| Language of instruction : English |
| | | Exam contract: not possible |
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Sequentiality
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No sequentiality
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There is no data for this choice.
Change the language, year or choose another item in the dropdown list if it is available.
| Degree programme | | Study hours | Credits | P2 SBU | P2 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | 1st year Master Bioinformatics - distance learning | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical |  |
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| | | Learning outcomes |
- EC
| The student is capable of acquiring new knowledge. | - EC
| The student knows the international nature of the field of statistical science and data science. |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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The student has basic knowledge of molecular biology.
The student has basic knowledge of statistical inference (probability distributions. estimation methods, statistical hypothesis testing).
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The course introduces the basic concepts and methods of (statistical) bioinformatics related to: genomics; proteomics; sequence alignment; microarrays; mass spectrometry; next generation sequencing; microbiome analysis.
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Period 2 Credits 4,00
| Evaluation method | |
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| Written exam | 100 % |
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| Multiple-choice questions | ✔ |
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| Off campus online evaluation/exam | ✔ |
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| For the full evaluation/exam | ✔ |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Recommended course material |
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Lecture notes, copies of papers/book chapters relevant for the lectures' topics. |
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| 1st year Master Biostatistics - distance learning | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| 1st year Master Data Science - distance learning | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| 1st year Master Quantitative Epidemiology - distance learning | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
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| | | Learning outcomes |
- EC
| The student is capable of acquiring new knowledge. | - EC
| The student knows the international nature of the field of statistical science and data science. |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
The student has basic knowledge of molecular biology.
The student has basic knowledge of statistical inference (probability distributions. estimation methods, statistical hypothesis testing).
|
|
|
|
The course introduces the basic concepts and methods of (statistical) bioinformatics related to: genomics; proteomics; sequence alignment; microarrays; mass spectrometry; next generation sequencing; microbiome analysis.
|
|
|
Period 2 Credits 4,00
| Evaluation method | |
|
| Written exam | 100 % |
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|
| Multiple-choice questions | ✔ |
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|
|
|
|
| Off campus online evaluation/exam | ✔ |
|
| For the full evaluation/exam | ✔ |
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|
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Recommended course material |
| |
Lecture notes, copies of papers/book chapters relevant for the lectures' topics. |
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1 Education, Examination and Legal Position Regulations art.12.2, section 2. |
| 2 Education, Examination and Legal Position Regulations art.16.9, section 2. |
3 Education, Examination and Legal Position Regulations art.15.1, section 3.
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| Legend |
| SBU : course load | SP : ECTS | N : Dutch | E : English |
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