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Geometry-Augmented Molecular Representation Learning for Property Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Accurate molecular representation plays a crucial role in expediting the process of drug discovery. Graph neural networks (GNNs) have demonstrated robust capabilities in molecular representation learning, adept at capturing structural and spatial inf...

Analysis of Cancer-Associated Mutations of POLB Using Machine Learning and Bioinformatics.

IEEE/ACM transactions on computational biology and bioinformatics
DNA damage is a critical factor in the onset and progression of cancer. When DNA is damaged, the number of genetic mutations increases, making it necessary to activate DNA repair mechanisms. A crucial factor in the base excision repair process, which...

A Network Enhancement Method to Identify Spurious Drug-Drug Interactions.

IEEE/ACM transactions on computational biology and bioinformatics
As medical safety and drug regulation gain heightened attention, the detection of spurious drug-drug interactions (DDI) has become key in healthcare. Although current research using graph neural networks (GNNs) to predict DDI has shown impressive res...

PseU-KeMRF: A Novel Method for Identifying RNA Pseudouridine Sites.

IEEE/ACM transactions on computational biology and bioinformatics
Pseudouridine is a type of abundant RNA modification that is seen in many different animals and is crucial for a variety of biological functions. Accurately identifying pseudouridine sites within the RNA sequence is vital for the subsequent study of ...

TransC-ac4C: Identification of N4-Acetylcytidine (ac4C) Sites in mRNA Using Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
N4-acetylcytidine (ac4C) is a post-transcriptional modification in mRNA that is critical in mRNA translation in terms of stability and regulation. In the past few years, numerous approaches employing convolutional neural networks (CNN) and Transforme...

HybAVPnet: A Novel Hybrid Network Architecture for Antiviral Peptides Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Viruses pose a great threat to human production and life, thus the research and development of antiviral drugs is urgently needed. Antiviral peptides play an important role in drug design and development. Compared with the time-consuming and laboriou...

TDFFM: Transformer and Deep Forest Fusion Model for Predicting Coronavirus 3C-Like Protease Cleavage Sites.

IEEE/ACM transactions on computational biology and bioinformatics
COVID-19, caused by the highly contagious SARS-CoV-2 virus, is distinguished by its positive-sense, single-stranded RNA genome. A thorough understanding of SARS-CoV-2 pathogenesis is crucial for halting its proliferation. Notably, the 3C-like proteas...

FluPMT: Prediction of Predominant Strains of Influenza A Viruses via Multi-Task Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Seasonal influenza vaccines play a crucial role in saving numerous lives annually. However, the constant evolution of the influenza A virus necessitates frequent vaccine updates to ensure its ongoing effectiveness. The decision to develop a new vacci...

Boundary-Aware Dual Biaffine Model for Sequential Sentence Classification in Biomedical Documents.

IEEE/ACM transactions on computational biology and bioinformatics
Assigning appropriate rhetorical roles, such as "background," "intervention," and "outcome," to sentences in biomedical documents can streamline the process for physicians to locate evidence and resources for medical treatment and decision-making. Wh...

SGLMDA: A Subgraph Learning-Based Method for miRNA-Disease Association Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
MicroRNAs (miRNA) are endogenous non-coding RNAs, typically around 23 nucleotides in length. Many miRNAs have been founded to play crucial roles in gene regulation though post-transcriptional repression in animals. Existing studies suggest that the d...