Teaching

WS 19/20 Systems BioMedicine

In this module for master students which attended Introduction to Bioinformatics I + II as well as Advanced Bioinformatics, we will introduce concepts of systems biology and describe its transition to systems medicine. The focus is on bioinformatic methods and the following topics are presented, among others:

• Availability of OMICS data
• Aims of precision and personalized medicine
• Complex diseases (cancer, multiple sclerosis, …)
• Network Medicine
• Cancer genomics and identification of disease-relevant variants
• Breath analysis
• De novo endophenotyping and patient stratification
• Drug target and biomarker discovery
• Disease subtyping
• Drug repositioning
• Lipidomics
• Privacy-aware machine learning

Lecture: Wednesday, 10:15 - 12:00 Uhr, Dr. Markus List, Room D 108, Richard-Wagner-Str. 10
Exercises:  Wednesday, 13:00 - 16:00 Uhr, Room D 102Richard-Wagner-Str. 10
Exercises held by Dr. Markus List, Gihanna Galindez

You can register for this lecture through TUM online. LMU students not enrolled with TUM can register via e-mail.

WS 19/20 - Introduction to Bioinformatics I

​​In this lecture we learn about the basic concepts that link biology and computer science.  We learn about the basics of molecular biology, methods for generating biological data as well as algorithms for their analysis. 

Lecture: Wednesday, 08:30 - 10:00 Uhr, Prof. Jan Baumbach, Room C 006, Luisenstr. 37
Exercise Group 1:  Wednesday, 10:00 - 13:00 Uhr, Room D 114Richard-Wagner-Str. 10
Exercise Group 2:  Wednesday, 10:00 - 13:00 Uhr, Room D 102Richard-Wagner-Str. 10
Exercises held by Dr. Markus List, Amit Fenn, Michael Lauber

You can register for this lecture through TUM online. LMU students not enrolled with TUM can register via e-mail. Additional information and course material can be found in the TUM Moodle.

WS 19/20 Bioinformatics Journal Club

In cooperation with the Graduate School Weihenstephan we offer a Journal Club in Bioinformatics. Here we discuss late breaking research in bioinformatics, learn about good paper writing and engage in critical discussions across diverse topics in the field. More information can be found on the website of the Graduate School.

Date: Every Monday throughout the semester at 11:30

Contact: Markus List

WS 19/20 - Problem-based Learning

​In problem-based learning, students will learn about scientific principles and necessary techniques for, e.g. literature search, writing, presentation. Students will apply these skills practically. This is the second part of the module which started in SS19.

Registration: Volker Heun, LMU

Contact: Tim Kacprowski and Josch Pauling

SS 19 Advanced Practical Course Bioinformatics

In this practical course, students will regularly participate in scientific activities at the Chair of Experimental Bioinformatics in Weihenstephan, including journal club and seminars. In addition, they will work on solving a practical task from one of the following topics:

1. Systems Medicine - Mechanistic insights into diseases

2. Drug re-purposing

3. Privacy-aware biomedical decision making

3. Multi-omics data integration

4. Cancer subtyping and biomarker discovery

5. Single-cell dynamics 
 

Dates: 

- Pre-meeting: 30.04.2019, Garching

- Every Monday 11:30 - 15:00 throughout the semester in OG-L19, Maximus-von-Imhof-Forum 3, Freising-Weihenstephan

- Project presentations: 27.06.2019, Munich 

- Finalization and live demonstration: as block in week 23.-27.09.2019 OG-L19a, Maximus-von-Imhof-Forum 3, Freising-Weihenstephan

Registration: Volker Heun, LMU

Contact: Markus List and Jan Baumbach

SS 19 Problem-based Learning

In problem-based learning, students will learn about scientific principles and necessary techniques for, e.g. literature search, writing, presentation. Students will apply these skills practically.

Registration: Volker Heun, LMU

Contact: Tim Kacprowski and Josch Pauling

SS 19 - Bioinformatics Journal Club

In cooperation with the Graduate School Weihenstephan we offer a Journal Club in Bioinformatics. Here we discuss late breaking research in bioinformatics, learn about good paper writing and engage in critical discussions across diverse topics in the field. More information can be found on the website of the Graduate School.

Date: Every Monday throughout the semester at 11:30

Contact: Markus List

In this lecture, concepts of the two lectures "Introduction to Bioinformatics" are expanded. Students will learn in depth about current challenges in the field and about algorithms used to solve these in areas.

You can register for this lecture through TUM online. Additional information and course material can be found in the TUM Moodle.

Dates:

- Lecture: Thursday, 10:30 - 12:00 Uhr, Room D105, Richard-Wagner-Str. 10

- Exercise Group 1:  Thursday, 08:00 - 10:15 Uhr, Room D 105, Richard-Wagner-Str. 10

- Exercise Group 2:  Thursday, 08:00 - 10:15 Uhr, Room D 114, Richard-Wagner-Str. 10

Contact: Markus List and Jan Baumbach

In this lecture we build upon Introduction to Bioinformatics I and learn more about the basic concepts that link biology and computer science.  We learn about the basics of molecular biology, methods for generating biological data as well as algorithms for their analysis. 

You can register for this lecture through TUM online. Additional information and course material can be found in the TUM Moodle.

Dates:

- Lecture: Thursday, 08:30 - 10:00 Uhr, Room C024, Luisenstr. 37

- Exercise Group 1:  Thursday, 16:00 - 19:00 Uhr, Room D 114, Richard-Wagner-Str. 10

- Exercise Group 2:  Thursday, 16:00 - 19:00 Uhr, Room D 102, Richard-Wagner-Str. 10

Contact: Markus List and Jan Baumbach

WS 18/19 - Introduction to Bioinformatics I

​In this lecture we learn about the basic concepts that link biology and computer science.  We learn about the basics of molecular biology, methods for generating biological data as well as algorithms for their analysis. 

Lecture: Wednesday, 08:30 - 10:00 Uhr, Prof. Jan Baumbach, Room C 006, Luisenstr. 37
Exercise Group 1:  Wednesday, 10:00 - 13:00 Uhr, Room D 114Richard-Wagner-Str. 10
Exercise Group 2:  Wednesday, 10:00 - 13:00 Uhr, Room D 118Richard-Wagner-Str. 10
Exercises held by Dr. Markus List, Olga Lazareva and Manuela Lautizi

You can register for this lecture through TUM online. LMU students not enrolled with TUM can register via e-mail. Additional information and course material can be found in the TUM Moodle.

WS 18/19 - Bioinformatics Journal Club

In cooperation with the Graduate School Weihenstephan we offer a Journal Club in Bioinformatics. Here we discuss late breaking research in bioinformatics, learn about good paper writing and engage in critical discussions across diverse topics in the field. More information can be found on the website of the Graduate School.

WS 18/19 - Seminar on Big Data in Biomedicine

Here we offer a so-called Hauptseminar on the topic "Big Data in Biomedicine". Every student will pick a topic and prepare a presentation.

Registration: Via e-mail to Volker Heun, LMU.

First meeting:

October 17th, 10.00 o'clock, Room D116, Richard-Wagner-Str. 10

WS 18/19 - Seminar on Computational Systems Medicine

Here we offer a so-called Hauptseminar on the topic "Computational Systems Medicine". Every student will pick a topic and prepare a presentation.

Registration: Via e-mail to Volker Heun, LMU.

First meeting:

October 17th, 12.00 o'clock, Room A032, Luisenstr. 37

In this lecture we build upon Introduction to Bioinformatics I and learn more about the basic concepts that link biology and computer science.  We learn about the basics of molecular biology, methods for generating biological data as well as algorithms for their analysis. 

Lecture: Thursday, 09:45 - 11:15 Uhr, Prof. Jan Baumbach, Room 0501.EG.120 (TUM-Stammgelände zentral)
Exercise Group 1:  Thursday, 14:45 - 17:00 Uhr, Room D 102Richard-Wagner-Str. 10
Exercise Group 2:  Thursday,, 17:15 - 19:30 Uhr, Room D 105Richard-Wagner-Str. 10
Exercises held by Dr. Markus List and Jan Quell

You can register for this lecture through TUM online. Additional information and course material can be found in the TUM Moodle.

WS17/18 - Introduction to Bioinformatics / Computational Biology

​[DM8847/MM552, quarter 3 - 10 ECTS]

The purpose of this course is to give an understanding of computational problems in modern biomedical research. We will start with concrete medical questions, develop a formal problem description, setup an algorithmic/statistical model, solve it and subseqquently derive real-world answers from within the solved model. The course aims for giving a basic understanding of which problems arise in modern molecular biology and clinical research, and how these problems can be solved with appropriate computational tools. ​It is a class that needs regular attendance. Precondition for admittance to the exam will be the preparation  of exercise sheets.

Slides: 1 2 3 4 5 6 7 8 9

Exercises: 2 3 4 5 6 7 8 9

Exam project: It is part of the oral exam. Download the project description at this link.

WS17/18 - Introduction into Programming (2nd part, Java)

[DM550/DM857, quarter 4 - 5/10 ECTS]

The course gives an introduction to structured and object-oriented programming.

Expected learning outcome. After the course, the student is expected to be able to:

  • design object-oriented models for concrete problems.

  • devise a program structure based on the model.

  • implement the planned program in the concrete programming language used.

  • find and use adequate elements in the program library belonging to the  language.

  • plan and execute a testing of the program.

  • design and implement recursive solutions of problems.

  • design and implement abstract data types.

  • use basic tree structures and algorithms for these.

 

Slides: 1 2 3 4 5 6 7 8 9

 

Exercises: week 43 44 45 46 47 48

Exam project: The exam project will be explained during the lectures. In blackboard, you will find a SDU assignment called "Project exam 2nd part (java)". Deadline is January 12, 2018. Hand in via blackboard. No extensions or exceptions! Hold the deadline.

SS17 - Database Design and Programming

​[NAT/DM505, TEK/SB2-ORG, and TEK/IT-ORG2, quarter 1 - 5 ECTS]

The course gives an introduction to the use, design, and implementation of a relational database.

Expected learning outcome. After the course, the student is expected to be able to:

  • design a suitable conceptual model for a database, on the basis of a problem description

  • transform a conceptual model for a database into a suitable relational model

  • write SQL queries for a relational database

  • optimize a relational database through choice of indexes, use of equivalent SQL-expressions, and use of the theory of normal forms

  • access a  database from an application program.

  • describe work done on the above subjects in clear and precise language, and in a structured fashion

Lecture book: Hector Garcia-Molina; Jeffrey D. Ullman; Jennifer Widom: Database Systems: The Complete Book. Prentice Hall, 2008.

Evaluation: evals, actions

WS16/17 - Introduction into Programming (2nd part, Java)

[DM537/DM550, quarter 4 - 5/10 ECTS]

The course gives an introduction to structured and object-oriented programming.

Expected learning outcome. After the course, the student is expected to be able to:

  • design object-oriented models for concrete problems.

  • devise a program structure based on the model.

  • implement the planned program in the concrete programming language used.

  • find and use adequate elements in the program library belonging to the  language.

  • plan and execute a testing of the program.

  • design and implement recursive solutions of problems.

  • design and implement abstract data types.

  • use basic tree structures and algorithms for these.

Evaluation: evals, actions

SS16 - Database Design and Programming

​[NAT/DM505, TEK/SB2-ORG, and TEK/IT-ORG2, quarter 1 - 5 ECTS]

The course gives an introduction to the use, design, and implementation of a relational database.

Expected learning outcome. After the course, the student is expected to be able to:

 

  • design a suitable conceptual model for a database, on the basis of a problem description

  • transform a conceptual model for a database into a suitable relational model

  • write SQL queries for a relational database

  • optimize a relational database through choice of indexes, use of equivalent SQL-expressions, and use of the theory of normal forms

  • access a  database from an application program.

  • describe work done on the above subjects in clear and precise language, and in a structured fashion

 

Lecture book: Hector Garcia-Molina; Jeffrey D. Ullman; Jennifer Widom: Database Systems: The Complete Book. Prentice Hall, 2008.

Evaluation: eval, actions

WS15/16 - Introduction to Bioinformatics

[DM834, quarter 3 - 10 ECTS]

The purpose of this course is to give an understanding of computational problems in modern biomedical research. We will start with concrete medical questions, develop a formal problem description, setup an algorithmic/statistical model, solve it and subseqquently derive real-world answers from within the solved model. The course aims for giving a basic understanding of which problems arise in modern molecular biology and clinical research, and how these problems can be solved with appropriate computational tools.

​It is a class that needs regular attendance. Precondition for admittance to the exam will be the preparation  of exercise sheets.

 

Evaluation: eval, actions

WS15/16 - Introduction into Programming (2nd part, Java)

[DM537/DM550, quarter 4 - 5/10 ECTS]

The course gives an introduction to structured and object-oriented programming.

Expected learning outcome. After the course, the student is expected to be able to:

  • design object-oriented models for concrete problems.

  • devise a program structure based on the model.

  • implement the planned program in the concrete programming language used.

  • find and use adequate elements in the program library belonging to the  language.

  • plan and execute a testing of the program.

  • design and implement recursive solutions of problems.

  • design and implement abstract data types.

  • use basic tree structures and algorithms for these.

Evaluation: evals, actions

SS15 - Database Design and Programming

​[NAT/DM505, TEK/SB2-ORG, and TEK/IT-ORG2, quarter 1 - 5 ECTS]

The course gives an introduction to the use, design, and implementation of a relational database.

Expected learning outcome. After the course, the student is expected to be able to:

 

  • design a suitable conceptual model for a database, on the basis of a problem description

  • transform a conceptual model for a database into a suitable relational model

  • write SQL queries for a relational database

  • optimize a relational database through choice of indexes, use of equivalent SQL-expressions, and use of the theory of normal forms

  • access a  database from an application program.

  • describe work done on the above subjects in clear and precise language, and in a structured fashion

 

Lecture book: Hector Garcia-Molina; Jeffrey D. Ullman; Jennifer Widom: Database Systems: The Complete Book. Prentice Hall, 2008.

Evaluation: eval, actions

WS14/15 - Bioinformatics I

[DM834, quarter 3 - 10 ECTS]

The purpose of this course is to give an understanding of computational problems in modern biomedical research. We will start with concrete medical questions, develop a formal problem description, setup an algorithmic/statistical model, solve it and subseqquently derive real-world answers from within the solved model. The course aims for giving a basic understanding of which problems arise in modern molecular biology and clinical research, and how these problems can be solved with appropriate computational tools.

​It is a class that needs regular attendance. Precondition for admittance to the exam will be the preparation  of exercise sheets.

Evaluation: eval, actions

WS14/15 - Introduction into Programming (2nd part, Java)

[DM537/DM550, quarter 4 - 5/10 ECTS]

The course gives an introduction to structured and object-oriented programming.

Expected learning outcome. After the course, the student is expected to be able to:

  • design object-oriented models for concrete problems.

  • devise a program structure based on the model.

  • implement the planned program in the concrete programming language used.

  • find and use adequate elements in the program library belonging to the  language.

  • plan and execute a testing of the program.

  • design and implement recursive solutions of problems.

  • design and implement abstract data types.

  • use basic tree structures and algorithms for these.

Evaluation: DM536/DM550, DM537, actions

SS14 - Biomedical Data Clustering

[DMISA2 - Kickoff meeting: February 4, 4pm, IMADA seminar room, 5 ECTS, exam: presumably March 18-23]

The purpose of this course is to give an understanding of clustering algorithms. Given a huge set (millions) of data objects, the goal is to partition them into clusters such that objects within one group are more similar to each other than to objects from other clusters. Special attention will be paid to clustering algorithms with application in bioinformatics.

It is a seminar-style class with essentially two meetings. At the first meeting, we will assign different topics that the students will prepare a talk for and a short essay (two pages), which will be graded. The final meeting with the talks will probably be in the week March 18-23.​​

SS14 - Introduction to Bioinformatics

​[DMISA3 - First class: to be announced, 5 ECTS]

The purpose of this course is to give an understanding of computational problems in modern Systems Biology research. We will start with concrete biomedical questions, develop a formal problem description, setup an algorithmic/statistical model, solve it and subseqquently derive real-world answers from within the solved model. The course aims for giving a basic understanding of which problems arise in modern molecular biology and why&how these problems cannot be solved without appropriate computational tools.

It is a class that needs regular attendance. Precondition for admittance to the exam will be the preparation and handing-in of the exercise sheets.

WS11/12 - Computational Biomedicine

​[Kickoff meeting/first class meeting: April 25, 2pm, room 007, ZBI building: E2.1 - 2 SWS class + 1 SWS tutorials, classes: Wednesdays, 2-4pm, ]

[Classes: Wednesdays, 2-4pm, room 007, ZBI building: E2.1, Tutorials: Mondays, 4-5pm, room 007, ZBI building: E2.1]

The class is dedicated to Master students of Computer Science or Bioinformatics. We will discuss the following topics: transcription factor identification, binding site prediction, de novo motif discovery, CHiP-seq data analysis, regulatory network databases, regulatory network visualization, statistical network properties, regulatory network evolution and conservation, combined analysis of networks and gene expression data, and modeling of regulatory networks.

SS11 - Computational Systems Biology

[Kickoff meeting: Oct 25, 10am, room 001, ZBI building: E2.1]

The seminar will cover sequence analysis methods (transcription factor binding site prediction, regulatory modules) and network analysis methods (evolution of gene regulatory networks, conserved network models, over-represented network motifs), and databases for gene regulatory interactions (RegulonDB, CoryneRegNet, TransFac). Generally, this Seminar is going to be more applied.

SS11 - Clustering

[Kickoff meeting: Oct 25, 2pm, room 001, ZBI building: E2.1]

Here, we'll concentrate on all kinds of clustering approaches with typical applications in bioinformatics (protein homology detection, microarray data clustering). We'll start with more basic approaches, such as k-means, and finally discuss more advanced techniques, like Markov Clustering, Spectral Clustering or Transitivity Clustering. A basic understanding in algorithmics is necessary for this course. You will learn how to read, understand and present complex algorithmic problems and possible solutions.​​

WS10/11 - Computational Systems Biology

[Kickoff meeting/first class meeting: April 20, 2pm, room 007, ZBI building: E2.1 - 2 SWS class + 1 SWS tutorials]​

The seminar will cover sequence analysis methods (transcription factor binding site prediction, regulatory modules) and network analysis methods (evolution of gene regulatory networks, conserved network models, over-represented network motifs), and databases for gene regulatory interactions (RegulonDB, CoryneRegNet, TransFac). Generally, this Seminar is going to be more applied.

SS10 - Computational Systems Biology

[Kickoff meeting: Oct 26, 10am, room 001, ZBI building]

The seminar will cover sequence analysis methods (transcription factor binding site prediction, regulatory modules) and network analysis methods (evolution of gene regulatory networks, conserved network models, over-represented network motifs), and databases for gene regulatory interactions (RegulonDB, CoryneRegNet, TransFac). Generally, this Seminar is going to be more applied.

SS10 - Clustering

[Kickoff meeting: Oct 26, 2pm, room 001, ZBI building]

Here, we'll concentrate on all kinds of clustering approaches with typical applications in bioinformatics (protein homology detection, microarray data clustering). We'll start with more basic approaches, such as k-means, and finally discuss more advanced techniques, like Markov Clustering, Spectral Clustering or Transitivity Clustering. A basic understanding in algorithmics is necessary for this course. You will learn how to read, understand and present complex algorithmic problems and possible solutions.​​

Teaching portfolio

Please find my official teaching concept, portfolio, and philosophy at my corresponding SDU website.

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Chair of Experimental Bioinformatics

TUM School of Life Sciences Weihenstephan

Technical University of Munich

Tel: +49-8161-71-2136

E-Mail: exbio[a.t_))wzw.tum.de

Office: OG-L06