AIMC Topic: Computational Biology

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Human essential gene identification based on feature fusion and feature screening.

IET systems biology Nov 22, 2024
Essential genes are necessary to sustain the life of a species under adequate nutritional conditions. These genes have attracted significant attention for their potential as drug targets, especially in developing broad-spectrum antibacterial drugs. H...
Humans Machine Learning Algorithms Computational Biology Cell Line, Tumor Genes, Essential ROC Curve
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Utilizing integrated bioinformatics and machine learning approaches to elucidate biomarkers linking sepsis to fatty acid metabolism-associated genes.

Scientific reports Nov 22, 2024
Sepsis, characterized as a systemic inflammatory response triggered by the invasion of pathogens, represents a continuum that may escalate from mild systemic infection to severe sepsis, potentially resulting in septic shock and multiple organ dysfunc...
Computational Biology Lipid Metabolism Fatty Acids Gene Expression Profiling Sepsis Humans Gene Regulatory Networks Machine Learning Biomarkers
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Deep multiple instance learning on heterogeneous graph for drug-disease association prediction.

Computers in biology and medicine Nov 21, 2024
Drug repositioning offers promising prospects for accelerating drug discovery by identifying potential drug-disease associations (DDAs) for existing drugs and diseases. Previous methods have generated meta-path-augmented node or graph embeddings for ...
Humans Neural Networks, Computer Drug Repositioning Deep Learning Computational Biology
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Accurate RNA 3D structure prediction using a language model-based deep learning approach.

Nature methods Nov 21, 2024
Accurate prediction of RNA three-dimensional (3D) structures remains an unsolved challenge. Determining RNA 3D structures is crucial for understanding their functions and informing RNA-targeting drug development and synthetic biology design. The stru...
RNA Nucleic Acid Conformation Computational Biology Software Models, Molecular Humans Deep Learning
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Leveraging Bioinformatics and Machine Learning for Identifying Prognostic Biomarkers and Predicting Clinical Outcomes in Lung Adenocarcinoma.

Genes Nov 21, 2024
There exist significant challenges for lung adenocarcinoma (LUAD) due to its poor prognosis and limited treatment options, particularly in the advanced stages. It is crucial to identify genetic biomarkers for improving outcome predictions and guidin...
Kaplan-Meier Estimate Male Adenocarcinoma of Lung Prognosis Protein Interaction Maps Lung Neoplasms Computational Biology Female Humans Biomarkers, Tumor Gene Expression Regulation, Neoplastic Machine Learning
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Deep neural networks for endemic measles dynamics: Comparative analysis and integration with mechanistic models.

PLoS computational biology Nov 21, 2024
Measles is an important infectious disease system both for its burden on public health and as an opportunity for studying nonlinear spatio-temporal disease dynamics. Traditional mechanistic models often struggle to fully capture the complex nonlinear...
Humans Neural Networks, Computer Forecasting Wales Endemic Diseases Measles England Computational Biology Disease Outbreaks Epidemiological Models
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MERIT: Accurate Prediction of Multi Ligand-binding Residues with Hybrid Deep Transformer Network, Evolutionary Couplings and Transfer Learning.

Journal of molecular biology Nov 20, 2024
Multi-ligand binding residues (MLBRs) are amino acids in protein sequences that interact with multiple different ligands that include proteins, peptides, nucleic acids, and a variety of small molecules. MLBRs are implicated in a number of cellular fu...
Machine Learning Software Deep Learning Humans Neural Networks, Computer Databases, Protein Protein Binding Ligands Computational Biology Binding Sites Proteins
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A combined deep learning framework for mammalian m6A site prediction.

Cell genomics Nov 20, 2024
N-methyladenosine (m6A) is the most prevalent chemical modification in eukaryotic mRNAs and plays key roles in diverse cellular processes. Precise localization of m6A sites is thus critical for characterizing the functional roles of m6A in various co...
Mammals Adenosine Neural Networks, Computer Animals Computational Biology RNA, Messenger Deep Learning Humans
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Learning patterns of HIV-1 resistance to broadly neutralizing antibodies with reduced subtype bias using multi-task learning.

PLoS computational biology Nov 20, 2024
The ability to predict HIV-1 resistance to broadly neutralizing antibodies (bnAbs) will increase bnAb therapeutic benefits. Machine learning is a powerful approach for such prediction. One challenge is that some HIV-1 subtypes in currently available ...
Epitopes Antibodies, Neutralizing HIV Antibodies Broadly Neutralizing Antibodies HIV-1 Humans HIV Infections Computational Biology Machine Learning
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A multi-perspective deep learning framework for enhancer characterization and identification.

Computational biology and chemistry Nov 19, 2024
Enhancers are vital elements in the genome that boost the transcriptional activity of neighboring genes and are essential in regulating cell-specific gene expression. Therefore, accurately identifying and characterizing enhancers is essential for com...
Computational Biology Enhancer Elements, Genetic Humans Deep Learning Neural Networks, Computer
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