statistics, multivariate analysis, network analysis
| eva.freyhult@nbis.se | |
|---|---|
| phone | +46 (0)18-6114248 |
Eva support statistical multivariate analysis and network analysis. Eva has a PhD in Bioinformatics from Uppsala University (2007), where she worked on various bioinformatic questions concerning non-coding RNA. After her PhD she worked as a postdoc/bioinformatician at Umeå University for two years (2008-2010), where she supported the medical faculty with various bioinformatic analysis and was involved in a project concerning normalization and clustering of microarray data. Back at Uppsala University (2010) she worked as a post doc in a Leukemia epigenetics project, where she used survival analysis to find factors important to relapse free survival of leukemic patients. Eva works as an NBIS expert since February 2012.
Eva supports statistical multivariate analysis and network analysis. This includes machine learning, cluster analysis, survival analysis, regression, classification, signal processing, data compression and transformation etc.
A typical support question concerns samples of two or more types, where the goal is to distinguish between the types based on a set of measurements (gene expression, DNA methylation, absorption, clinical parameters etc). Usually part of the problem is to build a reliable classifier, but another important part is to detect measurements that are important for distinguishing the types.
statistics, multivariate analysis, network analysis
| eva.freyhult@nbis.se | |
|---|---|
| phone | +46 (0)18-6114248 |
Eva support statistical multivariate analysis and network analysis. Eva has a PhD in Bioinformatics from Uppsala University (2007), where she worked on various bioinformatic questions concerning non-coding RNA. After her PhD she worked as a postdoc/bioinformatician at Umeå University for two years (2008-2010), where she supported the medical faculty with various bioinformatic analysis and was involved in a project concerning normalization and clustering of microarray data. Back at Uppsala University (2010) she worked as a post doc in a Leukemia epigenetics project, where she used survival analysis to find factors important to relapse free survival of leukemic patients. Eva works as an NBIS expert since February 2012.
Eva supports statistical multivariate analysis and network analysis. This includes machine learning, cluster analysis, survival analysis, regression, classification, signal processing, data compression and transformation etc.
A typical support question concerns samples of two or more types, where the goal is to distinguish between the types based on a set of measurements (gene expression, DNA methylation, absorption, clinical parameters etc). Usually part of the problem is to build a reliable classifier, but another important part is to detect measurements that are important for distinguishing the types.