Facility for Data Sciences & Biostatistics

The Core Facility Data Sciences und Biostatistics offers data analysis support for proteogenomics, classical bioinformatics, modelling and biostatistics.

 

1. Proteogenomics:

• Transcriptomics:
  RNA-sequencing data analysis, transcriptome quantification, transcriptome de novo assembly, differential gene expression
• Proteomics and peptidomics:
  Mass spectrometry (MS) data analysis approaches, identification and quantification of proteomes, differential protein expression, protein sequence analysis (enrichment and annotation)
• Proteogenomics:
  Integration of proteomics and transcriptomics data for identification of novel transcripts, integration of differential expression and abundance between RNA and proteomics

2. Classical Bioinformatics:

• Overrepresentation / enrichment analysis, sequence analysis / motif analysis, ML for sequence prediction (e.g., classifiers), network analysis, differential time series analysis

3. Modelling:

• Kinetic / mechanistic / computational / statistical modelling, deterministic and stochastic modelling, Bayesian Inference and model selection approaches, classical machine learning and deep learning approaches, classifiers / predictors

4. Biostatistics:

• Support on general statistics, statistics for data analysis, biometrical sample size calculation