AIMC Topic: Computational Biology

Clear Filters Showing 391 to 400 of 4266 articles

Hierarchical Graph Transformer With Contrastive Learning for Gene Regulatory Network Inference.

IEEE journal of biomedical and health informatics Jan 7, 2025
Gene regulatory networks (GRNs) are crucial for understanding gene regulation and cellular processes. Inferring GRNs helps uncover regulatory pathways, shedding light on the regulation and development of cellular processes. With the rise of high-thro...
Machine Learning Algorithms Humans Neural Networks, Computer Gene Regulatory Networks Computational Biology
View on PubMed DOI

MiRS-HF: A Novel Deep Learning Predictor for Cancer Classification and miRNA Expression Patterns.

IEEE journal of biomedical and health informatics Jan 7, 2025
Cancer classification and biomarker identification are crucial for guiding personalized treatment. To make effective use of miRNA associations and expression data, we have developed a deep learning model for cancer classification and biomarker identi...
Humans Algorithms Biomarkers, Tumor MicroRNAs Deep Learning Computational Biology Neoplasms Gene Expression Profiling
View on PubMed DOI

Self-Supervised Contrastive Learning on Attribute and Topology Graphs for Predicting Relationships Among lncRNAs, miRNAs and Diseases.

IEEE journal of biomedical and health informatics Jan 7, 2025
Exploring associations between long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and diseases is crucial for disease prevention, diagnosis and treatment. While determining these relationships experimentally is resource-intensive and time-consuming, ...
Disease RNA, Long Noncoding Supervised Machine Learning Humans Computational Biology Algorithms MicroRNAs
View on PubMed DOI

Deep Drug Synergy Prediction Network Using Modified Triangular Mutation-Based Differential Evolution.

IEEE journal of biomedical and health informatics Jan 7, 2025
Drug combination therapy is crucial in cancer treatment, but accurately predicting drug synergy remains a challenge due to the complexity of drug combinations. Machine learning and deep learning models have shown promise in drug combination predictio...
Humans Algorithms Computational Biology Mutation Drug Synergism Neoplasms Deep Learning
View on PubMed DOI

SequenceCraft: machine learning-based resource for exploratory analysis of RNA-cleaving deoxyribozymes.

BMC bioinformatics Jan 6, 2025
BACKGROUND: Deoxyribozymes or DNAzymes represent artificial short DNA sequences bearing many catalytic properties. In particular, DNAzymes able to cleave RNA sequences have a huge potential in gene therapy and sequence-specific analytic detection of ...
DNA, Catalytic Machine Learning Computational Biology RNA
View on PubMed DOI

Integrating bioinformatics and machine learning to identify AhR-related gene signatures for prognosis and tumor microenvironment modulation in melanoma.

Frontiers in immunology Jan 6, 2025
BACKGROUND: The Aryl Hydrocarbon Receptor (AhR) pathway significantly influences immune cell regulation, impacting the effectiveness of immunotherapy and patient outcomes in melanoma. However, the specific downstream targets and mechanisms by which A...
Computational Biology Transcriptome Databases, Genetic Skin Neoplasms Basic Helix-Loop-Helix Transcription Factors Prognosis Lymphocytes, Tumor-Infiltrating Animals Gene Expression Regulation, Neoplastic Mice Tumor Microenvironment Receptors, Aryl Hydrocarbon Gene Expression Profiling Biomarkers, Tumor Melanoma Humans Machine Learning
View on PubMed DOI

Mind the Gap: A Neural Network Framework for Imputing Genotypes in Non-Model Species.

Molecular ecology resources Jan 3, 2025
Reduced representation sequencing (RRS) has proven to be a cost-effective solution for sequencing subsets of the genome in non-model species for large-scale studies. However, the targeted nature of RRS approaches commonly introduces large amounts of ...
Genotype Neural Networks, Computer Haplotypes Computational Biology Machine Learning
View on PubMed DOI

Data and AI-driven synthetic binding protein discovery.

Trends in pharmacological sciences Jan 3, 2025
Synthetic binding proteins (SBPs) are a class of protein binders that are artificially created and do not exist naturally. Their broad applications in tackling challenges of research, diagnostics, and therapeutics have garnered significant interest. ...
Artificial Intelligence Animals Protein Binding Computational Biology Drug Discovery Humans Protein Engineering Proteins Models, Molecular
View on PubMed DOI

Neighborhood Topology-Aware Knowledge Graph Learning and Microbial Preference Inferring for Drug-Microbe Association Prediction.

Journal of chemical information and modeling Jan 2, 2025
The human microbiota may influence the effectiveness of drug therapy by activating or inactivating the pharmacological properties of drugs. Computational methods have demonstrated their ability to screen reliable microbe-drug associations and uncover...
Humans Computational Biology Microbiota Machine Learning
View on PubMed DOI

pACP-HybDeep: predicting anticancer peptides using binary tree growth based transformer and structural feature encoding with deep-hybrid learning.

Scientific reports Jan 2, 2025
Worldwide, Cancer remains a significant health concern due to its high mortality rates. Despite numerous traditional therapies and wet-laboratory methods for treating cancer-affected cells, these approaches often face limitations, including high cost...
Computational Biology Antineoplastic Agents Deep Learning Neoplasms Peptides Humans Algorithms
View on PubMed DOI
Popular Topics
Recent Journals