Degree | Type | Year |
---|---|---|
2503740 Computational Mathematics and Data Analytics | OT | 4 |
You can view this information at the end of this document.
Basic knowledge of the English language is required as part of the teaching material is in that language. Recommended to have taken the Bioinformatics course.
PART 1. Big Data in Drug Discovery
PART 2. Big Data in Omics Analysis
*Unless the requirements enforced by the health authorities demand a prioritization or reduction of these contents.
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Practical sessions | 21 | 0.84 | |
Presentation of Research Project | 3 | 0.12 | |
Theory classes | 21 | 0.84 | |
Type: Supervised | |||
Tutoring | 10 | 0.4 | |
Type: Autonomous | |||
Preparation of Research Project | 20 | 0.8 | |
Study | 70 | 2.8 |
The course is organized in sessions of 3 hours. Each session consists of a theoretical part (theory classroom) that will introduce the new concepts followed by a practical part (computer room) where the students will work on the implementation of concepts explained in the theoretical part. In each session the teacher will indicate the students some tasks to do autonomously, such as reading articles or sending reports. The material used by the teachers will be available on the Virtual Campus of the course.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Presentation Research Project | 20 | 0.5 | 0.02 | CM34, CM35, KM29, KM30, KM31, SM36, SM37, SM38 |
Presentation of practicum reports | 40 | 0.5 | 0.02 | CM34, CM35, KM29, KM30, KM31, SM36, SM37, SM38 |
Theoretical-practical exams | 40 | 4 | 0.16 | CM34, CM35, KM29, KM30, KM31, SM36, SM37, SM38 |
PART 1. Big Data in Drug Design (50%):
- practical exercises (30%)
- bioinformatics oral presentation of a project (20%)
BLOCK 2. Big Data in Data Analysis (50%):
- practical exercises (30%)
- theoretical-practical test (20%)
The minimum global qualification required to pass the subject will be 5 points. The minimum mark of each of the evaluated activities must be equal to or greater than 4 points. Students who have any of the parts suspended will be able to do the recovery exam where they can be re-examined from the suspended part.
R: https://www.r-project.org/
Rstudio: https://www.rstudio.com/
Name | Group | Language | Semester | Turn |
---|---|---|---|---|
(PLAB) Practical laboratories | 1 | Catalan | first semester | afternoon |
(TE) Theory | 1 | Catalan | first semester | afternoon |