Study programme 2020-2021Français
Algorithms and Bioinformatics
Programme component of Master's in Mathematics à la Faculty of Science

Students are asked to consult the ECTS course descriptions for each learning activity (AA) to know what special Covid-19 assessment methods are possibly planned for the end of Q3

CodeTypeHead of UE Department’s
contact details
Teacher(s)
US-M1-SCMATH-012-MOptional UEDELGRANGE OlivierS829 - Informatique théorique
  • DELGRANGE Olivier

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français150300066.001st term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
S-INFO-022Algorithms and Bioinformatics1503000Q1100.00%
Programme component

Objectives of Programme's Learning Outcomes

  • Have integrated and elaborate mathematical knowledge.
    • Mobilise the Bachelor's course in mathematics to address complex issues and have profound mathematical expertise to complement the knowledge developed in the Bachelor's course.
  • Carry out major projects.
    • Independently carry out a major project related to mathematics or mathematical applications. This entails taking into account the complexity of the project, its objectives and the resources available to carry it out.
    • Give constructive criticism on the quality and progress of a project.
    • Work in teams and, in particular, communicate effectively and with respect for others.
    • Present the objectives and results of a project orally and in writing.
  • Apply innovative methods to solve an unprecedented problem in mathematics or within its applications.
    • Appropriately make use of computer tools, as required by developing a small programme.

Learning Outcomes of UE

At the end of the instruction, the students will be able to explain the development needs of algorithms and data structures in the context of voluminous data such as genetic sequences. Students will be able to explain the classical algorithms for bioinformatics and string-matching. They will be able to implement algorithms for efficient manipulation of DNA sequences.

Content of UE

Algorithms, complexity of algorithms, strings, string-matching, sequence alignment; suffix tree; DNA sequencing and fragment assembly

Prior Experience

algorithmic, complexity of algorithms, programming in an imperative or object language

Type of Assessment for UE in Q1

  • Oral examination
  • Practical test

Q1 UE Assessment Comments

Oral examination on the theoretical course (50%) and presentation of group project developed for the practical part (50%)

Formula for the SCORE (/20) : Oral examination on the theoretical part, the score is NT (/20.) Presentation and written report on the (enhanced) project developed by group for the practical part, the score is NP (/20) If NT> = 8/20 and NP> = 8/20, then SCORE = (NP + NT) / 2
Otherwise SCORE = min (NP, NT)

Type of Assessment for UE in Q3

  • Oral examination
  • Practical Test

Q3 UE Assessment Comments

Oral examination on the theoretical course (50%) and presentation of group project developed for the practical part (50%)

Formula for the SCORE (/20) : Oral examination on the theoretical part, the score is NT (/20.) Presentation and written report on the (enhanced) project developed by group for the practical part, the score is NP (/20) If NT> = 8/20 and NP> = 8/20, then SCORE = (NP + NT) / 2
Otherwise SCORE = min (NP, NT)

Type of Resit Assessment for UE in Q1 (BAB1)

  • N/A

Q1 UE Resit Assessment Comments (BAB1)

Not applicable

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
S-INFO-022
  • Cours magistraux
  • Conférences
  • Préparations, travaux, recherches d'information

Mode of delivery

AAMode of delivery
S-INFO-022
  • Face to face

Required Reading

AA
S-INFO-022

Required Learning Resources/Tools

AARequired Learning Resources/Tools
S-INFO-022Not applicable

Recommended Reading

AA
S-INFO-022

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
S-INFO-022Not applicable

Other Recommended Reading

AAOther Recommended Reading
S-INFO-022- Introduction to Computational Molecular Biology
  J. Setubal, J. Meidanis
  PWS Publishing Company, 1997
- Algorithmic Aspects of Bioinformatics
  HJ Böckenhauer - D. Bongartz
  Springer, 2007

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
S-INFO-022Authorized
(*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term
Date de génération : 09/07/2021
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Tél: +32 (0)65 373111
Courriel: info.mons@umons.ac.be