AI Medical Compendium Topic:
Computational Biology

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Intelligence model on sequence-based prediction of PPI using AISSO deep concept with hyperparameter tuning process.

Scientific reports
Protein-protein interaction (PPI) prediction is vital for interpreting biological activities. Even though many diverse sorts of data and machine learning approaches have been employed in PPI prediction, performance still has to be enhanced. As a resu...

Multi-omics features of immunogenic cell death in gastric cancer identified by combining single-cell sequencing analysis and machine learning.

Scientific reports
Gastric cancer (GC) is a prevalent malignancy with high mortality rates. Immunogenic cell death (ICD) is a unique form of programmed cell death that is closely linked to antitumor immunity and plays a critical role in modulating the tumor microenviro...

Virus-host interactions predictor (VHIP): Machine learning approach to resolve microbial virus-host interaction networks.

PLoS computational biology
Viruses of microbes are ubiquitous biological entities that reprogram their hosts' metabolisms during infection in order to produce viral progeny, impacting the ecology and evolution of microbiomes with broad implications for human and environmental ...

MHIPM: Accurate Prediction of Microbe-Host Interactions Using Multiview Features from a Heterogeneous Microbial Network.

Journal of chemical information and modeling
Current studies have demonstrated that microbe-host interactions (MHIs) play important roles in human public health. Therefore, identifying the interactions between microbes and hosts is beneficial to understanding the role of the microbiome and thei...

From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology.

Nature protocols
Hematoxylin- and eosin-stained whole-slide images (WSIs) are the foundation of diagnosis of cancer. In recent years, development of deep learning-based methods in computational pathology has enabled the prediction of biomarkers directly from WSIs. Ho...

Tissue-aware interpretation of genetic variants advances the etiology of rare diseases.

Molecular systems biology
Pathogenic variants underlying Mendelian diseases often disrupt the normal physiology of a few tissues and organs. However, variant effect prediction tools that aim to identify pathogenic variants are typically oblivious to tissue contexts. Here we r...

Deep neural network models for cell type prediction based on single-cell Hi-C data.

BMC genomics
BACKGROUND: Cell type prediction is crucial to cell type identification of genomics, cancer diagnosis and drug development, and it can solve the time-consuming and difficult problem of cell classification in biological experiments. Therefore, a compu...

simona: a comprehensive R package for semantic similarity analysis on bio-ontologies.

BMC genomics
BACKGROUND: Bio-ontologies are keys in structuring complex biological information for effective data integration and knowledge representation. Semantic similarity analysis on bio-ontologies quantitatively assesses the degree of similarity between bio...

Predicting structure-targeted food bioactive compounds for middle-aged and elderly Asians with myocardial infarction: insights from genetic variations and bioinformatics-integrated deep learning analysis.

Food & function
Myocardial infarction (MI) is a significant global health issue. Despite the advances in genome-wide association studies, a complete genetic and molecular understanding of MI is elusive and needs to be fully explored. This study aimed to elucidate th...