Venue: Biomedicum 1, Meeting room 8-9, P-floor

Timing: 15:30 onwards

Presenter: Mehreen Ali, PhD student, FIMM

Missing data imputation methods in proteomic datasets

Mass spectrometry (MS)-based proteomic profiling has the potential to study comprehensive protein profiling of biological samples and thus has shifted the focus of research from qualitative to quantitative analyses. MS-based proteomics provide opportunity for more global profiling of post-translational modifications, in terms of yielding proteome-wide information about cancer cell signaling activity that is not accessible by genomics or transcriptomics alone. 

However, a substantial amount of data is missing at peptide/protein level primarily due to low-abundance peptides and/or poor ionization. Missing values in proteomics datasets limit the information extraction from proteomics datasets using statistical and machine learning methods, and thus have detrimental effect on downstream analyses.

In this talk, I will give a general overview of imputation methods adapted for proteomics datasets