AIMC Topic: Computational Biology
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Exploring drug-target interaction prediction on cold-start scenarios via meta-learning-based graph transformer.
Methods (San Diego, Calif.)
Nov 15, 2024
Predicting drug-target interaction (DTI) is of great importance for drug discovery and development. With the rapid development of biological and chemical technologies, computational methods for DTI prediction are becoming a promising approach. Howeve...
MuSE: A deep learning model based on multi-feature fusion for super-enhancer prediction.
Computational biology and chemistry
Nov 15, 2024
Although bioinformatics-based methods accurately identify SEs (Super-enhancers), the results depend on feature design. It is foundational to representing biological sequences and automatically extracting their key features for improving SE identifica...
Identification of diagnostic genes and the miRNA‒mRNA‒TF regulatory network in human oocyte aging via machine learning methods.
Journal of assisted reproduction and genetics
Nov 14, 2024
PURPOSE: Oocyte aging is a significant factor in the negative reproductive outcomes of older women. However, the pathogenesis of oocyte aging remains unclear. This study aimed to identify the hub genes involved in oocyte aging via bioinformatics meth...
Visualization Methods for DNA Sequences: A Review and Prospects.
Biomolecules
Nov 14, 2024
The efficient analysis and interpretation of biological sequence data remain major challenges in bioinformatics. Graphical representation, as an emerging and effective visualization technique, offers a more intuitive method for analyzing DNA sequence...
deepBBQ: A Deep Learning Approach to the Protein Backbone Reconstruction.
Biomolecules
Nov 14, 2024
Coarse-grained models have provided researchers with greatly improved computational efficiency in modeling structures and dynamics of biomacromolecules, but, to be practically useful, they need fast and accurate conversion methods back to the all-ato...
Machine learning-driven discovery of novel therapeutic targets in diabetic foot ulcers.
Molecular medicine (Cambridge, Mass.)
Nov 14, 2024
BACKGROUND: To utilize machine learning for identifying treatment response genes in diabetic foot ulcers (DFU).
Human-like dissociations between confidence and accuracy in convolutional neural networks.
PLoS computational biology
Nov 14, 2024
Prior research has shown that manipulating stimulus energy by changing both stimulus contrast and variability results in confidence-accuracy dissociations in humans. Specifically, even when performance is matched, higher stimulus energy leads to high...
An experimental analysis of graph representation learning for Gene Ontology based protein function prediction.
PeerJ
Nov 14, 2024
Understanding protein function is crucial for deciphering biological systems and facilitating various biomedical applications. Computational methods for predicting Gene Ontology functions of proteins emerged in the 2000s to bridge the gap between the...
Identification of TXN and F5 as novel diagnostic gene biomarkers of the severe asthma based on bioinformatics and machine learning analysis.
Autoimmunity
Nov 12, 2024
Asthma poses a major threat to human health. The aim of this study was to identify genetic markers of severe asthma and analyze the relationship between key genes and immune infiltration. Differentially expressed genes (DEGs) were first screened by d...
Using bioinformatics and artificial intelligence to map the cyclin-dependent kinase 4/6 inhibitor biomarker landscape in breast cancer.
Future oncology (London, England)
Nov 12, 2024
A cyclin-dependent kinase 4/6 (CDK4/6) inhibitor combined with endocrine therapy is the standard-of-care for patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative advanced breast cancer. However, not all patients r...
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