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[HTML][HTML] Liquid biopsy, ctDNA diagnosis through NGS
Liquid biopsy with circulating tumor DNA (ctDNA) profiling by next-generation sequencing
holds great promise to revolutionize clinical oncology. It relies on the basis that ctDNA …
holds great promise to revolutionize clinical oncology. It relies on the basis that ctDNA …
In silico polypharmacology of natural products
Natural products with polypharmacological profiles have demonstrated promise as novel
therapeutics for various complex diseases, including cancer. Currently, many gaps exist in …
therapeutics for various complex diseases, including cancer. Currently, many gaps exist in …
Evaluating the evaluation of cancer driver genes
Sequencing has identified millions of somatic mutations in human cancers, but
distinguishing cancer driver genes remains a major challenge. Numerous methods have …
distinguishing cancer driver genes remains a major challenge. Numerous methods have …
Improving cancer driver gene identification using multi-task learning on graph convolutional network
W Peng, Q Tang, W Dai, T Chen - Briefings in bioinformatics, 2022 - academic.oup.com
Cancer is thought to be caused by the accumulation of driver genetic mutations. Therefore,
identifying cancer driver genes plays a crucial role in understanding the molecular …
identifying cancer driver genes plays a crucial role in understanding the molecular …
Performance evaluation of pathogenicity-computation methods for missense variants
J Li, T Zhao, Y Zhang, K Zhang, L Shi… - Nucleic acids …, 2018 - academic.oup.com
With expanding applications of next-generation sequencing in medical genetics, increasing
computational methods are being developed to predict the pathogenicity of missense …
computational methods are being developed to predict the pathogenicity of missense …
MODIG: integrating multi-omics and multi-dimensional gene network for cancer driver gene identification based on graph attention network model
Motivation Identifying genes that play a causal role in cancer evolution remains one of the
biggest challenges in cancer biology. With the accumulation of high-throughput multi-omics …
biggest challenges in cancer biology. With the accumulation of high-throughput multi-omics …
Application of computational biology and artificial intelligence technologies in cancer precision drug discovery
Artificial intelligence (AI) proves to have enormous potential in many areas of healthcare
including research and chemical discoveries. Using large amounts of aggregated data, the …
including research and chemical discoveries. Using large amounts of aggregated data, the …
deepDriver: predicting cancer driver genes based on somatic mutations using deep convolutional neural networks
With the advances in high-throughput technologies, millions of somatic mutations have been
reported in the past decade. Identifying driver genes with oncogenic mutations from these …
reported in the past decade. Identifying driver genes with oncogenic mutations from these …
[HTML][HTML] The emerging potential for network analysis to inform precision cancer medicine
Precision cancer medicine promises to tailor clinical decisions to patients using genomic
information. Indeed, successes of drugs targeting genetic alterations in tumors, such as …
information. Indeed, successes of drugs targeting genetic alterations in tumors, such as …
A novel heterophilic graph diffusion convolutional network for identifying cancer driver genes
T Zhang, SW Zhang, MY **e, Y Li - Briefings in Bioinformatics, 2023 - academic.oup.com
Identifying cancer driver genes plays a curial role in the development of precision oncology
and cancer therapeutics. Although a plethora of methods have been developed to tackle this …
and cancer therapeutics. Although a plethora of methods have been developed to tackle this …