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A biomarker can be either predictive or prognostic. A predictive marker predicts benefit from a specific treatment; it helps to select a particular treatment over another. A prognostic marker predicts the natural history of disease (survival), independent of treatment. It can indicate a need for further treatment, but does not help to determine which treatment. The ROC Plotter is the first online transcriptome-level validation tool for predictive biomarkers in cancer research.

The Kaplan Meier plotter is capable to assess the correlation between the expression of 30k genes (mRNA, miRNA, protein) and survival in 25k+ samples from 21 tumor types including breast, ovarian, lung, & gastric cancer. Sources for the databases include GEO, EGA, and TCGA. Primary purpose of the tool is a meta-analysis based discovery and validation of survival biomarkers.

Genes showing higher expression in either tumor or metastatic tissues can help in better understanding tumor formation and can serve as biomarkers of progression or as potential therapy targets. Our goal was to establish an integrated database using available transcriptome-level datasets and to create a web platform which enables the mining of this database by comparing normal, tumor and metastatic data across all genes in real time. Our tool can termed can be used perform the analysis of the database in real time.

Scientists from nearly all disciplines face the problem of simultaneously evaluating many hypotheses. Conducting multiple comparisons increases the likelihood that a non-negligible proportion of associations will be false positives, clouding real discoveries. Drawing valid conclusions require taking into account the number of performed statistical tests and adjusting the statistical confidence measures. To facilitate multiple-testing corrections, we developed a fully automated solution not requiring programming skills or the use of a command line. Our registration free online tool is available at and compiles the five most frequently used adjustment tools, including the Bonferroni, the Holm, the Hochberg corrections, allows to calculate False Discovery Rates (FDR) and q-values. is a scientific project aiming to objectively compare the scientific output of Hungarian researchers and disciplines to each other. The analysis is performed by comparing each researcher to a common reference database containing Hungarian researchers of the same age and active in the same scientific discipline.