BIOI4440 Biological Data Analysis with R 5 ECTS

General description

The purpose of this course to teach the R statistical environment to be applied in biological data analysis. Since R is the most popular data analysis programming language used in high-throughput setting, this course, together with its sequel: BIOI4450 High Throughput Data Analysis, offers students a competitive skill-set not only in bioinformaticxs, but also in general molecular biology field.

Learning outcomes

After this course, students will be able to use R for analyzing diverse data types from very different biological experiments. Lectures will introduce the theoretical aspects of the introduced methodologies, and after that, students will have opportunity to explore the practical ways of performing the analyses by obligatory homework exercises.

Contents

1. Introduction to R statistical environment
2. Practicing R programming
3. Simple sequence analysis
4. Annotating gene groups
5. Measuring protein abundance with ELISA
6. Proteomics: mass spectometry
7. Inferring regulatory and other networks from gene expression data
8. Analysis of biological networks

Teaching methods

Lectures. Independent work by following the provided instructions. Work and learning must be documented by Moodle postings. Home assignments: weekly programming tasks and weekly submissions about lecture material.

Teaching language

English

Modes of study

Option 1
Available for:
  • Degree Programme Students
  • Other Students
  • Doctoral Students
  • Exchange Students
Exercise(s)
  • In English
Written exam
  • In English

Home assignments, classroom and independent coding practices, exam

Evaluation

Numeric 0-5.

Recommended year of study

1. year spring

Study materials

Lecture notes and other material provided by the teacher.
Book: Ortutay and Ortutay: Molecular Data Analysis Using R. John Wiley & Sons, Inc. 2016.

Belongs to following study modules

Department of Future Technologies
Department of Biochemistry
Department of Biochemistry
Department of Future Technologies
2016–2017
Teaching
Archived Teaching Schedule. Please refer to current Teaching Shedule.
Department of Future Technologies
DP in Computer Science
DP in Computer Science
DP Bachelor of Science in Techn.(Communication St)
DP in Information and Communication Technology
MDP in Digital Health and Life Sciences (Tech.)
Finnish Study Modules