AI Medical Compendium Topic:
Computational Biology

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Protein function annotation and virulence factor identification of Klebsiella pneumoniae genome by multiple machine learning models.

Microbial pathogenesis
Klebsiella pneumoniae is a type of Gram-negative bacterium which can cause a range of infections in human. In recent years, an increasing number of strains of K. pneumoniae resistant to multiple antibiotics have emerged, posing a significant threat t...

Apoptosis and NETotic cell death affect diabetic nephropathy independently: An study integrative study encompassing bioinformatics, machine learning, and experimental validation.

Genomics
OBJECTIVE: Although programmed cell death (PCD) and diabetic nephropathy (DN) are intrinsically conneted, the interplay among various PCD forms remains elusive. In this study, We aimed at identifying independently DN-associated PCD pathways and bioma...

EGG: Accuracy Estimation of Individual Multimeric Protein Models Using Deep Energy-Based Models and Graph Neural Networks.

International journal of molecular sciences
Reliable and accurate methods of estimating the accuracy of predicted protein models are vital to understanding their respective utility. Discerning how the quaternary structure conforms can significantly improve our collective understanding of cell ...

MicroRNAs: circulating biomarkers for the early detection of imperceptible cancers via biosensor and machine-learning advances.

Oncogene
This review explores the topic of microRNAs (miRNAs) for improved early detection of imperceptible cancers, with potential to advance precision medicine and improve patient outcomes. Historical research exploring miRNA's role in cancer detection coll...

A miRNA-disease association prediction model based on tree-path global feature extraction and fully connected artificial neural network with multi-head self-attention mechanism.

BMC cancer
BACKGROUND: MicroRNAs (miRNAs) emerge in various organisms, ranging from viruses to humans, and play crucial regulatory roles within cells, participating in a variety of biological processes. In numerous prediction methods for miRNA-disease associati...

Functional Neural Networks for High-Dimensional Genetic Data Analysis.

IEEE/ACM transactions on computational biology and bioinformatics
Artificial intelligence (AI) is a thriving research field with many successful applications in areas such as computer vision and speech recognition. Machine learning methods, such as artificial neural networks (ANN), play a central role in modern AI ...

TSVM: Transfer Support Vector Machine for Predicting MPRA Validated Regulatory Variants.

IEEE/ACM transactions on computational biology and bioinformatics
Genome-wide association studies have shown that common genetic variants associated with complex diseases are mostly located in non-coding regions, which may not be causal. In addition, the limited number of validated non-coding functional variants ma...

PPRTGI: A Personalized PageRank Graph Neural Network for TF-Target Gene Interaction Detection.

IEEE/ACM transactions on computational biology and bioinformatics
Transcription factors (TFs) regulation is required for the vast majority of biological processes in living organisms. Some diseases may be caused by improper transcriptional regulation. Identifying the target genes of TFs is thus critical for underst...

MAHyNet: Parallel Hybrid Network for RNA-Protein Binding Sites Prediction Based on Multi-Head Attention and Expectation Pooling.

IEEE/ACM transactions on computational biology and bioinformatics
RNA-binding proteins (RBPs) can regulate biological functions by interacting with specific RNAs, and play an important role in many life activities. Therefore, the rapid identification of RNA-protein binding sites is crucial for functional annotation...

A Survey of Deep Learning for Detecting miRNA- Disease Associations: Databases, Computational Methods, Challenges, and Future Directions.

IEEE/ACM transactions on computational biology and bioinformatics
MicroRNAs (miRNAs) are an important class of non-coding RNAs that play an essential role in the occurrence and development of various diseases. Identifying the potential miRNA-disease associations (MDAs) can be beneficial in understanding disease pat...