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BMB209: Workshops in Applied Bioinformatics

Study Board of Science

Teaching language: English
EKA: N220007112, N220007102
Censorship: Second examiner: None
Grading: Pass/Fail
Offered in: Odense
Offered in: Autumn, Spring
Level: PhD

STADS ID (UVA): N220007101
ECTS value: 2.5

Date of Approval: 29-04-2019


Duration: 1 semester

Version: Approved - active

Comment

None

Entry requirements

Bachelor of Science  or alike.

Academic preconditions

Students taking the course are expected to:

  • Basic knowledge in statistics and data analysis
  • Understand the basic principles of molecular biology

Course introduction

Despite the large number of available modern software to process and simulate biological data (eg. more than 10,000 reported in bio.tools), lack of practice and experience limits actually used methods in computational biology to a much smaller selection of popular and easy-to-operate tools.  

This workshop series aims to improve familiarity with a selection of up-to-date and powerful computational methods by hands-on experience supervised by experts in the respective fields including omics data analysis, statistics, image analysis and simulation of biological systems.
The students will learn how to create and apply software workflows for the analysis of noisy data and gain knowledge to visually and conceptually communicate underlying complex biological processes.

The workshops aim to provide insights into modern bioinformatics to students and interested researchers at the Department of Biochemistry and Molecular Biology as well as other interested parties.

The taught material will not only improve awareness of unknown or novel software, algorithms and methods but also lower the often steep learning curves for actually applying the methods. 

In the workshops, renowned often international experts will furthermore promote and encourage best-practice in computational biology.

Expected learning outcome

The learning objective of the course is that the student demonstrates the ability to:

  • Independently reproduce given bioinformatics examples
  • Work with complex data 
  • Apply sophisticated software tools
  • Describe and distinguish between analytical methods in computational biology
  • Know how to objectively discuss applied data analysis methods presented e.g. in publications
  • Use online bioinformatics resources

Content

The following main topics are contained in the course:

  • Introduction into software resources in bioinformatics
  • Popular data analysis workflows in bioinformatics
  • Application of selected software tools
  • Presentation of current challenges in bioinformatics by invited experts

Literature

See Blackboard for syllabus lists and additional literature references.

Examination regulations

Prerequisites for participating in the exam a)

Timing

During the course

Tests

Attendance of workshops

EKA

N220007112

Censorship

Second examiner: None

Grading

Pass/Fail

Identification

Full name and SDU username

Language

Normally, the same as teaching language

Examination aids

To be announced during the course

ECTS value

0

Additional information

The prerequisite examination is a prerequisite for participation in exam element a)

Exam element a)

Timing

Autumn / Spring

Prerequisites

Type Prerequisite name Prerequisite course
Examination part Prerequisites for participating in the exam a) N220007101, BMB209: Workshops in Applied Bioinformatics

Tests

Individual report

EKA

N220007102

Censorship

Second examiner: None

Grading

Pass/Fail

Identification

Full name and SDU username

Language

Normally, the same as teaching language

Examination aids

To be announced during the course

ECTS value

2.5

Additional information

The examination form for re-examination may be different from the exam form at the regular exam.

Indicative number of lessons

14 - hours per semester

Teaching Method

The teaching method is based on three phase model.

Intro phase: 8 hours

Skills training phase: 6 hours, hereof:

  •  Tutorials: 6 hours

Educational activities

In the individual report, the student reproduces one of the given bioinformatics workflows. Details on the individual assignment will be discussed during the workshops. The report should consist of at least 5 pages with a maximum of 10 pages excluding references. It should contain the following sections: a) Introduction and description of assignment; b) Overview of the student's procedure to solve the task; and c) evaluation of results and conclusion.

Teacher responsible

Name E-mail Department
Veit Schwämmle veits@bmb.sdu.dk Institut for Biokemi og Molekylær Biologi

Timetable

34
Monday
19-08-2019
Tuesday
20-08-2019
Wednesday
21-08-2019
Thursday
22-08-2019
Friday
23-08-2019
08 - 09
09 - 10
10 - 11
11 - 12
12 - 13
13 - 14
14 - 15
15 - 16
Show full time table

Administrative Unit

Biokemi og Molekylær Biologi

Team at Registration & Legality

NAT

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