LEARNING OUTCOMES
The course provides you with an introduction to computational methods used in sequence and genome analysis. After the course you can analyze and understand real-life genomic data sets encountered in computational and biomedical research groups and in industry. Specifically, you can align genome sequences, identify genes and conserved regions in the genomes, use hidden Markov models for segmentation of genomes, build phylogenetic trees to estimate evolutionary relationships, and recognize and explain the meaning of different kinds of variation observed in real-life genomic data sets.
Credits: 5
Schedule: 04.09.2023 - 19.10.2023
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Lu Cheng
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 comprises a brief introduction to genes, genomes, and related biological concepts, and covers basic algorithms and models to analyse biological sequences and genomic data sets, including techniques for gene finding, sequence alignment, permutation sampling, hidden Markov models, and the neighbor joining algorithm.
Assessment Methods and Criteria
valid for whole curriculum period:
Examination and exercises.
Workload
valid for whole curriculum period:
16 + 18 (4 + 2)
DETAILS
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
SDG: Sustainable Development Goals
3 Good Health and Well-being
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language : English
Teaching Period : 2022-2023 Autumn I
2023-2024 Autumn IEnrollment :
Sisu (sisu.aalto.fi).