Fall 2016 / DM847
Introduction to Bioinformatics

General Information

Course introduction

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 subsequently 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 as well as the course project.

Expected learning outcome

  • Explain and understand the central dogma of molecular biology, central aspects of gene regulation, the basic principle of epigenetic DNA modifications, and specialties w.r.t. bacteria & phage genetics
  • Model ontologies for biomedical data dependencies
  • Design of systems biology databases
  • Explain and implement DNA & amino acid sequence analysis methods (HMMs, scoring matrices, and efficient statistics with them on data structures like suffix arrays)
  • Explain and implement statistical learning methods on biological networks (network enrichment)
  • Explain the specialties of bacterial genetics (the operon prediction trick)
  • Explain and implement methods for suffix trees, suffix arrays, and the Burrows-Wheeler transformation
  • Explain de novo sequence pattern screening with EM algorithm and entropy models.
  • Explain and implement basic methods for supervised and unsupervised data mining, as well as their application to biomedical OMICS data sets

Topics Covered

The following main topics are contained in the course:

  • Central dogma of molecular genetics, epigenetics, and bacterial and phage genetics
  • Design of online databases for molecular biology content (ontologies, and example databases: NCBI, CoryneRegNet, ONDEX)
  • DNA and amino acid sequence pattern models (HMMS, scoring matrices, mixed models, efficient statistics with them on big data sets)
  • Specialities in bacterial genetics (sequence models and functional models for operons prediction)
  • De novo identification of transcription factor binding motifs (recursive expectation maximization, entropy-based models)
  • Analysis of next-generation DNA sequencing data sets (memory-aware short sequence read mapping data with Burrows Wheeler transformation and suffix arrays, bi-modal peak calling)
  • Visualization of biological networks (graph layouting: small but highly variable graphs vs. huge but rather static graphs)
  • Systems biology and statistics on networks (network enrichment with CUSP, jActiveModules and KeyPathwayMiner)
  • Basic supervised and unsupervised classification methods for OMICS data analysis

Requirements

During the course the students have to complete exercise sheets and participate on one large project at the end of the semester. The project will be evaluated with pass/fail and needs to be passed in order to be eligible for the oral exam at the end of the semester.

Evaluation

You can download the evaluation results without comments here and the according action plan here. Thank you to all students who have returned the evaluation form.

Lectures

# Date Content Slides Readings
1 Wed, 14.09.2016, 8-10 Introduction here
2 Thu, 15.09.2016, 2-4 Databases here
3 Wed, 21.09.2016, 10-12 Sequence Logos & Operon Prediction here
4 Wed, 28.09.2016, 10-12 Transcription Factor Binding Sites here
5 Wed, 05.10.2016, 10-12 De Novo Motif Discovery here
6 Tue, 11.10.2016, 08-10 ChIP Data Analysis here
7 Tue, 25.10.2016, 2-4 Network Enrichment here
8 Tue, 01.11.2016, 4-6 Clustering here
9 Tue, 08.11.2016, 4-6 Data Mining here
NEW Thu, 10.11.2016, 4-6 Excursion to the Hospital location
here
10 Tue, 15.11.2016 --
11 Tue, 22.11.2016, 4-6 --
11 Thu, 24.11.2016, 2-4 recap

Assignment

General Notes

Here, you find all necessary information for the mandatory assignment for the course. Please note, that passing this assignment is necessary in order to be eligible to take the oral exam. Grading will be pass/fail with internal censor.

There will be no extensions to the deadlines!

Deadline Intermediate Report: December 19.

Deadline Final Hand-In: January 9.

It is allowed and encouraged to work in teams of 5 students. Make sure, when submitting your reports and code, that all your team members' names are included.

Materials

Additional Links

Exercises

# TA Session Topic Hand-In Due Download
1 Thu, 22.09.2016 Databases Wed, 21.09.2016 here
2 Thu, 29.09.2016 Sequence Logos (corrected) Wed, 28.09.2016 here
3 Thu, 06.10.2016 Transcription Factors Wed, 05.10.2016 here
4 Thu, 13.10.2016 De Novo Motifs Wed, 12.10.2016 here
Upstream Sequences
5 Thu, 27.10.2016 ChIP Data Wed, 26.10.2016 here
Read Mappings
6 Thu, 03.11.2016 Network Enrichment Wed, 02.11.2016 here
Map of Quatar
Map of Zimbabwe
7 Thu, 15.11.2016 Clustering Wed, 09.11.2016 here
Datasets and Helpers
TransClust
8 Thu, 17.11.2016 Data Mining Wed, 16.11.2016 here
Datasets and Additional Information

Materials

All lecture slides are relevant for the exams.

TBA