Study programme 2017-2018Français
Biological Data Processing
Programme component of Master's Degree in Biochemistry and Molecular and Cell Biology Research Focus à la Faculty of Science
CodeTypeHead of UE Department’s
contact details
Teacher(s)
US-M2-BBMCFA-037-MOptional UEGROSJEAN PhilippeS807 - Ecologie numérique des milieux aquatiques
  • GROSJEAN Philippe

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français1010000221st term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
S-BIOG-077Biological Data Processing1010000Q1100.00%
Programme component

Objectives of Programme's Learning Outcomes

  • In the field of biological sciences and particularly in the field of the biochemistry, molecular and cell biology, possess highly specialised and integrated knowledge and a wide range of skills adding to those covered in the Bachelor's programme in biological sciences.
  • Develop and integrate a high degree of autonomy.
    • Pursue further training and develop new skills independently.
  • In the field of biological sciences and particularly in the field of the biochemistry, molecular and cell biology, possess highly specialised and integrated knowledge and a wide range of skills adding to those covered in the Bachelor's programme in biological sciences.
  • Develop and integrate a high degree of autonomy.
    • Pursue further training and develop new skills independently.

Learning Outcomes of UE

To specialize students in biology in the manipulation of biological data through their initiation to various complementary concepts to biostatistics. This course supplements biostatistical concepts taught until now with various more advanced topics that are not normally seen in these courses: problem of floating-point calculation precision, best coding of data in relation with the current problem, how to realize reproducible analyses, reproducible pseudo-random generators, pre-sorting of the data with SQL commands. This course is partly modular in function of specific needs of students.

Content of UE

Data management; databases; SQL queries; S language (software R); floating-point calculation; pseudo-random numbers generation; reproducible analysis; unit tests; data formats; optimization of calculation speed; optimization of RAM used; vectorized algorithms.

Prior Experience

Advanced biostatistics.

Type of Assessment for UE in Q1

  • Oral examination

Q1 UE Assessment Comments

Evaluation according to questions and answers durting an oral examination.

Type of Assessment for UE in Q3

  • Oral examination

Q3 UE Assessment Comments

Evaluation according to questions and answers durting an oral examination.

Type of Resit Assessment for UE in Q1 (BAB1)

  • Oral examination

Q1 UE Resit Assessment Comments (BAB1)

Evaluation according to questions and answers durting an oral examination.

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
S-BIOG-077
  • Cours magistraux
  • Conférences
  • Ateliers et projets encadrés au sein de l'établissement
  • Préparations, travaux, recherches d'information

Mode of delivery

AAMode of delivery
S-BIOG-077
  • Face to face

Required Reading

AA
S-BIOG-077

Required Learning Resources/Tools

AARequired Learning Resources/Tools
S-BIOG-077Not applicable

Recommended Reading

AA
S-BIOG-077

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
S-BIOG-077Chambers, J.M., 2008. Software for data analysis. Programming with R. Springer, New York, 498pp.

Other Recommended Reading

AAOther Recommended Reading
S-BIOG-077Chambers, J.M., 1998. Programming with data. A guide to the S language. Springer, New York, 469pp.Fortner, B., 1995. The data handbook. A guide to understanding the organization and visualization of technical data. Springer, New York, 350pp.Venables, W.N. & B.D. Ripley, 2000. Programming with R. Springer, New York, 264pp.Venables, W.N. & B.D. Ripley, 2000. Modern applied statistics with S-PLUS (3rd ed.). Springer, New York, 501pp.

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
S-BIOG-077Authorized
(*) 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 : 11/01/2018
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Tél: +32 (0)65 373111
Courriel: info.mons@umons.ac.be