The gastrointestinal tract (GIT) is an intricate ecosystem harboring the microbiome consisting of fungi, bacteria, viruses and archaebacteria living symbiotically with the host1. The microbiome benefits the host through selective carbohydrates and polyphenols fermentation2to produce bioactive metabolites3. ...
Imaging, genetics, epigenetics and proteomics technologies allow the precise interrogation of cellular functions and cell–cell communication and might, thus, aid in the study of nano–bio interactions. Biological variables, such as age and sex, impact interactions with nanoparticles and should, thus, ...
(2022) illustrates this with a deep neural network that integrates multi-omics data—including gene expressions, copy number variations, gene mutations, protein expressions, and metabolomics—from cancer cell lines [177]. The model features innovative components such as a graph embedding layer to ...
Through model construction and data mining, precision medicine is made possible. As technology continues to advance and applications expand, AI is poised to play an increasingly vital role in the field of medicine. Conclusions Multi-omics have already become essential methods for elucidating the ...
Tan et al. combined six immune associated genes (CD163, FPR3, LPAR5, P2ry12, PLAUR, SIGLEC1) to construct a prognostic model for LGG, where the calculated risk score could be used to differentiate the overall survival rates of LGG16. The carcinogenesis and cancer progression are ...
Multi-omics analysis reveals the genetics and immune landscape of dexamethasone responsive genes in cancer microenvironment.doi:10.21037/ATM-20-3650Yu ShenYing C WuLixiong GuAME Publishing Company
These findings suggest that new therapeutic strategies targeting gene dosage and epigenetic modification should be considered in personalized cancer medicine. This culture model may be applied to the further identification of plausible determinants of cancer metastasis and relapse....
Graph Neural Networks (GNNs), pathway analysis and multi-omics analysis have shown great potential in the field of cancer diagnosis and treatment. Methods A GNNs model was constructed to predict the immunotherapy response and identify key pathways. Based on the genes of key pathways, bioinformatic ...
Unsupervised learning is employed to identify dissimilarities in unlabelled data for clustering purposes. Reinforcement learning is a dynamic process in which the model trains by reward and punishment mechanisms. Machine learning capabilities that can be applied in ME/CFS, and diseases in general, using...
C. et al. Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes. Cell 184, 2239–2254.e2239 (2021). Article CAS PubMed PubMed Central Google Scholar Neftel, C. et al. An integrative model of cellular states, plasticity, and genetics for glioblastoma. Cell 178...