LEARNING OUTCOMES
The course provides you with basic understanding of high-throughput data and computational methods that are commonly used for analysing the data in biological and biomedical problems. After the course you have skills to apply various computational methods in real biological problems and study the field further.
Credits: 5
Schedule: 25.10.2022 - 12.12.2022
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Harri Lähdesmäki
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
The course introduces computational and statistical methods for analyzing modern high-throughput biological data and their use in systems biology. The course covers microarray, high-throughput sequencing (HTS), single-cell and mass-spectrometry technologies and computational methods for HTS data alignment, genotyping, gene expression analysis, chromatin immunoprecipitation sequencing, epigenetics and proteomics. Relevant high-throughput measurement technologies are reviewed during the course.
Assessment Methods and Criteria
valid for whole curriculum period:
Examination and exercise work.
Workload
valid for whole curriculum period:
24 + 12 (4 + 2)
DETAILS
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language : English
Teaching Period : 2022-2023 Autumn II
2023-2024 Autumn IIEnrollment :
Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.