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.

  • Research data management (RDM)

    We are committed to the success of FAIR (Findable, Accessible, Interoperable, and Reusable) and open research data. Research data possess immense value, which, when combined with tomorrow's technologies such as machine and deep learning, can unlock answers to questions we cannot even conceive today. Therefore, the flexible contextualization of research data with machine-actionable metadata is essential to advance modern science.

  • Biological data science

    Modern technologies now allow researchers to simultaneously study biological organisms and processes across various molecular layers and in diverse biological contexts. To leverage this wealth of data, we are developing advanced methods for both supervised and unsupervised analysis of multi-modal omics data using cutting-edge machine learning and statistical modeling techniques. As part of fslabs.org, we contribute to the open-source data analysis library environment, ensuring that our innovations are accessible to the broader research community. Our methods enable comprehensive, data-driven integration and analysis of data derived from multiple omics technologies and varied biological scenarios, thereby enhancing our understanding of complex biological systems.

  • Prediction of acclimation modulators and integrators based on ‘omics data

    Acclimation responses involve complex interactions among genes, proteins, and metabolites, resulting in both general and specific elements. Previously, we focused on extracting response-specific structural models from complex 'omics data using functional constraint aggregation and network topology inference.

Research data management (RDM)

We are committed to the success of FAIR (Findable, Accessible, Interoperable, and Reusable) and open research data. Research data possess immense value, which, when combined with tomorrow's technologies such as machine and deep learning, can unlock answers to questions we cannot even conceive today. Therefore, the flexible contextualization of research data with machine-actionable metadata is essential to advance modern science.

We draw inspiration from the open-source software community's success, developing approaches that enable the biological community to collaboratively build a community-wide FAIR research data resource. Our research group participates in the National Research Data Infrastructure (NFDI) initiative with the DataPLANT project, which empowers plant researchers to engage in a thriving RDM ecosystem without barriers.

Biological data science

Modern technologies now allow researchers to simultaneously study biological organisms and processes across various molecular layers and in diverse biological contexts. To leverage this wealth of data, we are developing advanced methods for both supervised and unsupervised analysis of multi-modal omics data using cutting-edge machine learning and statistical modeling techniques. As part of fslabs.org, we contribute to the open-source data analysis library environment, ensuring that our innovations are accessible to the broader research community. Our methods enable comprehensive, data-driven integration and analysis of data derived from multiple omics technologies and varied biological scenarios, thereby enhancing our understanding of complex biological systems.

Prediction of acclimation modulators and integrators based on ‘omics data

Acclimation responses involve complex interactions among genes, proteins, and metabolites, resulting in both general and specific elements. Previously, we focused on extracting response-specific structural models from complex 'omics data using functional constraint aggregation and network topology inference.

Predicting modulators and integrators based on regulatory network topology and differential expression levels remains challenging, especially with limited acclimation data. However, incorporating additional regulatory characteristics of proteins—such as thermostability, aggregation propensity, intrinsic disorder, and post-translational modifications—can improve this identification.

This project proposes a novel approach using sequential meta-learning to integrate these regulatory characteristics, overcoming data sparsity challenges. In collaboration with CRC experimental groups, we will test our model’s predictions by introducing thermostable protein homologs into plant and algal cells. These experiments are expected to reduce acclimation capabilities and cause growth retardation, validating our approach in experimental evolution assays.

Team

Our research team on CSB

Janine Mertel (Team Assistant)

Janine Mertel

Team Assistant
Timo Mühlhaus (Professor)

Timo Mühlhaus

Professor
David Zimmer (PostDoc)

David Zimmer

PostDoc
Felix Jung (PhD Student)

Felix Jung

PhD Student
Oliver Maus (PhD Student)

Oliver Maus

PhD Student
Kevin Frey (PhD Student)

Kevin Frey

PhD Student
Lukas Weil (PhD Student)

Lukas Weil

PhD Student
Kevin Schneider (PhD Student)

Kevin Schneider

PhD Student
Caroline Ott (PhD Student)

Caroline Ott

PhD Student
Christopher Lux (PhD Student)

Christopher Lux

PhD Student
Annika Paul (Bachelor Student)

Annika Paul

Pauline Hans (Bachelor Student)

Pauline Hans

TS

Tobias Scheid

  • 2023

    Selina Ziegler (Master Student)

  • 2022

    Felix Jung (Master Student)

    David Zimmer (PhD Student)

    Christopher Lux (Master Student)

    Nathan Mikhaylenko (PhD Student)

  • 2020

    Kevin Frey (Master Student)

    Lukas Weil (Master Student)

    Kevin Schneider (Master Student)

    Caroline Ott (Master Student)

  • 2019

    Patrick Blume (Master Student)

    Marc Gottlieb (Bachelor Student)

  • 2018

    David Zimmer (Master Student)

    Esther Wieczorek (Master Student)

    Isabella Christina Capilla Navarro (Master Student)

    Benedikt Venn (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

BMC bioinformatics
2024
Temporal classification of short time series data
Venn B, Leifeld T, Zhang P, Mühlhaus T
BMC bioinformatics
2024
Temporal classification of short time series data
Venn B, Leifeld T, Zhang P, Mühlhaus T
Data
2023
DataPLAN: A Web-Based Data Management Plan Generator for the Plant Sciences
Zhou X, Beier S, Brilhaus D, {Martins Rodrigues} C, Mühlhaus T, von Suchodoletz D, Twyman R, Usadel B, Kranz A
International Journal of Molecular Sciences
2023
DeepSTABp: A Deep Learning Approach for the Prediction of Thermal Protein Stability
Jung F, Frey K, Zimmer D, Mühlhaus T
Nature Communications
2023
Proteomics and constraint-based modelling reveal enzyme kinetic properties of Chlamydomonas reinhardtii on a genome scale
Arend M, Zimmer D, Xu R, Sommer F, Mühlhaus T, Nikoloski Z
Plant Cell and Environment
2023
Competition co-immunoprecipitation reveals the interactors of the chloroplast CPN60 chaperonin machinery
Ries F, Weil H, Herkt C, Mühlhaus T, Sommer F, Schroda M, Willmund F
microLife
2023
Characterization of a soluble library of the Pseudomonas aeruginosa PAO1 membrane proteome with emphasis on c-di-GMP turnover enzymes
Scherhag A, Räschle M, Unbehend N, Venn B, Glueck D, Mühlhaus T, Keller S, {Pérez Patallo} E, Zehner S, Frankenberg-Dinkel N
The Plant journal : for cell and molecular biology
2023
PLANTdataHUB: a collaborative platform for continuous FAIR data sharing in plant research
Weil H, Schneider K, Tschöpe M, Bauer J, Maus O, Frey K, Brilhaus D, {Martins Rodrigues} C, Doniparthi G, Wetzels F, Lukasczyk J, Kranz A, Grüning B, Zimmer D, Deßloch S, von Suchodoletz D, Usadel B, Garth C, Mühlhaus T
International Journal of Molecular Sciences
2023
DeepSTABp: A Deep Learning Approach for the Prediction of Thermal Protein Stability
Jung F, Frey K, Zimmer D, Mühlhaus T
2022
DataPLANT – Tools and Services to structure the Data Jungle for fundamental plant researchers
Mühlhaus T, Brillhaus D, Tschöpe M, Maus O, Grüning B, Garth C, {Martins Rodrigues} C, von Suchodoletz D
Journal of experimental botany
2022
Complexome profiling on the Chlamydomonas lpa2 mutant reveals insights into PSII biogenesis and new PSII associated proteins
Spaniol B, Lang J, Venn B, Schake L, Sommer F, Mustas M, Geimer S, Wollman F, Choquet Y, Mühlhaus T, Schroda M
2022
Immutable yet evolving: ARCs for permanent sharing in the research data-time continuum
Garth C, Lukasczyk J, Mühlhaus T, Venn B, Krüger J, Glogowski K, {Martins Rodrigues} C, von Suchodoletz D
F1000Research
2022
Plotly.NET: A fully featured charting library for .NET programming languages
Schneider K, Venn B, Mühlhaus T
EMBO Rep
2022
A longer isoform of Stim1 is a negative SOCE regulator but increases cAMP-modulated NFAT signaling
Knapp M, Alansary D, Poth V, Förderer K, Sommer F, Zimmer D, Schwarz Y, Künzel N, Kless A, Machaca K, Helms V, Mühlhaus T, Schroda M, Lis A, Niemeyer B
2022
Data Stewards as ambassadors between the NFDI and the community
von Suchodoletz D, Mühlhaus T, Brillhaus D, Jabeen H, Usadel B, Krüger J, Gauza H, {Martins Rodrigues} C
Cell Systems
2022
What differentiates a stress response from responsiveness in general?
Vogel C, Balázsi G, Löwer A, Jiang C, Schmid A, Sommer M, Yang L, Münch C, Wang A, Israni-Winger K, Mühlhaus T, {Des Marais} D, Oster H, Socolovsky M
Communications biology
2022
Systems-wide analysis revealed shared and unique responses to moderate and acute high temperatures in the green alga Chlamydomonas reinhardtii
Zhang N, Mattoon E, McHargue W, Venn B, Zimmer D, Pecani K, Jeong J, Anderson C, Chen C, Berry J, Xia M, Tzeng S, Becker E, Pazouki L, Evans B, Cross F, Cheng J, Czymmek K, Schroda M, Mühlhaus T, Zhang R
Frontiers in plant science
2021
Data Management and Modeling in Plant Biology
Krantz M, Zimmer D, Adler S, Kitashova A, Klipp E, Mühlhaus T, Nägele T
Molecular Neurodegeneration
2021
Parkinson mice show functional and molecular changes in the gut long before motoric disease onset
Gries M, Christmann A, Schulte S, Weyland M, Rommel S, Martin M, Baller M, Röth R, Schmitteckert S, Unger M, Liu Y, Sommer F, Mühlhaus T, Schroda M, Timmermans J, Pintelon I, Rappold G, Britschgi M, Lashuel H, Menger M, Laschke M, Niesler B, Schäfer K
Journal of experimental botany
2021
Complexome profiling on the Chlamydomonas lpa2 mutant reveals insights into PSII biogenesis and new PSII associated proteins
Spaniol B, Lang J, Venn B, Schake L, Sommer F, Mustas M, Geimer S, Wollman F, Choquet Y, Mühlhaus T, Schroda M
Cell Reports
2021
The chaperone-binding activity of the mitochondrial surface receptor Tom70 protects the cytosol against mitoprotein-induced stress
Backes S, Bykov Y, Flohr T, Räschle M, Zhou J, Lenhard S, Krämer L, Mühlhaus T, Bibi C, Jann C, Smith J, Steinmetz L, Rapaport D, Storchová Z, Schuldiner M, Boos F, Herrmann J
Biological Chemistry
2021
iMLP, a predictor for internal matrix targeting-like sequences in mitochondrial proteins
Schneider K, Zimmer D, Nielsen H, Herrmann J, Mühlhaus T
Nature Chemical Biology
2021
Peroxiredoxins couple metabolism and cell division in an ultradian cycle
Amponsah P, Yahya G, Zimmermann J, Mai M, Mergel S, Mühlhaus T, Storchova Z, Morgan B
Science advances
2021
Topology of the redox network during induction of photosynthesis as revealed by time-resolved proteomics in tobacco
Zimmer D, Swart C, Graf A, Arrivault S, Tillich M, Proost S, Nikoloski Z, Stitt M, Bock R, Mühlhaus T*, Boulouis A*
Computational and Structural Biotechnology Journal
2021
Identifying the minimum amplicon sequence depth to adequately predict classes in eDNA-based marine biomonitoring using supervised machine learning
Dully V, Wilding T, Mühlhaus T, Stoeck T
Biological Chemistry
2021
iMLP: A predictor for internal matrix targeting-like sequences in mitochondrial proteins
Schneider K, Zimmer D, Nielsen H, Herrmann J, Mühlhaus T
Science advances
2021
Topology of the redox network during induction of photosynthesis as revealed by time-resolved proteomics in tobacco
Zimmer D, Swart C, Graf A, Arrivault S, Tillich M, Proost S, Nikoloski Z, Stitt M, Bock R, Mühlhaus T*, Boulouis A*
Plant physiology
2020
Identification of chloroplast envelope proteins with critical importance for cold acclimation
Trentmann O, Mühlhaus T, Zimmer D, Sommer F, Schroda M, Haferkamp I, Keller I, Pommerrenig B, Neuhaus H
BMC Plant Biol
2020
Identification of small RNAs during cold acclimation in Arabidopsis thaliana
Tiwari B, Habermann K, Arif M, Weil H, Garcia-Molina A, Kleine T, Mühlhaus T, Frank W
Frontiers in plant science
2020
Overexpression of Sedoheptulose-1,7-Bisphosphatase Enhances Photosynthesis in Chlamydomonas reinhardtii and Has No Effect on the Abundance of Other Calvin-Benson Cycle Enzymes
Hammel A, Sommer F, Zimmer D, Stitt M, Mühlhaus T, Schroda M
Biochimica et biophysica acta. Bioenergetics
2020
Clingy genes: Why were genes for ribosomal proteins retained in many mitochondrial genomes?
Bertgen L, Mühlhaus T, Herrmann J
Molecular cell
2020
The NADH Dehydrogenase Nde1 Executes Cell Death after Integrating Signals from Metabolism and Proteostasis on the Mitochondrial Surface
Saladi S, Boos F, Poglitsch M, Meyer H, Sommer F, Mühlhaus T, Schroda M, Schuldiner M, Madeo F, Herrmann J
2020
A Bloom Filter-Based Framework for Interactive Exploration of Large Scale Research Data
Doniparthi G, Mühlhaus T, Deßloch S
The Plant cell
2020
Vernalization Alters Sink and Source Identities and Reverses Phloem Translocation from Taproots to Shoots in Sugar Beet (Beta vulgaris)
{Martins Rodrigues} C, Müdsam C, Keller I, Zierer W, Czarnecki O, Corral J, Reinhardt F, Nieberl P, Fiedler-Wieschers K, Sommer F, Schroda M, Mühlhaus T, Harms K, Flügge U, Sonnewald U, Koch W, Ludewig F, Neuhaus H, Pommerrenig B
Entropy
2020
TMEA: A Thermodynamically Motivated Framework for Functional Characterization of Biological Responses to System Acclimation
Schneider K, Venn B, Mühlhaus T
The Plant journal : for cell and molecular biology
2020
Acclimation in plants - the Green Hub consortium
Kleine T, Nägele T, Neuhaus H, Schmitz-Linneweber C, Fernie A, Geigenberger P, Grimm B, Kaufmann K, Klipp E, Meurer J, Möhlmann T, Mühlhaus T, Naranjo B, Nickelsen J, Richter A, Ruwe H, Schroda M, Schwenkert S, Trentmann O, Willmund F, Zoschke R, Leister D
iScience
2020
Translational Components Contribute to Acclimation Responses to High Light, Heat, and Cold in Arabidopsis
Garcia-Molina A, Kleine T, Schneider K, Mühlhaus T, Lehmann M, Leister D
Entropy
2020
TMEA: A Thermodynamically Motivated Framework for Functional Characterization of Biological Responses to System Acclimation
Schneider K, Venn B, Mühlhaus T
Biotechnology journal
2019
Metabolic engineering of Corynebacterium glutamicum for high-level ectoine production - design, combinatorial assembly and implementation of a transcriptionally balanced heterologous ectoine pathway
Gießelmann G, Dietrich D, Jungmann L, Kohlstedt M, Jeon E, Yim S, Sommer F, Zimmer D, Mühlhaus T, Schroda M, Jeong K, Becker J, Wittmann C
Journal of neurochemistry
2019
Poor transcript-protein correlation in the brain: negatively correlating gene products reveal neuronal polarity as a potential cause
Moritz C, Mühlhaus T, Tenzer S, Schulenborg T, Friauf E
Plant physiology
2019
The Chlamydomonas deg1c Mutant Accumulates Proteins Involved in High Light Acclimation
Theis J, Lang J, Spaniol B, Ferté S, Niemeyer J, Sommer F, Zimmer D, Venn B, Mehr S, Mühlhaus T, Wollman F, Schroda M
Journal of Open Source Software
2019
FSharpGephiStreamer: An idiomatic bridge between F{\#} and network visualization
Schneider K, Mühlhaus T
Plant Physiol
2019
The Role of Plastidic Trigger Factor Serving Protein Biogenesis in Green Algae and Land Plants
Rohr M, Ries F, Herkt C, Gotsmann V, Westrich L, Gries K, Trösch R, Christmann J, Chaux-Jukic F, Jung M, Zimmer D, Mühlhaus T, Sommer F, Schroda M, Keller S, Möhlmann T, Willmund F
18th ECC
2019
Curve form based quantization of short time series data
Leifeld T, Venn B, Cui S, Zhang Z, Mühlhaus T, Zhang P
Frontiers in plant science
2018
Artificial Intelligence Understands Peptide Observability and Assists With Absolute Protein Quantification
Zimmer D, Schneider K, Sommer F, Schroda M, Mühlhaus T
BIO-PROTOCOL
2018
Detection of Internal Matrix Targeting Signal-like Sequences (iMTS-Ls) in Mitochondrial Precursor Proteins Using the TargetP Prediction Tool
Boos F, Mühlhaus T, Herrmann J
Nature Plants
2018
Commonalities and differences of chloroplast translation in a green alga and land plants
Trösch R, Barahimipour R, Gao Y, Badillo-Corona J, Gotsmann V, Zimmer D, Mühlhaus T, Zoschke R, Willmund F
New Phytologist
2018
Investigations on VELVET regulatory mutants confirm the role of host tissue acidification and secretion of proteins in the pathogenesis of Botrytis cinerea
Müller N, Leroch M, Schumacher J, Zimmer D, Könnel A, Klug K, Leisen T, Scheuring D, Sommer F, Mühlhaus T, Schroda M, Hahn M
The Journal of cell biology
2018
Tom70 enhances mitochondrial preprotein import efficiency by binding to internal targeting sequences
Backes S, Hess S, Boos F, Woellhaf M, Gödel S, Jung M, Mühlhaus T, Herrmann J
Frontiers in plant science
2018
Absolute Quantification of Major Photosynthetic Protein Complexes in Chlamydomonas reinhardtii Using Quantification Concatamers (QconCATs)
Hammel A, Zimmer D, Sommer F, Mühlhaus T, Schroda M
Frontiers in plant science
2018
Artificial Intelligence Understands Peptide Observability and Assists With Absolute Protein Quantification
Zimmer D, Schneider K, Sommer F, Schroda M, Mühlhaus T
Plant molecular biology
2017
Substrates of the chloroplast small heat shock proteins 22E/F point to thermolability as a regulative switch for heat acclimation in Chlamydomonas reinhardtii
Rütgers M, Muranaka L, Mühlhaus T, Sommer F, Thoms S, Schurig J, Willmund F, Schulz-Raffelt M, Schroda M
Plant Physiology
2016
GUN1 controls accumulation of the plastid ribosomal protein S1 at the protein level and interacts with proteins involved in plastid protein homeostasis
Tadini L, Pesaresi P, Kleine T, Rossi F, Guljamow A, Sommer F, Mühlhaus T, Schroda M, Masiero S, Pribil M, Rothbart M, Hedtke B, Grimm B, Leister D
Proceedings of the National Academy of Sciences of the United States of America
2016
A repeat protein links Rubisco to form the eukaryotic carbon-concentrating organelle
Mackinder L, Meyer M, Mettler-Altmann T, Chen V, Mitchell M, Caspari O, {Freeman Rosenzweig} E, Pallesen L, Reeves G, Itakura A, Roth R, Sommer F, Geimer S, Muhlhaus T, Schroda M, Goodenough U, Stitt M, Griffiths H, Jonikas M
The Plant journal : for cell and molecular biology
2015
The Chlamydomonas heat stress response
Schroda M, Hemme D, Mühlhaus T
Nature Plants
2015
Identification of the transporter responsible for sucrose accumulation in sugar beet taproots
Jung B, Ludewig F, Schulz A, Meißner G, Wöstefeld N, Flügge U, Pommerrenig B, Wirsching P, Sauer N, Koch W, Sommer F, Mühlhaus T, Schroda M, Cuin T, Graus D, Marten I, Hedrich R, Neuhaus H
Biochimica et biophysica acta
2015
ATP-dependent molecular chaperones in plastids - More complex than expected
Trösch R, Mühlhaus T, Schroda M, Willmund F
Plant Cell
2014
Conditional Depletion of the Chlamydomonas Chloroplast ClpP Protease Activates Nuclear Genes Involved in Autophagy and Plastid Protein Quality Control
Ramundo S, Casero D, Mühlhaus T, Hemme D, Sommer F, Crevecoeur M, Rahire M, Schroda M, Rusch J, Goodenough U, Pellegrini M, Perez-Perez M, Crespo J, Schaad O, Civic N, Rochaix J
The Plant cell
2014
Nitrogen-Sparing Mechanisms in Chlamydomonas Affect the Transcriptome, the Proteome, and Photosynthetic Metabolism
Schmollinger S*, Mühlhaus T*, Boyle N, Blaby I, Casero D, Mettler T, Moseley J, Kropat J, Sommer F, Strenkert D, Hemme D, Pellegrini M, Grossman A, Stitt M, Schroda M, Merchant S
The Plant cell
2014
Systems Analysis of the Response of Photosynthesis, Metabolism, and Growth to an Increase in Irradiance in the Photosynthetic Model Organism Chlamydomonas reinhardtii
Mettler T, Mühlhaus T, Hemme D, Schöttler M, Rupprecht J, Idoine A, Veyel D, Pal S, Yaneva-Roder L, Winck F, Sommer F, Vosloh D, Seiwert B, Erban A, Burgos A, Arvidsson S, Schönfelder S, Arnold A, Günther M, Krause U, Lohse M, Kopka J, Nikoloski Z, Mueller-Roeber B, Willmitzer L, Bock R, Schroda M, Stitt M
Methods in molecular biology (Clifton, N.J.)
2014
Identification and validation of protein-protein interactions by combining co-immunoprecipitation, antigen competition, and stable isotope labeling
Sommer F, Mühlhaus T, Hemme D, Veyel D, Schroda M
The Plant cell
2014
Systems-Wide Analysis of Acclimation Responses to Long-Term Heat Stress and Recovery in the Photosynthetic Model Organism Chlamydomonas reinhardtii
Hemme D, Veyel D, Mühlhaus T, Sommer F, Jüppner J, Unger A, Sandmann M, Fehrle I, Schönfelder S, Steup M, Geimer S, Kopka J, Giavalisco P, Schroda M
The Plant cell
2012
Evidence for a role of VIPP1 in the structural organization of the photosynthetic apparatus in Chlamydomonas
Nordhues A, Schöttler M, Unger A, Geimer S, Schönfelder S, Schmollinger S, Rütgers M, Finazzi G, Soppa B, Sommer F, Mühlhaus T, Roach T, Krieger-Liszkay A, Lokstein H, Crespo J, Schroda M
Mol Cell Proteomics
2011
Quantitative shotgun proteomics using a uniform 15N-labeled standard to monitor proteome dynamics in time course experiments reveals new insights into the heat stress response of Chlamydomonas reinhardtii
Mühlhaus T, Weiss J, Hemme D, Sommer F, Schroda M
International review of cell and molecular biology
2010
New insights into the roles of molecular chaperones in Chlamydomonas and Volvox
Nordhues A, Miller S, Mühlhaus T, Schroda M
Systembiologie.de
2010
Wie Pflanzen auf Umweltveränderungen reagieren
Hemme D, Weiss J, Mühlhaus T, Sommer F, Schroda M
Plant Signal Behav
2009
A 'foldosome' in the chloroplast?
Schroda M, Mühlhaus T
The Journal of biological chemistry
2008
Assistance for a chaperone: Chlamydomonas HEP2 activates plastidic HSP70B for cochaperone binding
Willmund F, Hinnenberger M, Nick S, Schulz-Raffelt M, Mühlhaus T, Schroda M
The Journal of biological chemistry
2007
The NH2-terminal domain of the chloroplast GrpE homolog CGE1 is required for dimerization and cochaperone function in vivo
Willmund F*, Mühlhaus T*, Wojciechowska M, Schroda M
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Teaching

Our teaching activity for bachelor and master students

BIO-BTE-10-L-4
Project

Project for Bachelor Molekulare Biologie

Scientific Programming for Biologists

9 CP - Semester-missing
OpenOlat

Put your skills into practice with an individual project in the field of bioinformatics. This course offers a unique opportunity to apply theoretical knowledge in a practical setting, allowing you to tackle real-world problems and develop solutions that can have a significant impact on the field.
Potential project topics cover the entire spectrum of bioinformatics, offering a diverse range of challenges and learning experiences. You can explore various areas including:
  • Algorithm Development: Implement algorithms for analyzing biological data, such as DNA sequences, protein structures, or gene expression profiles. These algorithms can help identify patterns, make predictions, and uncover new insights into biological processes.
  • Data Analysis and Visualization: Apply and implement methods to process and visualize large-scale biological data sets. This could involve creating visualizations to represent complex data or developing pipelines to automate data analysis workflows.
  • Systems Biology: Work on integrating data from various biological systems to understand how they interact and function as a whole. Projects might involve modeling biological networks, or analyzing cellular processes and metabolic pathways.
  • Web Service Implementation: Design and implement web-based tools and services that allow researchers to access or analyze biological data. This could include creating databases, developing APIs, or building user-friendly interfaces for existing bioinformatics tools.
You have the flexibility to discuss your own project idea or choose from a list of proposed projects. By engaging in these projects, you will gain hands-on experience, enhance your problem-solving skills, and develop a deeper understanding of bioinformatics. This practical approach not only reinforces your existing knowledge but also prepares you for future research or professional work in the field.

BIO-CSB-10-L-3
Practical Course

Practical Course for Bachelor Biology / Master Biology

Computational Systems Biology

10 ECTS - Semester-missing
OpenOlat

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.

KIS-ID-missing
Lecture

Lecture for Bachelor Biology

Bioinformatics

4 CP - Sommersemester 2024
OpenOlat

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

BIO-BIO-10-W-1
Vorlesung

Vorlesung for Keine Zugangsvoraussetzungen

Einführung in die Programmierung für Biologie

Wintersemester 2024/25
OpenOlat

Das Hauptziel dieser Lehrveranstaltung inklusive begleitender Übungen besteht darin, den Teilnehmenden ein Verständnis für die fundamentalen Prinzipien der funktionalen und objektorientierten Programmierung zu vermitteln. Zusätzlich sollen sie sich mit essenziellen Datenstrukturen und Algorithmen vertraut machen. Dabei werden grundlegende konzeptionelle Grundlagen, Methoden und Techniken zur Strukturierung von Daten und zur Entwicklung von Algorithmen vermittelt. Des Weiteren werden Tools des wissenschaftlichen Rechnens und der Datenverarbeitung präsentiert, insbesondere solche, die zur Visualisierung und Verarbeitung von Messdaten genutzt werden können.

Practical Course

Practical Course for Bachelor Biology / Master Biology

Bioinformatik

10 ECTS - Semester-missing
OpenOlat

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.

KIS-ID-missing
Lecture

Lecture for Bachelor Biology

Bioinformatics

4 CP - Sommersemester 2024
OpenOlat

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

BIO-BIO-10-W-1
Vorlesung

Vorlesung for Keine Zugangsvoraussetzungen

Einführung in die Programmierung für Biologie

Wintersemester 2024/25
OpenOlat

Das Hauptziel dieser Lehrveranstaltung inklusive begleitender Übungen besteht darin, den Teilnehmenden ein Verständnis für die fundamentalen Prinzipien der funktionalen und objektorientierten Programmierung zu vermitteln. Zusätzlich sollen sie sich mit essenziellen Datenstrukturen und Algorithmen vertraut machen. Dabei werden grundlegende konzeptionelle Grundlagen, Methoden und Techniken zur Strukturierung von Daten und zur Entwicklung von Algorithmen vermittelt. Des Weiteren werden Tools des wissenschaftlichen Rechnens und der Datenverarbeitung präsentiert, insbesondere solche, die zur Visualisierung und Verarbeitung von Messdaten genutzt werden können.

Open Source

Take a look on our public repositories on github. Feel free to contribute!

View Github

Contact

Faculty Impressum Datenschutz

Prof. Dr. Timo Mühlhaus
Computational Systems Biology

RPTU University of Kaiserslautern
Erwin-Schrödinger-Str. 56 R244
67663 Kaiserslautern, Germany

+ 49 631 205 4657
+ 49 631 205 3799