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Computational Biology

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Deep Learning Approaches for the Prediction of Protein Functional Sites.

Molecules (Basel, Switzerland)
Knowing which residues of a protein are important for its function is of paramount importance for understanding the molecular basis of this function and devising ways of modifying it for medical or biotechnological applications. Due to the difficulty...

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

IEEE journal of biomedical and health informatics
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...

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

IEEE journal of biomedical and health informatics
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...

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

IEEE journal of biomedical and health informatics
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, ...

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

IEEE journal of biomedical and health informatics
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...

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

BMC bioinformatics
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 ...

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

Molecular ecology resources
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 ...

Data and AI-driven synthetic binding protein discovery.

Trends in pharmacological sciences
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. ...