| Language of instruction : English |
| Exam contract: not possible |
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Sequentiality
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Mandatory sequentiality bound on the level of programme components
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Following programme components must have been included in your study programme in a previous education period
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Medical and Molecular Biology (3564)
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6.0 stptn |
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| Degree programme | | Study hours | Credits | P1 SBU | P1 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | 2nd year Master Bioinformatics | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical |  |
| 2nd year Master Bioinformatics - icp | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
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| | | Learning outcomes |
- EC
| The student can handle scientific quantitative research questions, independently, effectively, creatively, and correctly using state-of-the-art design and analysis methodology and software. | - EC
| The student is capable of acquiring new knowledge. | - EC
| The student is able to efficiently acquire, store and process data. | - EC
| The student can critically appraise methodology and challenge proposals for and reported results of data analysis. | - EC
| The student can work in a multidisciplinary, intercultural, and international team. | - EC
| The student knows the international nature of the field of statistical science and data science. | - EC
| The student is an effective written and oral communicator, both within their own field as well as across disciplines. |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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The student has knowledge about molecular biology and understands the basic concepts of chemistry, physics, computer programming, combinatorics, statistics, biochemistry and biosynthesis.
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Bioinformatics; protein identification; protein expression analysis; mass spectrometry.
The course focuses on problems related to the analysis of protein sequences and protein expression. Examples of topics: protein identification using tandem mass spectrometry by database searches; analysis of protein expression data obtained by using mass spectrometry; diagnostic classification using protein mass spectra, isotope computation and low-level preprocessing of mass spectral data, quantitative proteomics by isobaric labels, isotope modeling, wavelet analysis for peak detection and noise removal.
Student possesses a general knowledge about topics and problems related to the analysis of protein sequences and protein expression. S/he is familiar with issues, methods and software associated with spectral interpretation. S/he is familiar with various experimental techniques used to study protein expression levels. S/he knows basic problems and methods related to the analysis of data obtained by using the techniques.
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Excursion/Fieldwork ✔
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Lecture ✔
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Project ✔
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Discussion/debate ✔
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Homework ✔
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Presentation ✔
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Period 1 Credits 4,00
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| Evaluation conditions (participation and/or pass) | ✔ |
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| Conditions | A student must at least attend all components of the evaluation. |
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| Consequences | Students get an "X" score if they do not meet the condition. |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Compulsory course material |
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Lecture notes; photo/electronic copies of relevant book chapters and papers; lab visit
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| Recommended reading |
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- Principles of Proteomics,Richard Twyman,2,Garland Science,9780815344728,Available as e-book: https://www.taylorfrancis.com/books/mono/10.1201/9780429258527/principles-proteomics-ph-cfe-richard-twyman-george
- Computational Methods for Mass Spectrometry Proteomics,Ingvar Eidhammer; Kristian Flikka; Lennart Martens; Svein-Ole Mikalsen,Wiley,9780470512975,Available as e-book: https://onlinelibrary-wiley-com.bib-proxy.uhasselt.be/doi/book/10.1002/9780470724309
- Protein Bioinformatics: An Algorithmic Approach to Sequence and Structure Analysis,Ingvar Eidhammer; Inge Jonassen; William R. Taylor,Wiley,9780470848395,Available as e-book: https://onlinelibrary-wiley-com.bib-proxy.uhasselt.be/doi/book/10.1002/9780470092620
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| 2nd year Master Biostatistics | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| 2nd year Master Data Science | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| 2nd year Master Quantitative Epidemiology | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| Exchange Programme Statistics | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
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| | | Learning outcomes |
- EC
| The student can handle scientific quantitative research questions, independently, effectively, creatively, and correctly using state-of-the-art design and analysis methodology and software. | - EC
| The student is capable of acquiring new knowledge. | - EC
| The student is able to efficiently acquire, store and process data. | - EC
| The student can critically appraise methodology and challenge proposals for and reported results of data analysis. | - EC
| The student can work in a multidisciplinary, intercultural, and international team. | - EC
| The student knows the international nature of the field of statistical science and data science. | - EC
| The student is an effective written and oral communicator, both within their own field as well as across disciplines. |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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|
The student has knowledge about molecular biology and understands the basic concepts of chemistry, physics, computer programming, combinatorics, statistics, biochemistry and biosynthesis.
|
|
|
|
Bioinformatics; protein identification; protein expression analysis; mass spectrometry.
The course focuses on problems related to the analysis of protein sequences and protein expression. Examples of topics: protein identification using tandem mass spectrometry by database searches; analysis of protein expression data obtained by using mass spectrometry; diagnostic classification using protein mass spectra, isotope computation and low-level preprocessing of mass spectral data, quantitative proteomics by isobaric labels, isotope modeling, wavelet analysis for peak detection and noise removal.
Student possesses a general knowledge about topics and problems related to the analysis of protein sequences and protein expression. S/he is familiar with issues, methods and software associated with spectral interpretation. S/he is familiar with various experimental techniques used to study protein expression levels. S/he knows basic problems and methods related to the analysis of data obtained by using the techniques.
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Excursion/Fieldwork ✔
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|
|
|
Lecture ✔
|
|
|
|
Project ✔
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|
|
|
|
|
|
|
Discussion/debate ✔
|
|
|
|
Homework ✔
|
|
|
|
Presentation ✔
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|
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|
Period 1 Credits 4,00
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| Evaluation conditions (participation and/or pass) | ✔ |
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| Conditions | A student must at least attend all components of the evaluation. |
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|
|
| Consequences | Students get an "X" score if they do not meet the condition. |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Compulsory course material |
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Lecture notes; photo/electronic copies of relevant book chapters and papers; lab visit
|
|
|
| Recommended reading |
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- Principles of Proteomics,Richard Twyman,2,Garland Science,9780815344728,Available as e-book: https://www.taylorfrancis.com/books/mono/10.1201/9780429258527/principles-proteomics-ph-cfe-richard-twyman-george
- Computational Methods for Mass Spectrometry Proteomics,Ingvar Eidhammer; Kristian Flikka; Lennart Martens; Svein-Ole Mikalsen,Wiley,9780470512975,Available as e-book: https://onlinelibrary-wiley-com.bib-proxy.uhasselt.be/doi/book/10.1002/9780470724309
- Protein Bioinformatics: An Algorithmic Approach to Sequence and Structure Analysis,Ingvar Eidhammer; Inge Jonassen; William R. Taylor,Wiley,9780470848395,Available as e-book: https://onlinelibrary-wiley-com.bib-proxy.uhasselt.be/doi/book/10.1002/9780470092620
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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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