B
Balázs Győrffy
Researcher at Semmelweis University
Publications - 263
Citations - 13744
Balázs Győrffy is an academic researcher from Semmelweis University. The author has contributed to research in topics: Cancer & Breast cancer. The author has an hindex of 42, co-authored 204 publications receiving 8915 citations. Previous affiliations of Balázs Győrffy include Hungarian Academy of Sciences.
Papers
More filters
Journal ArticleDOI
Online Survival Analysis Software to Assess the Prognostic Value of Biomarkers Using Transcriptomic Data in Non-Small-Cell Lung Cancer
TL;DR: An integrated database and an online tool capable of uni- and multivariate analysis for in silico validation of new biomarker candidates in non-small cell lung cancer are established.
Journal ArticleDOI
Validation of miRNA prognostic power in hepatocellular carcinoma using expression data of independent datasets
TL;DR: An integrated miRNA expression database was set up and prognostic miRNAs identified as potential prognostic biomarkers for HCC were validated and the expression was significantly altered in 102 mi RNAs in tumors compared to normal liver tissues.
Journal ArticleDOI
Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling Rapid Biomarker Cutoff Optimization
Jan Budczies,Frederick Klauschen,Bruno Valentin Sinn,Balázs Győrffy,Wolfgang D. Schmitt,Silvia Darb-Esfahani,Carsten Denkert +6 more
TL;DR: The functionality of Cutoff Finder is illustrated by the analysis of the gene expression of estrogen receptor and progesterone receptor in breast cancer tissues, which is analyzed and correlated with immunohistologically determined ER status and distant metastasis free survival.
Journal ArticleDOI
Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients
A. Marcell Szász,András Lánczky,Ádám Nagy,Susann Förster,Kim Hark,Jeffrey E. Green,Alex Boussioutas,Rita A. Busuttil,András Szabó,Balázs Győrffy +9 more
TL;DR: A robust database enabling the swift validation of previous and future gastric cancer survival biomarker candidates predicting first progression (FP) and overall survival (OS) using uni- and multivariate Cox proportional hazards regression analysis is established.
Journal ArticleDOI
Implementing an online tool for genome-wide validation of survival-associated biomarkers in ovarian-cancer using microarray data from 1287 patients.
TL;DR: In this article, the authors developed a global online biomarker validation platform that mines all available microarray data to assess the prognostic power of 22,277 genes in 1287 ovarian cancer patients.