AIMC Topic: Computational Biology
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Identification and validation of immune and diagnostic biomarkers for interstitial cystitis/painful bladder syndrome by integrating bioinformatics and machine-learning.
Frontiers in immunology
Jan 23, 2025
BACKGROUND: The etiology of interstitial cystitis/painful bladder syndrome (IC/BPS) remains elusive, presenting significant challenges in both diagnosis and treatment. To address these challenges, we employed a comprehensive approach aimed at identif...
The tumour histopathology "glossary" for AI developers.
PLoS computational biology
Jan 23, 2025
The applications of artificial intelligence (AI) and deep learning (DL) are leading to significant advances in cancer research, particularly in analysing histopathology images for prognostic and treatment-predictive insights. However, effective trans...
DisDock: A Deep Learning Method for Metal Ion-Protein Redocking.
Proteins
Jan 22, 2025
The structures of metalloproteins are essential for comprehending their functions and interactions. The breakthrough of AlphaFold has made it possible to predict protein structures with experimental accuracy. However, the type of metal ion that a met...
Identification of lipid metabolism-related gene markers and construction of a diagnostic model for multiple sclerosis: An integrated analysis by bioinformatics and machine learning.
Analytical biochemistry
Jan 22, 2025
BACKGROUND: Multiple sclerosis (MS) is an autoimmune inflammatory disorder that causes neurological disability. Dysregulated lipid metabolism contributes to the pathogenesis of MS. This study aimed to identify lipid metabolism-related gene markers an...
Deep learning methods for proteome-scale interaction prediction.
Current opinion in structural biology
Jan 22, 2025
Proteome-scale interaction prediction is essential for understanding protein functions and disease mechanisms. Traditional experimental methods are often limited by scale and complexity, driving the need for computational approaches. Deep learning ha...
Joint embedding-classifier learning for interpretable collaborative filtering.
BMC bioinformatics
Jan 22, 2025
BACKGROUND: Interpretability is a topical question in recommender systems, especially in healthcare applications. An interpretable classifier quantifies the importance of each input feature for the predicted item-user association in a non-ambiguous f...
MVGNN-PPIS: A novel multi-view graph neural network for protein-protein interaction sites prediction based on Alphafold3-predicted structures and transfer learning.
International journal of biological macromolecules
Jan 21, 2025
Protein-protein interactions (PPI) are crucial for understanding numerous biological processes and pathogenic mechanisms. Identifying interaction sites is essential for biomedical research and targeted drug development. Compared to experimental metho...
Paying attention to the SARS-CoV-2 dialect : a deep neural network approach to predicting novel protein mutations.
Communications biology
Jan 21, 2025
Predicting novel mutations has long-lasting impacts on life science research. Traditionally, this problem is addressed through wet-lab experiments, which are often expensive and time consuming. The recent advancement in neural language models has pro...
MCTASmRNA: A deep learning framework for alternative splicing events classification.
International journal of biological macromolecules
Jan 20, 2025
Alternative splicing (AS) plays crucial post-transcriptional gene function regulation roles in eukaryotic. Despite progress in studying AS at the RNA level, existing methods for AS event identification face challenges such as inefficiency, lengthy pr...
Biocomputing at the crossroad between emulating artificial intelligence and cellular supremacy.
Current opinion in biotechnology
Jan 20, 2025
Biocomputation aims to create sophisticated biological systems capable of addressing important problems in (bio)medicine with a machine-like precision. At present, computational gene networks engineered by single- or multi-layered assembly of DNA-, R...
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