recent advances...
Generative Biomedical Event Extraction With Constrained Decoding Strategy.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Currently, biomedical event extraction has received considerable attention in various fields, including natural language processing, bioinformatics, and computational biomedicine. This has led to the emergence of numerous machine learning and deep le...
De Novo Drug Design by Multi-Objective Path Consistency Learning With Beam A Search.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Generating high-quality and drug-like molecules from scratch within the expansive chemical space presents a significant challenge in the field of drug discovery. In prior research, value-based reinforcement learning algorithms have been employed to g...
A Knowledge Graph-Based Method for Drug-Drug Interaction Prediction With Contrastive Learning.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Precisely predicting Drug-Drug Interactions (DDIs) carries the potential to elevate the quality and safety of drug therapies, protecting the well-being of patients, and providing essential guidance and decision support at every stage of the drug deve...
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