DM840: Algorithms in Cheminformatics

The Study Board for Science

Teaching language: Danish or English depending on the teacher, but English if international students are enrolled
EKA: N340003102
Assessment: Second examiner: External
Grading: 7-point grading scale
Offered in: Odense
Offered in: Autumn, Spring
Level: Master's level course approved as PhD course

STADS ID (UVA): N340003101
ECTS value: 10

Date of Approval: 12-03-2025


Duration: 1 semester

Version: Approved - active

Entry requirements

None

Academic preconditions

Students taking the course are expected to:

  • be able to design and implement programs, using standard algorithmic approaches and data structures.
  • be able to judge the complexity of algorithms, with regard to runtime as well as with regard to space usage.

Course introduction

The purpose of the course is to enable the student to solve a wide range of non-trivial discrete computational problems within computer science that are motivated from or arise in chemistry, by applying advanced algorithmic ideas, graph theoretical approaches, knowledge from related fields of discrete mathematics, and complexity theory. The course gives an academic basis for writing a Master's thesis, that aims to apply core computer science approaches to relevant questions in chemistry, biology, physics, or mathematics.

Expected learning outcome

After the course the student is expected to have the following.

Knowledge of

  • different levels of representation of molecular structures.
  • methods for analysing the structure of molecules.
  • rule-based modelling of chemical systems.
  • graph algorithms related to graph transformation.
  • different representations of chemical systems.
  • methods for analysis of chemical systems.

Skills in

  • implementing algorithms and data structures from the course.

Competences in

  • explaining and applying methods, models, and algorithmic ideas from the course.
  • formulating methods, models, and algorithms from the course in precise language.
  • describing implementations of algorithms, data structures, and experimental work carried out, in a structured fashion, in a clear and precise language.

Content

The following broad topics are contained in the course:

  • representation of molecular structures
  • graph transformation and artificial chemistries
  • subgraph isomorphism, graph isomorphism, and graph canonicalization
  • combinatorial structures
  • metabolic networks and pathways analysis
  • concurrency theory
  • stochastic processes

Literature

See itslearning for syllabus lists and additional literature references.

Examination regulations

Exam element a)

Timing

January and June

Tests

Portfolio exam

EKA

N340003102

Assessment

Second examiner: External

Grading

7-point grading scale

Identification

Student Identification Card - Name

Language

Normally, the same as teaching language

Duration

Oral exam, 30 minutes, no preparation

Examination aids

To be announced during the course

ECTS value

10

Additional information

The portfolio consists of the following elements:
1) a number of assignements handed in during the course
2) An oral exam suring the exam period

To achieve a passing grade overall, both element 1 and element 2 must independently meet the objectives. The assessment of element 1 will take place in conjunction with the completion of element 2.

Element 1 counts for 20% and element 2 counts for 80%, in which a overall evaluation is applied.

Indicative number of lessons

60 hours per semester

Teaching Method

Planned lessons: 


Total number of planned lessons: 60

Hereof: 

Common lessons in classroom/auditorium: 60

The common lessons will be a mix of classical lectures, discussions, and solving exercises.

Other planned teaching activities:

Studying material for the lectures, solving exercises, and application of the acquired knowledge and skills in projects.

Teacher responsible

Name E-mail Department
Jakob Lykke Andersen jlandersen@imada.sdu.dk Institut for Matematik og Datalogi

Timetable

Odense
Show full time table (start E24)
Show full time table (start F25)

Administrative Unit

Institut for Matematik og Datalogi (datalogi)

Team at Registration

NAT

Offered in

Odense

Recommended course of study

Profile Education Semester Offer period

Transition rules

Transitional arrangements describe how a course replaces another course when changes are made to the course of study. 
If a transitional arrangement has been made for a course, it will be stated in the list. 
See transitional arrangements for all courses at the Faculty of Science.