Graduate School of health and Medical Sciences

Bioinformatics for Microbiology
Provider: Faculty of Health and Medical Sciences

Activity no.: 3122-17-00-01	There are no available seats
	Enrollment deadline: 11/10/2017

Date and time	06.11.2017, at: 08:30 - 17.11.2017, at: 17:00
Regular seats	13
Course fee	11,880.00 kr.
Lecturers	Henrik Christensen
ECTS credits	8.50

Contact person	Henrik Christensen E-mail address: hech@sund.ku.dk

Enrolment Handling/Course Organiser	PhD administration E-mail address: phdkursus@sund.ku.dk

Aim and content This course is free of charge for PhD students at Danish universities (except Copenhagen Business School). Special rules apply for research year students enrolled at Faculty of Health and Medical Sciences at UCPH. All other participants must pay the course fee. Anyone can apply for the course, but if you are not a PhD student, you will be placed on the waiting list for the course until enrollment deadline. After the deadline of enrollment, available seats will be allocated to students on the waiting list. Learning objectives A student who has met the objectives of the course will be able to: 1. Understand and discuss the advantages and disadvantages of the methods, analyze data in a bioinformatics context using the procedures described below and draw valid conclusions based on the results obtained. 2. Assemble Illumina reads, do simple prediction of open reading frames from DNA sequences and to deposit own sequences with NCBI. 3. Download DNA sequences from databases, understand the detailed information of proteins in Uniprot, view 3D structures, predict the function of unknown proteins by dataset comparison. 4. Know differences between local compared to global alignments, perform more complicated alignment of proteins, to perform BLAST searches and to obtain precise data of similarity and identity. 5. Construct multiple alignments, trim multiple alignments, identify errors with multiple alignments and use a reference sequence. 6. Construct a phylogenetic tree by neighbour joining including the bootstrap as well as to use maximum likelihood and Baysian inference and to select the most appropriate phylogenetic method for the situation. 7. Design PCR primers to target a single DNA sequence and design PCR primers to separate a target group of sequences from a non-target. 8. Gain access to prokaryotic genomes and compare organization of prokaryotic genomes and perform SNP analysis. Perform in silico subtractions of proteins in one genome from another, to construct simple phylogenetic trees based on whole genomic sequences as units and to classify prokaryotes online based on high throughput 16S rRNA reads (metagenomics). 9. Perform sequence based identification of prokaryotes based on 16S rRNA sequences and use computer programs to infer population structures (MLST) and estimate related parameters. Perform simple sequence based identification of virus, fungi and parasites. 10. Use the tools introduced for independent work on their own project related to their Ph.D. study. Content Week 1: Theory will be introduced by lectures in 35 % of the course time. The participants will contribute to the theoretical presentations. Practical computer exercises will cover another 50 % of the course and 15 % of course time will be used to discuss outcomes of exercises. The exercises allow training in relation to the theory introduced and will be solved in groups of 1-3 persons with extensive help from teacher. Day 1: DNA sequencing, databases, search functions and sequence exchange. Day 2: Pairwise -, multiple alignment. Day 3: Primer-design and phylogeny. Day 4: Genomics including metagenomics. Day 5: Sequence based typing and identification of microorganisms. Week 2: Projects are defined which allow students to work with subjects relevant their own projects related to their Ph.D. study in more detail. The project work will involve groups of 1-3 students and be related to cases with microorganisms of environmental, food, veterinary and human health importance. The week can be used directly to produce material for a scientific paper in relation to investigations in progress or the participant can do pilot investigations relevant to coming activities. The project will be extensively supervised and will aim at writing up a project report. The outline of the report should be like a short scientific paper (Introduction, Material & methods, Results, Discussion, References). For students without a project it will be possible to select from predefined projects. Day 1: Identification of project. Example of PhD project with microbiome analysis. Day 2: Project work. Day 3: Project work. Day 4: Presentation of projects. Day 5: Presentation of projects. Describe the course curriculum in terms of scientific topics covered. Participants The course is relevant to Ph. D. students with a very limited background in bioinformatics as well as participants who received some training in bioinformatics during their candidate study. The course is mainly relevant for participants that work with bacteria, although topics in relation to virus, fungi and parasites are covered as well. The participants need to have basic knowledge about biochemistry and genetics at BSc level. The participants need to bring at least one updated labtop computer with one of the major operating systems (Windows, Apple, Linux) which can access wireless networks. To coordinate teaching in relation to participants backgrounds, applications including CV with full contact address including Email address and a 1/2-1 page justification of educational qualifications should be submitted to Email: hech@sund.ku.dk not later than 11 October 2017. Relevance to graduate programmes The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH: Molecular Bacteriology and Infection Veterinary and Animal Sciences Biostatistics and Bioinformatics Language English Form Theoretical and practical course. During the first week, theory will be introduced by lectures where the participants will contribute to some of the theoretical presentations. Practical computer exercises will have the main focus and the outcome of the exercises will be discussed between teacher and participants. The exercises allow training in relation to the theory introduced and will be solved in groups of 1-3 persons per computer with help from the teachers. The second week will be devoted to project work that will involve groups of 1-3 students and be related to cases with microorganisms of environmental, food, veterinary and human health importance. The participants will give a presentation of their project work as well as deliver a short report after the course. The outline of the report will have to be like a short scientific paper. Course director Henrik Christensen, associate professor, Department of Veterinary Animal Sciences, University of Copenhagen, hech@sund.ku.dk Teachers Henrik Christensen, associate professor, Department of Veterinary and Animal Sciences, University of Copenhagen, Egle Kudirkiene, Post. doc., Department of Veterinary and Animal Sciences, University of Copenhagen, Camilla V. Lauritsen, research assistant, Department of Veterinary and Animal Sciences, University of Copenhagen. Steffen L. Jørgensen, PhD student, Department of Veterinary and Animal Sciences, University of Copenhagen. Dates 6 – 10, 13 – 17 November 2017 (8.30-12.00 + 13-17.00) Course location KU-SUND at Frederiksberg Campus Registration Please register before 11 October 2017 Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrolment. Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

Click the search button to search Courses.

See which courses you can attend and when

Jan	Feb	Mar	Apr
May	Jun	Jul	Aug
Sep	Oct	Nov	Dec

New courses
Courses are published regularly. High demand courses are announced in spring and autumn.

Learn which courses are announced on fixed dates