Syllabus for Informatics Toolbox for Systematics

Systematikens verktygslåda - informatik

Syllabus

  • 5 credits
  • Course code: 1BG395
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Biology A1F, Applied Biotechnology A1F
  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2012-03-08
  • Established by: The Faculty Board of Science and Technology
  • Applies from: week 27, 2012
  • Entry requirements: 150 credits including (1) 60 credits in biology and 30 credits in chemistry or 30 credits in earth science, or (2) 90 credits in biology, in both cases including Fundamental and Molecular Systematics, 10 credits, or Evolutionary Patterns, 15 credits.
  • Responsible department: Biology Education Centre

Learning outcomes

The course intends to give the student a set tool (in the form of Perl, MySQL and R) to handle, store, structure, analyse and visualise data in a molecular-systematic project. After completing the course, the student should be able to


  • choose and apply existing applications in Perl, MySQL and R

  • design simple databases in MySQL

  • write new or modify existing scripts (in Perl, SQL and R) to solve simple problems

  • outline solutions to information flow based on Perl, R and SQL for a systematic research project

Content

The course presents and applies the most popular open environments in bioinformatics to design practical solutions to concrete problems within the systematics.
- Automation of bioinformatic data management; application of bioinformatics, from process to algorithm, to solve problems through programming
- Biological databases with MySQL; common database types, design of relational databases, configuration of MySQL server, data management with SQL
- Automation with Perl; basic syntax and logic, references, subroutines and modules, regular expressions, file management, Perl DBI
- Numerical data analysis with R; data structures, import of data, visualisation, programs in R, multivariate data analysis (clustering, PCA, classification) in R, program package in R, interface with MySQL
- Programming for the web; Apache web server, HTML and XHTML, CGI with Perl, CSS, Ecmascript, visualisation with Perl, CGI and R

Instruction

The teaching is given in the form of e-teaching

Assessment

Parts of the course: Theory 2 HE credits, Practice 3 HE credits
The theory part is examined by a computer-based test

Reading list

Reading list

Applies from: week 06, 2012

  • Bessant, Conrad; Oakley, Darren; Shadforth, Ian Building bioinformatics solutions : with Perl, R, and SQL

    Second edition.: Oxford, United Kingdom: Oxford University Press, 2014

    Find in the library