Course contents *

No information inserted

Intended learning outcomes *

This is an introductory course in bioinformatics and biostatistics. After passing the course, the student should:

• know the theory behind fundamental bioinformatics analysis methods.
• be familiar with widely used bioinformatics databases.
• know basic concepts of probability and statistics.
• be able to describe statistical methods and probability distributions relevant for molecular biology data.
• know the applications and limitations of different bioinformatics and statistical methods.
• be able to perform and interpret bioinformatics and statistical analyses with real molecular biology data.

Course Disposition

The course consists of lectures and computer-based laboratory exercises.

Specific prerequisites *

Admission requirements for programme students at KTH:
At least 150 credits from grades 1, 2 and 3 of which at least 100 credits from years 1 and 2, and bachelor's work must be completed.  The 150 credits should include a minimum of 20 credits within the fields of Mathematics, Numerical Analysis and Computer Sciences, 5 of these must be within the fields of Numerical Analysis and Computer Sciences, 20 credits of Chemistry, possibly including courses in Chemical Measuring Techniques and 20 credits of Biotechnology or Molecular Biology.

Admission requirements for independent students:
A total of 20 university credits (hp) in Biotechnology or Molecular Biology. 20 credits of Chemistry, possibly including courses in Chemical Measuring Techniques and 20 credits within the fields of Mathematics, Numerical Analysis and Computer Sciences, 5 of these must be within the fields of Numerical Analysis and Computer Sciences, Documented proficiency in English corresponding to English B.

Recommended prerequisites

The following courses, or equivalent, are recommended: SF1644 Calculus in one Variable, BB1010 Introduction to Biotechnology. Computer acquaintance equivalent to DN1212 Numerical Methods and Basic programming.

Equipment

No information inserted

Literature

Zvelebil and Baum, Understanding Bioinformatics (2007), Garland Science

Biostatistics: The Bare Essentials. G. R. Norman and D. L. Streiner. (B.C. Decker, 3rd edition)

Listan kan komma att ändras. Ändringar kommer att annonseras på kursens hemsida senast fyra veckor före kursstart.

Grading scale *

A, B, C, D, E, FX, F

Examination *

• LAB1 - Laboratory Work, 2.0 credits, Grading scale: P, F
• TEN1 - Written Examination, 5.0 credits, Grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Other requirements for final grade *

TEN1 – Written examination, 5.0 credits, grade scale: A, B, C, D, E, FX, F

LAB1 – Laboratory work, 2.0 credits, grade scale: P, F

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

Olof Emanuelsson

Course web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Offered by

CBH/Gene Technology

Main field of study *

Biotechnology

Education cycle *

Second cycle

Add-on studies

No information inserted

Ethical approach *

• All members of a group are responsible for the group's work.
• In any assessment, every student shall honestly disclose any help received and sources used.
• In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Supplementary information

Överlappar med BB2441

The course will not be given from Fall 2017

Students are required to sign up at least two weeks in advance for examination.

The course is given provided at least seven students are admitted.