Welcome to CSB
The capability of biological systems to respond to environmental changes is realized by a complex dynamic adjustment of the interplay between genes, proteins and metabolites. For a deeper understanding at the systems level, we need to study the structure and dynamics of cellular and organismal functions rather than the characteristics of isolated parts of a cell or an organism.
Welcome to CSB
What our research is aiming for
The main focus of our group is the application and development of computational methods to process and integrate quantitative biological data from modern high-throughput measurements in order to gain novel insights into biological responses to environment changes. The main challenge is the rigorous integration of different system level analyses and present knowledge into biological interpretable models. Therefore, we want to drive theory and technology forward with a combination of biological science, applied informatics, statistical and machine learning approaches.
Team
Our research team on CSB
Janine Mertel
Team AssistantTimo Mühlhaus
ProfessorDavid Zimmer
PostDocLukas Weil
PhD StudentSelina Ziegler
Research AssociateChristopher Lux
PhD StudentFelix Jung
PhD StudentBenedikt Venn
PhD StudentOliver Maus
PhD StudentKevin Frey
PhD StudentKevin Schneider
PhD StudentCaroline Ott
PhD Student-
2023
Selina Ziegler (Master Student)
-
2022
David Zimmer (PhD Student)
Christopher Lux (Master Student)
Felix Jung (Master Student)
Nathan Mikhaylenko (PhD Student)
-
2020
Lukas Weil (Master Student)
Kevin Frey (Master Student)
Kevin Schneider (Master Student)
Caroline Ott (Master Student)
-
2019
Patrick Blume (Master Student)
Marc Gottlieb (Bachelor Student)
-
2018
David Zimmer (Master Student)
Benedikt Venn (Master Student)
Esther Wieczorek (Master Student)
Isabella Christina Capilla Navarro (Master Student)
-
2017
Kevin Schneider (Bachelor Student)
-
2016
Lukas Weil (Bachelor Student)
David Zimmer (Bachelor Student)
Sabrina Gödel (Master Student)
-
2015
Esther Wieczorek (Bachelor Student)
Paul Menges (Bachelor Student)
Publications
View our selected publications
Teaching
Our teaching activity for bachelor and master students
Lecture for Bachelor Biology
Bioinformatics & Biophysics
The lecture will introduce models and recipes for biological systems. It focuses on fundamental concepts of bioinformatics and provides a model-based understanding to improve the knowledge of biological systems quantitatively. Main topics are:
- Finding hidden patterns in biology
- Comparing biological sequences
- Molecular and structure prediction
- Creating and analysing biological network models
- Modeling kinetic and stochastic processes in living systems
Reading Course for Master Biology
Biological Data Science
3 CP - Sommersemester 2024
In Computational Systems Biology, millions of data points on proteins, genes, tissues, and more are often analyzed and integrated for systemic studies. The volume and complexity of this data make it challenging to extract meaningful patterns and biological knowledge from it. Consequently, employing advanced methodologies becomes exceedingly crucial to solve such problems on a global scale. This course will provide students with fundamental knowledge that empowers them to understand the application of quantitative methods in addressing biological challenges and facilitating innovative breakthroughs.
Lecture for Mixed Audience
Scientific Programming for Biologists
3 CP - Wintersemester 2023/24
Practical Course for Bachelor Biology / Master Biology
Computational Systems Biology
10 ECTS - Semester-missing
The Advanced Practical Course in Computational Systems Biology is designed to provide students with practical experience and advanced knowledge in analyzing biological systems using computational techniques. The course consists of four modules:
- Programming Warm-Up: Students refresh their programming skills, focusing on solving biological problems.
- Organism-wide Transcriptomics Analysis: Students learn how to analyze RNA sequencing data to identify differentially expressed genes and understand gene expression patterns.
- Inference of Gene Regulatory Networks: Students explore methods for inferring gene regulatory networks from gene expression data and literature data, gaining insights into complex regulatory interactions among genes and proteins.
- Automated High-Throughput Literature Search: Students utilize a ChatGTP-like large language model to automate literature search and extract relevant information from scientific articles.
Lecture for Bachelor Biology
Bioinformatics & Biophysics
4 CP - Sommersemester 2023
The lecture will introduce models and recipes for biological systems. It focuses on fundamental concepts of bioinformatics and provides a model-based understanding to improve the knowledge of biological systems quantitatively. Main topics are:
- Finding hidden patterns in biology
- Comparing biological sequences
- Molecular and structure prediction
- Creating and analysing biological network models
- Modeling kinetic and stochastic processes in living systems
Reading Course for Master Biology
Biological Data Science
3 CP - Sommersemester 2024
In Computational Systems Biology, millions of data points on proteins, genes, tissues, and more are often analyzed and integrated for systemic studies. The volume and complexity of this data make it challenging to extract meaningful patterns and biological knowledge from it. Consequently, employing advanced methodologies becomes exceedingly crucial to solve such problems on a global scale. This course will provide students with fundamental knowledge that empowers them to understand the application of quantitative methods in addressing biological challenges and facilitating innovative breakthroughs.
Lecture for Mixed Audience
Scientific Programming for Biologists
3 CP - Wintersemester 2023/24
Prof. Dr. Timo Mühlhaus
Computational Systems Biology
RPTU University of Kaiserslautern
Paul-Ehrlich-Str. 23 R109
67663 Kaiserslautern, Germany
+ 49 631 205 4657
+ 49 631 205 3799