Practical Bioinformatics for Biologists
Aim of the course
At the end of the course, the student is able to:
1. Understand and describe the origin(s) and properties of “big data”, in particular those coming from the ‘Omics technologies’, evaluate the challenges they are posing in modern biology applications, and basic principles and applications of bioinformatics.
2. Master a Linux/Unix environment: navigate and use the file system, including understanding directory structure/permissions, and creating/editing/removing files. Work on remote computers and High Performance Computing (HPC) cluster. Install and run several types of software in this environment.
3. Handle, manage, explore, and extract information from big and complex data files (e.g. personal and public databases) using basic functionality and options of building block data analysis tools included in Unix-like operating systems.
4. Design and implement custom tools using scripting programming languages (e.g., Shell, R and/or Python) to explore, analyse, and visualize data.
5. Design and implement analytic pipeline consisting of combining, automatizing, and wrapping tasks/analyses using general command-line tools to address specific problems.
6. Integrate personal data or data from public databases into a concrete case study example and design (a) workflow(s) to address a given biological research question, choose the most appropriate method for its implementation, and reflect on the biological implications of results.
Contents & Structure
Practical Bioinformatics for Biologists (PBfB) introduces students to use general computational tools to work more effectively on a daily basis. It pulls together a broad range of free powerful, and flexible tools that are applicable to geneticists, molecular biologists, ecologists, oceanographers, physiologists, and anyone interested or in need of bioinformatics in their research. It features practical use of bioinformatic techniques to solve real analysis problems.
PBfB will cover the “nuts and bolts” of datacentered computing tasks in a Unix/Linux environment. Basics of using such an environment, including installing and running software on remote machines will be introduced. Students will become familiar with command line tools to explore and analyze data, and explore the use of scripting languages such as Python and R to (a) write custom analysis tools as needed and (b) act as “glue” to make effective pipelines of other tools. Practical use of databases and how to retrieve data from remote public databases will be introduced. Various data visualization technics, including among other GIS tools, will be introduced using R statistical language.
Topics address in PBfB will use concrete example taken from various field, for example data from Next Generation Sequencing (NGS) technologies in genetics and molecular biology, as well as remote sensing and oceanographic data widely used in environmental ecological and evolutionary biology.
The course consists of short lectures featuring new concepts and examples interspersed with practical computer exercises and individual assignments. During the last week, students will prepare a project assignment in small groups featuring the use of the skills learned during the course and aiming at solving a concrete example. Students will present and explain their pipeline and results to the group in an oral presentation during the last days of the course.
|Required knowledge & preparation||This course does not require any a priori knowledge of bioinformatics, just elementary computer skills (i.e. locate files via command line etc.)
Open for all with Bachelor or Master in Biological Sciences.
Students belonging to the GELIFES MSc Biology: Marine Biology, Behavioural Neuroscience or Ecology and Evolution have first choice.
|Course material||Handout (web-based). Book: Practical computing for biologists. (1sted.), Haddock S.H.D. and Dunn C.W., ISBN: 978-0878933914, ca. € 60,00.|
|Course credits||5 ECTS|
|Location||Linneausborg, Nijenborgh 7, Groningen|
|Duration & date||8-1-2018 till 3-2-2018. Full time course|
|Costs||Participation fee is €275 for all participating GELIFES PhD students. PhD students from other institution may be welcome to participate if there is sufficient room in the course. The course fee for external participants is € 350. Potential travelling & housing costs are not included and are for the student.|
|Participants||Maximum number of students will be fixed to 25|
|Registration||Master students: please register through the Ocasys portal
PhD students: please register by filling out the registration form
|Laatst gewijzigd:||12 september 2017 15:46|