Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

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: 13.09.2021 - 28.10.2021

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Lu Cheng, Pekka Marttinen

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

Study Material
  • valid for whole curriculum period:

    Nello Cristianini and Matthew Hahn: Introduction to Computational Genomics: A Case Studies Approach. Cambridge University Press, 2007.

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information
  • valid for whole curriculum period:

    Teaching Period:

    2020-2021 Autumn I

    2021-2022 Autumn I

    Course Homepage: https://mycourses.aalto.fi/course/search.php?search=CS-E5865

    Registration for Courses: Kurssille ilmoittaudutaan WebOodissa. Katso ilmoittautumisaika WebOodista. Ilmoittautumiseen