Results 261 to 270 of about 13,113,839 (405)

THE USE OF COMPUTERS IN CLINICAL TRIALS

open access: bronze, 1967
William H. Forrest, J. Weldon Bellville
openalex   +1 more source

Highly multiplexed digital PCR assay for simultaneous quantification of variant allele frequencies and copy number alterations of KRAS and GNAS in pancreatic cancer precursors

open access: yesMolecular Oncology, EarlyView.
Combining melting curve analysis enhances the multiplexing capability of digital PCR. Here, we developed a 14‐plex assay to simultaneously measure single nucleotide mutations and amplifications of KRAS and GNAS, which are common driver genes in pancreatic cancer precursors. This assay accurately quantified variant allele frequencies in clinical samples
Junko Tanaka   +10 more
wiley   +1 more source

Q fever outbreak in the terraced vineyards of Lavaux, Switzerland

open access: yesNew Microbes and New Infections, EarlyView., 2014
Abstract Coxiella burnetii infection (Q fever) is a widespread zoonosis with low endemicity in Switzerland, therefore no mandatory public report was required. A cluster of initially ten human cases of acute Q fever infections characterized by prolonged fever, asthenia and mild hepatitis occurred in 2012 in the terraced vineyard of Lavaux ...
C. Bellini   +9 more
wiley   +1 more source

Artificial Intelligence for Clinical Trial Design.

open access: yesTIPS - Trends in Pharmacological Sciences, 2019
S. Harrer   +3 more
semanticscholar   +1 more source

Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma

open access: yesMolecular Oncology, EarlyView.
This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu   +15 more
wiley   +1 more source

Comparing self‐reported race and genetic ancestry for identifying potential differentially methylated sites in endometrial cancer: insights from African ancestry proportions using machine learning models

open access: yesMolecular Oncology, EarlyView.
Integrating ancestry, differential methylation analysis, and machine learning, we identified robust epigenetic signature genes (ESGs) and Core‐ESGs in Black and White women with endometrial cancer. Core‐ESGs (namely APOBEC1 and PLEKHG5) methylation levels were significantly associated with survival, with tumors from high African ancestry (THA) showing ...
Huma Asif, J. Julie Kim
wiley   +1 more source

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