AIMC Topic: Computational Biology
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A comprehensive analysis of m6A/m7G/m5C/m1A-related gene expression and immune infiltration in liver ischemia-reperfusion injury by integrating bioinformatics and machine learning algorithms.
European journal of medical research
Jun 13, 2024
BACKGROUND: Liver ischemia-reperfusion injury (LIRI) is closely associated with immune infiltration, which commonly occurs after liver surgery, especially liver transplantation. Therefore, it is crucial to identify the genes responsible for LIRI and ...
The attentive reconstruction of objects facilitates robust object recognition.
PLoS computational biology
Jun 13, 2024
Humans are extremely robust in our ability to perceive and recognize objects-we see faces in tea stains and can recognize friends on dark streets. Yet, neurocomputational models of primate object recognition have focused on the initial feed-forward p...
The Prediction of Recombination Hotspot Based on Automated Machine Learning.
Journal of molecular biology
Jun 12, 2024
Meiotic recombination plays a pivotal role in genetic evolution. Genetic variation induced by recombination is a crucial factor in generating biodiversity and a driving force for evolution. At present, the development of recombination hotspot predict...
DP-site: A dual deep learning-based method for protein-peptide interaction site prediction.
Methods (San Diego, Calif.)
Jun 12, 2024
BACKGROUND: Protein-peptide interaction prediction is an important topic for several applications including various biological processes, understanding drug discovery, protein function abnormal cellular behaviors, and treating diseases. Over the year...
Protein embeddings predict binding residues in disordered regions.
Scientific reports
Jun 12, 2024
The identification of protein binding residues helps to understand their biological processes as protein function is often defined through ligand binding, such as to other proteins, small molecules, ions, or nucleotides. Methods predicting binding re...
SEP-AlgPro: An efficient allergen prediction tool utilizing traditional machine learning and deep learning techniques with protein language model features.
International journal of biological macromolecules
Jun 11, 2024
Allergy is a hypersensitive condition in which individuals develop objective symptoms when exposed to harmless substances at a dose that would cause no harm to a "normal" person. Most current computational methods for allergen identification rely on ...
Machine learning integrative approaches to advance computational immunology.
Genome medicine
Jun 11, 2024
The study of immunology, traditionally reliant on proteomics to evaluate individual immune cells, has been revolutionized by single-cell RNA sequencing. Computational immunologists play a crucial role in analysing these datasets, moving beyond tradit...
Drug repurposing based on the DTD-GNN graph neural network: revealing the relationships among drugs, targets and diseases.
BMC genomics
Jun 11, 2024
MOTIVATION: The rational modelling of the relationship among drugs, targets and diseases is crucial for drug retargeting. While significant progress has been made in studying binary relationships, further research is needed to deepen our understandin...
Sequence homology score-based deep fuzzy network for identifying therapeutic peptides.
Neural networks : the official journal of the International Neural Network Society
Jun 10, 2024
The detection of therapeutic peptides is a topic of immense interest in the biomedical field. Conventional biochemical experiment-based detection techniques are tedious and time-consuming. Computational biology has become a useful tool for improving ...
Thinking Beyond Disease Silos: Dysregulated Genes Common in Tuberculosis and Lung Cancer as Identified by Systems Biology and Machine Learning.
Omics : a journal of integrative biology
Jun 10, 2024
The traditional way of thinking about human diseases across clinical and narrow phenomics silos often masks the underlying shared molecular substrates across human diseases. One Health and planetary health fields particularly address such complexitie...
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