Identifying critical states of hepatocellular carcinoma based on landscape dynamic network biomarkers
Sign Up to like & getrecommendations! Published in 2020 at "Computational biology and chemistry"
DOI: 10.1016/j.compbiolchem.2020.107202
Abstract: Hepatocellular carcinoma (HCC) is the major histological form of primary liver cancer. It has usually reached the disease state once the patient is diagnosed since there are no specific symptoms in the early stages of… read more here.
Keywords: state; hepatocellular carcinoma; dynamic network; critical states ... See more keywords
Subnetwork representation learning for discovering network biomarkers in predicting lymph node metastasis in early oral cancer
Sign Up to like & getrecommendations! Published in 2021 at "Scientific Reports"
DOI: 10.1038/s41598-021-03333-5
Abstract: Cervical lymph node metastasis is the leading cause of poor prognosis in oral tongue squamous cell carcinoma and also occurs in the early stages. The current clinical diagnosis depends on a physical examination that is… read more here.
Keywords: network biomarkers; node metastasis; metastasis early; metastasis ... See more keywords
Identifying critical states of hepatocellular carcinoma based on single-sample dynamic network biomarkers combined with simulated annealing algorithm
Sign Up to like & getrecommendations! Published in 2021 at "Current Bioinformatics"
DOI: 10.2174/1574893616666210727144206
Abstract: Hepatocellular carcinoma(HCC) is one of the most common malignant tumors. Due to the insidious onset and poor prognosis, most patients have reached the advanced stage at the time of diagnosis. Studies have shown thatdynamic network… read more here.
Keywords: hepatocellular carcinoma; state; network; dynamic network ... See more keywords
Development of dynamical network biomarkers for regulation in Epstein-Barr virus positive peripheral T cell lymphoma unspecified type
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Genetics"
DOI: 10.3389/fgene.2022.966247
Abstract: Background: This study was performed to identify key regulatory network biomarkers including transcription factors (TFs), miRNAs and lncRNAs that may affect the oncogenesis of EBV positive PTCL-U. Methods: GSE34143 dataset was downloaded and analyzed to… read more here.
Keywords: network; positive ptcl; network biomarkers; biomarkers regulation ... See more keywords