AIMC Topic: Computational Biology
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DSSGNN-PPI: A Protein-Protein Interactions prediction model based on Double Structure and Sequence graph neural networks.
Computers in biology and medicine
May 29, 2024
The process of experimentally confirming complex interaction networks among proteins is time-consuming and laborious. This study aims to address Protein-Protein Interactions (PPIs) prediction based on graph neural networks (GNN). A novel multilevel p...
Machine learning-derived immunosenescence index for predicting outcome and drug sensitivity in patients with skin cutaneous melanoma.
Genes and immunity
May 29, 2024
The functions of immunosenescence are closely related to skin cutaneous melanoma (SKCM). The aim of this study is to uncover the characteristics of immunosenescence index (ISI) to identify novel biomarkers and potential targets for treatment. Firstly...
Leveraging conformal prediction to annotate enzyme function space with limited false positives.
PLoS computational biology
May 29, 2024
Machine learning (ML) is increasingly being used to guide biological discovery in biomedicine such as prioritizing promising small molecules in drug discovery. In those applications, ML models are used to predict the properties of biological systems,...
Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy.
Frontiers in immunology
May 29, 2024
Cancer immunotherapy has witnessed rapid advancement in recent years, with a particular focus on neoantigens as promising targets for personalized treatments. The convergence of immunogenomics, bioinformatics, and artificial intelligence (AI) has pro...
On knowing a gene: A distributional hypothesis of gene function.
Cell systems
May 28, 2024
As words can have multiple meanings that depend on sentence context, genes can have various functions that depend on the surrounding biological system. This pleiotropic nature of gene function is limited by ontologies, which annotate gene functions w...
An artificial intelligence-assisted clinical framework to facilitate diagnostics and translational discovery in hematologic neoplasia.
EBioMedicine
May 28, 2024
BACKGROUND: The increasing volume and intricacy of sequencing data, along with other clinical and diagnostic data, like drug responses and measurable residual disease, creates challenges for efficient clinical comprehension and interpretation. Using ...
Protein-Protein Interfaces: A Graph Neural Network Approach.
International journal of molecular sciences
May 28, 2024
Protein-protein interactions (PPIs) are fundamental processes governing cellular functions, crucial for understanding biological systems at the molecular level. Compared to experimental methods for PPI prediction and site identification, computationa...
MoRF_ESM: Prediction of MoRFs in disordered proteins based on a deep transformer protein language model.
Journal of bioinformatics and computational biology
May 28, 2024
Molecular recognition features (MoRFs) are particular functional segments of disordered proteins, which play crucial roles in regulating the phase transition of membrane-less organelles and frequently serve as central sites in cellular interaction ne...
Integrated bioinformatics combined with machine learning to analyze shared biomarkers and pathways in psoriasis and cervical squamous cell carcinoma.
Frontiers in immunology
May 28, 2024
BACKGROUND: Psoriasis extends beyond its dermatological inflammatory manifestations, encompassing systemic inflammation. Existing studies have indicated a potential risk of cervical cancer among patients with psoriasis, suggesting a potential mechani...
MicroRNAs
HeLa Cells
Databases, Genetic
Psoriasis
Biomarkers, Tumor
Computational Biology
Female
Humans
Uterine Cervical Neoplasms
Gene Expression Regulation, Neoplastic
Carcinoma, Squamous Cell
Machine Learning
Signal Transduction
Gene Expression Profiling
Transcriptome
Protein Interaction Maps
Gene Regulatory Networks
Prediction of peptide hormones using an ensemble of machine learning and similarity-based methods.
Proteomics
May 27, 2024
Peptide hormones serve as genome-encoded signal transduction molecules that play essential roles in multicellular organisms, and their dysregulation can lead to various health problems. In this study, we propose a method for predicting hormonal pepti...
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