Inhalt

[ 665MBBTGEDU16 ] VU Genomic Data Analysis

Versionsauswahl
Es ist eine neuere Version 2020W dieser LV im Curriculum Master's programme Biophysics 2023W vorhanden.
(*) Unfortunately this information is not available in english.
Workload Education level Study areas Responsible person Hours per week Coordinating university
6 ECTS B2 - Bachelor's programme 2. year Physics Irene Tiemann-Boege 4 hpw Johannes Kepler University Linz
Detailed information
Original study plan Bachelor's programme Molecular Biosciences 2016W
Objectives With the advent of the human genome project, new tools and resources have become available that deeply impact the field of biology. The aim of this curse is to introduce students to the different tools and databases necessary for the analysis of genomic information that are key for any research project in biology. Additionally, the course offers a laboratory module that will guide students through the different steps for accessing biological databases and their use. Goals 1. To provide an introduction to genomic databases with a focus on the National Center for Biotechnology Information (NCBI), UCSC, and EBI 2. To focus on the analysis of proteins and DNA 3. To introduce the student to the analysis of genomes 4. To combine theory and practice to help you solve research problems in biology
Subject Part 1 -- Introduction to genomics

1. Introduction to genomics-3 case studies

  • Definition of bioinformatics/genomics
  • 3 study cases—why is genomics important?

- Finding a disease gene—Progeria story
- Synthetic biology—artificial genomes
- Evolutionary biology—What makes us human?

2. Genome projects / Comparative genomics

  • Sequencing Projects
  • Sequenced genomes
  • Understanding a genome sequence
  • Finding genes
  • Structural features

3. Genomic variation

  • Genomic variation
  • From SNPs to copy number variants and their evolution
  • HapMap project
  • Genotyping
  • Ethical issues
  • Human disease

4. The Human Genome Project

  • The Human Genome Project
  • Strategy of the human genome
  • Assembly
  • Main conclusions of the human genome project
  • Sequencing individual genomes

5. Emerging sequencing technologies

  • New sequencing technologies
  • Principles of new technologies
  • Commercial platforms
  • Sequencing RNA—replacement of expression arrays

Part 2 -- Introduction to databases (lab based)

1. Accessing information about DNA and proteins

* Genome browsers

  • Overview of the NCBI website
  • Accessing information: accession numbers and RefSeq
  • Entrez Gene (and UniGene, HomoloGene)
  • Protein Databases: UniProt, ExPASy
  • Three genome browsers: NCBI, UCSC, Ensembl
  • Access to biomedical literature

2. Sequence alignments

  • Pairwise sequence alignment
  • Definitions: homologs, paralogs, orthologs
  • Perform pairwise alignments (NCBI BLAST)
  • Assigning scores to aligned amino acids: Dayhoff’s PAM matrices
  • Alignment algorithms: Needleman-Wunsch, Smith-Waterman

3. How to use BLAST

  • BLAST-Basic local alignment search tool
  • How to use BLAST
  • How to interpret BLAST results
  • BLAST-like tools for genomic DNA

4. Advanced sequence search

  • PSI-BLAST
  • Multiple sequence alignment
  • Multiple ale alignment of genomic sequences

5. Finding a novel gene

  • Strategy to find a novel gene in the databases
Criteria for evaluation
  • Lecture: based on a series of quizzes, no computer, short answer / multiple choice.

Offered as a final exam or offered as small quizzes at the beginning of each

  • Laboratory: Results from computer lab—Report after each day
Methods The course will be taught in two parts. The first part will focus on the theoretical background of genomics including topics in genetics, molecular biology, and biochemistry. The second part will provide an introduction to the databases with step to step examples of how to retrieve different information. During the laboratory module students will work in groups to solve a series of problems based on the taught material.
Language English
Study material
  1. Bioinformatics and Functional Genomics by Jonathan Pevsner (Wiley-Blackwell, 2nd edition 2009).
  2. A Primer of Genome Science by Greg Gibson (Spencer V. Muse Publisher: Sinauer Associates, 3rd Edition 2008)
Changing subject? No
Corresponding lecture (*)665GEDAGEDU11: VU Genomische Datenanalyse (6 ECTS)
Earlier variants They also cover the requirements of the curriculum (from - to)
665GEDAGEDU11: VU Genomic Data Analysis (2011W-2016S)
On-site course
Maximum number of participants 25
Assignment procedure Assignment according to priority