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• Course title: ISB103: Academic Induction
• Number of ECTS: 2
• Course code: MMCB-2
• Module(s): Module 1.1
• Language: EN
• Mandatory: Yes

This introductory week consists of 3 parts:

• (i) Learning about the structure and rules of your Master study line.


• (ii) A brief overview of ethics in academic writing (e.g. plagiarism), how to properly handle references, and how to structure a typical scientific report.


• (iii) Basics of science communication.

• Understanding the structure and rules of your study line


• Being able to write reports for the upcoming experimental and computational courses


• Being able to communicate scientific results

1. Overview lecture and Q/A session to study line structure and rules
2. Lectures on ethics and academic writing
3. Lectures and case studies on research integrity
4. Lectures and exercices on science communication

CPE 1 title: Introduction to academic writing
Description: This class provides a brief overview of ethics in academic writing (e.g. plagiarism), how to properly handle references, and how to structure a typical scientific report, e.g. introduction, materials and methods, and results.ÌýÌý
Course instructors: Evan Williams

CPE 2 title:ÌýIntroduction to research integrity
Description:ÌýThis class provides a brief overview of research integrity and discusses key principles and case studies.
Course instructors: Thomas Sauter

CPE 3 title: Introduction to science communication
Description:ÌýThis class provides a brief overview of science communication
Course instructors: Serge Haan

Assessment modality:ÌýContinuous assessment

Assessment tasks/
Type of assessment/
Grading scheme/
Weight for final grade

• 
  Task 1:Ìý
  Written exam –Ìý20 points (0-20) –ÌýFull exam 50%
  Objectives:ÌýProper citations, plagiarism identification, recognize proper scientific writing styles (e.g. objective, impersonal)
  Assessment rules:ÌýCorrect responses
  Assessment criteria:ÌýCounts of correct responses

• 
  Task 2:Ìý
  Presentation –Ìý20 points (0-20) –Ìý25%
  Objectives:ÌýPresent and discuss case study.
  Assessment rules:ÌýClarity of presentation
  Assessment criteria:ÌýTeacher’s assessment

• 
  Task 3:Ìý
  Written exam –Ìý20 points (0-20) 25%


• 
  Objectives:ÌýProper citations, plagiarism identification, recognize proper scientific writing styles (e.g. objective, impersonal)
  Assessment rules:Ìý4 quizzes in Moodle
  Assessment criteria:ÌýCounts of correct responses
  

• Course title: ISB811: Biosafety and Introduction to Cell and Molecular Biology
• Number of ECTS: 3
• Course code: MMCB-1
• Module(s): Module 1.1
• Language: EN
• Mandatory: Yes

Getting an overview on working in a bioscience laboratory
Ability to design and perform experiments in modern bioscience
Understanding of the safety regulations in a bioscience laboratory

Safety regulations in bioscience
Sterile working
Ordering reagents
Preparing solutions
Designing and organizing experiments
Analysis of data
Presentation of research results

Written Exam: End of Course Assessment

Learning material
Ìý ÌýInstruction hand-outs, PDF-files of method articles
Teaching methods and assessment
Obligatory attendance, summary protocol

• Course title: ISB101: Genomics / Databases
• Number of ECTS: 5
• Course code: MMCB-3
• Module(s): Module 1.1
• Language: EN
• Mandatory: Yes

This course introduces the theory and practice of current concepts in genomics and genetics, particularly to introduce the genome as the basic foundation for systems biology. Topics include overview of genomes, sequencing and mapping, comparative genomics, population genetics and genomics, basic bioinformatics, population-level and rare variation analysis (SNPs, indels), functional genomics and clinical genomics. The course familiarizes students with the tools and principles of genomics, with a focus on the requirement for efficiently processing high volumes of data. By the end of the course, students will have a working knowledge of current genomics technologies and approaches as well as the types of databases and computational tools available.

Learn the fundamentals molecular biology and biochemistry background for genetics and genomics.
Obtain an overview on how current sequencing technologies work and how to analyse the data.
Introduce programmatic data analysis in R.
Become familiar with common, large biological databases routinely used in genomics and genetics, and how to retrieve and analyse these datasets.
Learn scripting the R programming language as well as searches with regular expressions.
Develop familiarity with command line interface of ³ÉÈËÍ·Ìõx shells for data transfer and handling.
After the course, students will understand how to perform large-scale data analyses on networked computers for genomics and related disciplines.

The course consists of half-day lecture segments on genetics and genomics technologies and five half-day lecture segments data analysis in R in the first week. The second week introduces a project to be conducted in groups that revisits key elements of the lectures in practical.

Total grade is composed of graded exercises in R, (30%), a graded report (35%) and written exam on genomics (35%).

Ìý Written exam:Ìý
Students will take an exam on the theory of genomics methods and the fundamentals
of DNA regulation and measurement.Ìý
Students will then submit a report on a particular set of DNA variants
assigned to them.

Ìý Presentation:Ìý
Students will prepare a written report regarding the practical project
in genomics, where they study the DNA from a sequenced family and identify the
causal mutations leading to disease.Ìý

Students have an oral presentation (ungraded) two days prior to the submission of the report, to make sure students have understood the project. Project is graded based on meeting criteria established in the rubric.ÌýÌý

Written exam on genomics:ÌýStudents will take an exam on fundamental commands and methods in
command line interfaces and in R.

Key words: databases, genomics, next-generation sequencing (NGS), single-nucleotide polymorphism (SNP), genome-wide association studies (GWAS), R, data analysis

• Course title: ISB201: Gene Regulation / Transcriptomics
• Number of ECTS: 5
• Course code: MMCB-4
• Module(s): Module 1.2
• Language: EN
• Mandatory: Yes

Ìý

Week 1:
After DNA replication, certain parts of the genome are transcribed into mRNA. This process is extremely well regulated and coordinated to allow for cell- and situation-dependent expression of necessary gene products. MISB201 is teaching a solid understanding of how gene expression works in mammalian cells and how it is regulated at all known levels. Furthermore, the non-coding genome is extensively covered.

Week 2:
An introduction into the most common language R to analyse high throughput gene expression data coming from various RNA Seq or single cell Seq. Explanations and hands-on exercises to learn to use: Data retrieval, Database use, Data formatting, Statistics QC of RNA Seq data, RNA Seq data analysis, and Sc Seq data analysis.Ìý

Ìý

Ìý

Learn critical thinking and approaching complex contents in a relatively short period of time, enhance self-study skills to repeat and recap the taught material. Interactive group exercises in class are included to enhance interactions and understanding.Ìý
Have a solid understanding of how gene expression works in a mammalian cells, how it is regulated at the various cellular levels, which types of RNA are generated and what functions they have in the cell, how gene expression can be measured and manipulated and how the data retrieved from high throughput technologies are handled and analysed.

1.Putting gene transcription into a general context of cellular life cycles;

2. Epigenetic mechanisms involved in gene expression;Ìý

3. Transcription machinery assembly at the promoter and the transcriptional process itself;

4. Post-transcriptional regulatory mechanisms (fine-tuning the amount of expressed genes);

5. Types of transcribed RNAs with a focus on lnc and miRNAs;

6.ÌýTechnologies to measure and quantify gene expression.

7. R to analyse high throughput gene expression data coming from various RNA Seq or single cell Seq.

8. Data retrieval, Database use, Data formatting, Statistics QC of RNA Seq data, applications of up-to-date bioinformatics tools and packages (as these are changing, this will be updated regularly)

Written exam:

Objective: Overview of transcriptomics (first week)

Assessment criteria:ÌýAssessing knowledge of the theory behind gene regulation

Ìý

ÌýTake-home assignment
:

Objective:ÌýWriting an R script for RNA Seq data analysis

ÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌý

• Course title: ISB301: Protein Structure and Function
• Number of ECTS: 5
• Course code: MMCB-5
• Module(s): Module 1.2
• Language: EN
• Mandatory: No

• Solid knowledge of how proteins function as ‘molecular machines’


• Understand general ‘rules’ and common principles in protein activity regulation


• Understand the generic architecture of proteins and protein mediated processes (enzyme catalysis, signalling)


• Learn about the evolutionary principles that are exploited to create the diversity of proteins


• Apply knowledge to the difficult question of drug discovery

Ìý

In the main lecture we will use a mix of classical theory- and methods-focused lectures, flipped classroom teaching, Kahoot-formative testing and exercises to provide you with an intensive training in modern protein biology.
We will start by reviewing basics of chemistry that apply to protein biochemistry and repeat the fundamentals from amino acids to secondary structures. Next we have a look at the basic building blocks of proteins, domains, and learn how these combine to form new functional entities. Then we look at how proteins react as enzymes and with each other, how they are modified, and which factors determine how fast they react. In the fourth section, we look at how major signalling pathways function on the protein-structural level, before we in the fifth section look at drug discovery. We learn about basics in drug discovery and will apply our knowledge from all the sections in group exercises to formulate steps necessary in drug discovery.
These theoretical sections are supported by method focused lectures, where we learn about common tools in protein biochemistry. This includes, the structure and application of antibodies e.g. in Western blotting, bio/physical techniques to study protein-protein interactions in vitro and in cells, basics of protein structure determination and common assays in drug discovery.
Additional lectures and exercises will introduce you to the use of protein databases and computational protein structure analysis.
In an accompanying seminar you will elaborate a presentation on a protein science topic and present it to the class.
Last but not least, you will gather hands on experience in a practical that will introduce you to basic techniques of protein biochemistry, such as Western blotting.

• Two Quick Tests during the lecture – 20% of the final grade


• Report and contribution to practical (TP) – 30 % of the final grade


• Final written exam – 50 % of the final grade

Bibliography
How proteins work (Mike Williamson) Garland Science, ISBN-10: 9780815344469
https://www.amazon.com/How-Proteins-Work-Mike-Williamson/dp/0815344465/

• Course title: ISB302: Proteomics
• Number of ECTS: 5
• Course code: MMCB-6
• Module(s): Module 1.2
• Language: EN
• Mandatory: No

The course will provide an overview of current proteomics, covering topics such as proteomes, their relationship to genomes and transcriptomes, and the principles of proteostasis, which involves balancing protein synthesis and degradation. We will also discuss the role of mass spectrometry in modern proteomics experiments and clinical applications. To reinforce these concepts, students will participate in a practical course where they will analyze the effect of a chemotherapeutic drug on the proteome composition of cell culture cells. Each student will prepare their own samples, which will be analyzed using mass spectrometry, SDS-PAGE, and western blotting.

Biological mass spectrometry
Mass spectrometry-based proteomics
Analytical strategies for proteins (enrichment, separation, identification and quantification)
Phosphoproteomics
Protein microarray

The course will cover the following proteomics techniques: Liquid chromatography, mass spectrometry of proteins and peptides (LC-MS), Identification of peptides and proteins, Interpretation of peptide mass spectra, Quantification of peptides and proteins, Isotope labelling techniques for multiplexing peptide analysis, Tracing of protein synthesis using isotope-labelled amino acids, Measurement of post-translational modifications, Measurements of protein-protein interactions, Protein labelling by orthogonal methodologies. Additional methods that will be taught: Protein extraction from cell culture cells, Protein analysis using SDS-PAGE, Protein identification using Western blotting.

Ìý 1) Take-home assignment: (40 % of the final grade)

Objectives:
Scientific work relies on the effective communication of ideas and the
ability to present a finding in a comprehensive, understandable way. The report
is designed to take the results summarized in the presentation into a written
form that fits the requirements of modern scientific reports.

Assessment rules:Ìý
The reports are scored by the teaching staff on a scale from 0 to 20.
The reports have to be handed in through the Moodle system and by the time
indicated in Moodle. No reports will be accepted that are not submitted through
the Moodle system.

Assessment criteria:Ìý
The report will be judged for the following criteria: scientific
content, readability, structure, validity of the conclusions and if the report
is in line with the formal requirements outlined in the instructions to the
practical course.

Ìý2)
Ìý Written exam
:
(30 % of the final grade)

Objectives:
Ìý
The written exam will cover the lectures and the practical parts of the
course. The test is a multiple-choice test with 30 questions.

Assessment rules:Ìý
Selecting the right answer from a number of possible answers.

Assessment criteria:Ìý
Each question counts the same. A question is considered as falsely
answered if the wrong answer is selected or more than the allowed answers are
selected. The test contains questions that require calculations. Only
scientific calculators are allowed during the test (No use of a phone or
similar).

3)
Ìý Presentation
: (20 % of the final grade)

Objectives:
Ìý
Summarize the results of the practical course and present them in a
concise form that is understandable for other participants and the teaching
staff.

Assessment rules:Ìý
The student will get feedback on the structure, the presentation style
and the results that are presented

Assessment criteria:Ìý
Presentation quality – readability, font size, use of headlines,
complete labelling of graphs – does the presenter obey the 5 min limit, is the
presentation understandable?

4)Ìý
ÌýÌý
Quiz
:Ìý
(10 % of the final grade)

Objectives:Ìý
Repeat and deepen the understanding of the different techniques and
proteomics concepts that were introduced in the lectures

Assessment rules:Ìý
Answer 10 questions online using the Moodle system.

Assessment criteria:Ìý
Four quizzes with 10 points each. There is no limit to repeating the
quizzes.

Ìý

Ìý

Ìý

Support:
Handout: A booklet prepared by lecturers will be provided.

• Course title: ISB202: Practicals in Gene Regulation
• Number of ECTS: 5
• Course code: MMCB-7
• Module(s): Module 1.3
• Language: EN
• Mandatory: No

• Practical approach to transcriptomics: experimental manipulation of gene expression in cancer cells


• Analysis of transcriptomic high throughput data and selection of interesting target genes for validation


• Perturbation of gene expression of selected target genes


• Extraction of RNA from cultured and manipulated cancer cells


• Measuring gene expression levels by qPCR


• Determination qPCR primer efficiency


• Using reporter gene assays to study promoter activation via cytokine stimulation of cultured cells


• Performing wet lab experiments

Ìý

• Understanding principles of practical gene level perturbation


• Analysing high throughput data (RNAseq) to identify single targets of interest


• Experiencing and performing tissue culture, cancer cell treatment/stimulation, RNA extraction + quantification and qPCR to measure affected gene expression levels: standard measure to quantify gene expression


• Understanding principles, data analysis and QC aspects (e.g. primer efficiency and design) of qPCR


• Analysing other, supplied data (qPCR data) in relation with generated data


• Understanding principles of reporter gene assays and promoter activation via specific transcription factors (in vitro and in silico)


• Generating and critically analysing own data


• Working in a team in a wet lab environment


• Writing a detailed scientific report

Ìý

Practical work in teaching lab, lectures, data analysis:

• Melanoma tissue culture
• Treatment of cells with cancer drugs (targeted therapy)
• RNA extraction and quantification
• Reverse Transcription
• qPCR with data analysis of own (and provided) results
• Stimulation of melanoma cells with cytokines for promoter activation
• Reporter gene assay
• Introductory lecture on the course (theory and practical details), lectures on RNA+RNA extraction, qPCR data analysis, reporter gene assays, primer design
• Bioinformatic analysis of RNAseq data generated in Signal Transduction lab
• qPCR primer design
• in silico promoter studies

Ìý

Task 1:Ìý
Take-home assignment (WrittenÌýreport)Ìý20 points (0-20)Ìý60%
Objectives:ÌýFinal report
Assessment criteria:ÌýQuality of report writing, presentation of scientific results generated in the wet lab course, understanding of the results and interpretation, troubleshooting capacity, correctness of scientific results and provided tasks.

Task 2:ÌýÌý
Written exam (
Knowledge test during the course)Ìý20 points (0-20)Ìý15%
Objectives:ÌýTesting knowledge of provided course material and scripts, standard wet lab calculations
Assessment criteria: Performance

Task 3:Ìý
Active participation PracticalÌýlab workÌý
20 points (0-20): 15 %


Objectives:Ìý
practically planning and performing molecular biological experiments; generating interpretable scientific data; observing safety rules and punctuality, bioinformatic analysis of transcriptomic high throughput data.


Assessment rules:ÌýPresence in the lab, active participation, pipetting skills, level of understanding of required tasks
Assessment criteria:ÌýMotivation, performance (wet lab skills),Ìý2 mini reports (promoter studies, bioinformatic analysis of RNAseq data)

Task 4: Presentation (Journal Club 20 points (0-20):Ìý
10%


Objectives:Ìý
Presenting a scientific publication to whole group of students, summarizing and explaining complex data on different topics


Assessment rules:ÌýPowerPoint presentation, explain the article’s purpose, methods, results and conclusions in a clear and understandable way, discuss data criticallyÌý
Assessment criteria:ÌýPresenting skills, content of presentation, active participation during discussion

ÌýÌýÌýÌýÌýÌýÌýÌýÌýÌýÌý

• Course title: ISB701: Introduction to Systems Biology
• Number of ECTS: 5
• Course code: MMCB-8
• Module(s): Module 1.3
• Language: EN
• Mandatory: No

Getting an overview on the elements of systems biology and its concepts and applications; Ability to analyze biological processes by systems biology methods and concepts; Understanding of the principles of systems biology, such as topology, stochiometry and kinetics

Recall and apply key procedures and methods in mathematics and bioinformatics; Differentiate the key principles of bottom-up systems biology; Integrate basic understanding of bottom-up systems biology by designing, creating and analyzing models

Definition of systems biology; Basic concepts in systems biology; Biophysical basis of enzyme reactions; Math recap: Matrices; Linear Equations and Ordinary Differential Equations; Balancing and Modelling; Model Analysis (Steady States, Stability, Phase Portrait, Bifurcation plot); Network motifs; Application examples

Written exam:Ìý

1) Understanding after week1

2) Understanding after week2

3) Competency in Modeling and model analysis

Detailed Course Handbook including links to deepening youtube videos, as a basis for independent studying during this flipped-classroom course.

• Course title: ISB702: Pharmacokinetics
• Number of ECTS: 5
• Course code: MMCB-9
• Module(s): Module 1.3
• Language: EN
• Mandatory: No

Getting an overview of the elements of pharmacology pharmacokinetics (PK) and its concepts and applications; Ability to model and analyze simple PK processes; Develop, run and present own PK model based on ordinary differential equations.

Recall and apply key procedures and methods in modelling and model analysis; Understand and Differentiate the key principles of PK; Integrate basic understanding of PK applying dynamical modelling within the R framework.

Definition of pharmacology and PK; Basic concepts in PK: ADME – Absorption, Distribution, Metabolism, Elimination; PK models and application examples;Ìý Safety pharmacology; Introduction mrgsim package in R; Modelling case studies; Modelling project: Develop, run and present own project idea, with the help of tutors

Continuous assessment

Week 1

• Written examÌýMultiple choice -25% of the final grade

Week 2

• Written examÌýMultiple choice – 25%Ìýof the final grade

Presentation

• Pitch and present own project – 50 % of the final grade

Lecture slides and modelling material will be provided on moodle.

• Course title: ISB104: Translational biomedical research in neurodegeneration – from bed-to-bench-to-bedside
• Number of ECTS: 5
• Course code: MMCB-10
• Module(s): Module 1.3
• Language: EN
• Mandatory: No

• Introduction to clinical and translational medicineÌý


• Introduction into precision medicineÌý


• Practical experience of recruitment of study participantsÌý


• Processing of patient’s bio-samples for molecular profiling (RT-QuIC)


• Patient-derived cellular disease models


• Lab automationÌýÌý


• Use of patient derived cellular disease models for phenotypic drug screeningÌý


• Designing of a Clinical Study including arms, events and Case Report Forms (CRFs)Ìý


• Introduction to Electronic Data Capturing (EDC) system – REDCapÌý


• Cross-talk between clinician, data scientist and lab scientist


• FAIR principles and data FAIRification of data (making data Findable, Accessible, Interoperable and Reusable)Ìý


• Clinical data curation, harmonization and basic analysisÌý


• Different types of clinical trials and expected outcomes


• Biomarkers for precision medicineÌý


• Translation into care and preventionÌý
  

This course focuses on the introduction to translational biomedicine, a rapidly growing discipline across different biomedical research discipline. It aims to (i) identify unmet needs together with people with Parkinson’s disease, (ii) to accelerate the transfer of knowledge generated on the bench (laboratory) to be translated back to bedside (clinical trials and care). This course will introduce the clinical and translational medicine field, addressing its evolution and fundamental concepts including (i) domain expertise, (ii) interdisciplinary collaboration and (iii) outreach and communication, with concrete examples in the context of neurodegenerative diseases e.g. Parkinson’s disease (PD). Students will have the opportunity to visit the Parkinson’s Research Clinic (PRC) at CHL (Centre Hospitalier de Luxembourg) and experience the daily clinical research routine and recruitment of people with PD for clinical studies. This course will also include hands-on laboratory practice of how researchers process the collected bio-samples from people with PD and make them available for subsequent molecular (e.g sequencing) and cellular (e.g. induced pluripotent stem cells) profiling and drug screening. In addition, this course will also introduce into biocomputational expertise, i.e. how to design a case report form (CRF), capture data from a clinical study using an electronic data capturing system (e.g. REDCap), how to curate and FAIRify (making data Findable, Accessible, Interoperable and Reusable) the collected data and finally analyze the curated data for unlocking the potential of deep phenotypes patient cohorts for an earlier diagnosis and a better treatment.Ìý Overall the course integrates biocomputational, biological and medical expertise for a comprehensive translational concept.

First session

• Written exam (50%)


• Report of laboratory work (50%)

Retake exam

• Oral exam

• The Fundamental Characteristics of a Translational Scientist DOI: 10.1021/acsptsci.9b00022


• Electronic Data Capturing (EDC) system – REDCap short video (5min)


• FIAR principles publication