Decode the Phosphoproteome: Fine-Tune Our R Pipeline
- Beschreibung
Why phosphoproteomics?
How does a cell decide when a protein should be active? Often, the answer is a single phosphate group. Adding a small phosphate group can change a protein's shape, turn it on or off, or kick off an entire signalling cascade. Phosphoproteomics, the large-scale study of these modifications by mass spectrometry, is one of the fastest-growing areas in proteomics. It lets us see which proteins are being switched on or off, and when.
The challenge
Mass spectrometry produces complex datasets. Turning raw data into biological insight takes a solid analysis pipeline. Our lab has developed an R script to process our phosphoproteomics data, and now we need fresh eyes to make it better.
Your mission
Take our existing R workflow and help us fine-tune it:
- Run the pipeline on real phosphoproteomics data from our lab
- Test and compare analysis choices (filtering, normalisation, statistical thresholds, and so on)
- Identify weak spots, improve the code, and make the protocol more robust and reproducible
- Interpret the output: which proteins are phosphorylated, and what might that mean biologically?
Why join?
This is a hands-on project with real data and a real impact: your improvements will be used in ongoing lab research. It's ideal if you enjoy dataanalysis, coding, or the idea of working at the interface of biology and bioinformatics. Basic R knowledge is helpful, but enthusiasm and a willingness to learn matter most.
- Projektzeitraum
- Wintersemester 2026/2027
- Bewerbungszeitraum
- 12. bis 26.10.2026
- Durchführung
- nach Absprache
- Studienfach
- offen für alle Studienfächer
- Betreuende
- Rebecca John, Dr. Tatsiana Straub
- Institut
- Institut für Biologie (190) (Plants Systems Biology (190d))
- Sprache
- englisch
- Teilnehmendenanzahl
- min. 1, max. 1
- Arbeitsaufwand
-
ca. 30 Stunden pro Teilnehmende:r
| 1
ECTS-Punkte
Arbeitsaufwand (Stunden und ggf. ECTS) sind ungefähre Angaben. Die tatsächlich vergebenen ECTS-Punkte ergeben sich aus der tatsächlich geleisteten Arbeit.
- Für dieses Projekt ist kein Motivationsschreiben des Studierenden erforderlich
- Projektart
- experimentell
- Lernziele
-
Die Teilnehmende lernen in diesem Projekt:
What you will learn
- How protein phosphorylation works and why it matters for signaling and regulation
- The principles behind phosphoproteomics and mass spectrometry data
- Practical data analysis and statistics in R
- How to optimize, validate and document a bioinformatics workflow
- Critical thinking: separating real biological signal from noise
- Anmerkungen für Studierende