AI Medical Compendium Topic:
Computational Biology

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During haptic communication, the central nervous system compensates distinctly for delay and noise.

PLoS computational biology
Physically connected humans have been shown to exploit the exchange of haptic forces and tactile information to improve their performance in joint action tasks. As human interactions are increasingly mediated through robots and networks it is importa...

SGFCCDA: Scale Graph Convolutional Networks and Feature Convolution for circRNA-Disease Association Prediction.

IEEE journal of biomedical and health informatics
Circular RNAs (circRNAs) have emerged as a novel class of non-coding RNAs with regulatory roles in disease pathogenesis. Computational models aimed at predicting circRNA-disease associations offer valuable insights into disease mechanisms, thereby en...

Drug-Target Prediction Based on Dynamic Heterogeneous Graph Convolutional Network.

IEEE journal of biomedical and health informatics
Novel drug-target interaction (DTI) prediction is crucial in drug discovery and repositioning. Recently, graph neural network (GNN) has shown promising results in identifying DTI by using thresholds to construct heterogeneous graphs. However, an empi...

Generating Biomedical Hypothesis With Spatiotemporal Transformers.

IEEE journal of biomedical and health informatics
Generating biomedical hypotheses is a difficult task as it requires uncovering the implicit associations between massive scientific terms from a large body of published literature. A recent line of Hypothesis Generation (HG) approaches - temporal gra...

Generative AI in the Advancement of Viral Therapeutics for Predicting and Targeting Immune-Evasive SARS-CoV-2 Mutations.

IEEE journal of biomedical and health informatics
The emergence of immune-evasive mutations in the SARS-CoV-2 spike protein is consistently challenging existing vaccines and therapies, making precise prediction of their escape potential a critical imperative. Artificial Intelligence(AI) holds great ...

SFWN: A Novel Semi-Supervised Feature Weighted Neural Network for Gene Data Feature Learning and Mining With Graph Modeling.

IEEE journal of biomedical and health informatics
Gene expression data can serve for analyzing the genes with changed expressions, the correlation between genes and the influence of different circumstance on gene activities. However, labeling a large number of gene expression data is laborious and t...

TPGPred: A Mixed-Feature-Driven Approach for Identifying Thermophilic Proteins Based on GradientBoosting.

International journal of molecular sciences
Thermophilic proteins maintain their stability and functionality under extreme high-temperature conditions, making them of significant importance in both fundamental biological research and biotechnological applications. In this study, we developed a...

Knowledge-based inductive bias and domain adaptation for cell type annotation.

Communications biology
Measurement techniques often result in domain gaps among batches of cellular data from a specific modality. The effectiveness of cross-batch annotation methods is influenced by inductive bias, which refers to a set of assumptions that describe the be...

Exploration of common pathogenesis and candidate hub genes between HIV and monkeypox co-infection using bioinformatics and machine learning.

Scientific reports
This study explored the pathogenesis of human immunodeficiency virus (HIV) and monkeypox co-infection, identifying candidate hub genes and potential drugs using bioinformatics and machine learning. Datasets for HIV (GSE 37250) and monkeypox (GSE 2412...