Bioinformatics for Proteomics II

NUMMER: 201911
KÜRZEL: BioInfPro2
MODULBEAUFTRAGTE:R: PD Dr. rer. medic. Martin Eisenacher
FAKULTÄT: Medizinisches Proteom Center
SPRACHE: Deutsch
ANGEBOTEN IM: jedes Sommersemester


FORM: schriftlich oder mündlich
TERMIN: Siehe Prüfungsamt.


Lecture: slide-based lecture. Tutorial: Solution of small practical exercises using real example
data as homework, programming tasks, group work, live-presentation of code and software
and seminar-like form of teaching.


Discipline-specific competences:
After the successful completion of this module
∙ the students have become familiar with the most important knowledge from the lecture
“Bioinformatics for Proteomics I” as a brief recapitulation,
∙ they have become familiar with the principles of advanced methods used in bioinformatics
for proteomics,
∙ they are able to explain and use advanced methods that currently are employed to
analyze raw data (i.e., mass spectra) and results (i.e., peptide/protein identification
and quantification results) and to interpret them biologically,
∙ they understand the underlying algorithmic and statistical concepts of these methods,
∙ they are able to use proteomics-specific software and the workflow engine KNIME,
∙ they are able to design and program own solution strategies
∙ and they are able to apply the discussed software tools and methods to real data and

Interdisciplinary/generic competences:
∙ instrumental competences:
– Intensive usage of the learning platform Moodle
∙ systemic competences:
– Independent learning and working
– Teamwork and ability to work in a team
∙ communicative competences:
– Presentation of own work and results
– Communication of bioinformatics-specific technical terms
– Rhetoric and linguistic competence (English)


∙ Brief recapitulation of “Bioinformatics for Proteomics I”
∙ Computational comparison of protein lists
∙ Statistics for the comparison of experimental groups
∙ Machine learning-based biomarker discovery (supervised and unsupervised methods)
∙ Enrichment analysis
∙ Network analysis
∙ Single / multiple / parallel reaction monitoring (SRM / MRM / PRM)
∙ Data independent acquisition (DIA)
∙ Algorithms for de novo sequencing of peptides
∙ Open searches
∙ Dark matter of proteomics
∙ Proteoforms
∙ Metaproteomics and proteogenomics
∙ Software tools used in bioinformatics for proteomics (Tutorial)
∙ Practical (programming) tasks (Tutorial)
∙ Workflow engine KNIME (Tutorial)


Bestandene schriftliche oder mündliche Prüfung


Recommended prior knowledge: English, basic programming
skills and lecture/tutorials “Bioinformatics for Proteomics I” in the winter term (recommended,
not required).