Whole System Molecular Medicine

Module details

Title

Whole System Molecular Medicine

Type

Specialist

Module code

SBI130

Credits

10

Requirement

Compulsory

Aim of this module

It is becoming increasingly clear that diseases and disease processes are complex and involve many interactions within the genome, across metabolic pathways, and between the individual and the environment. Such considerations are important if the consequences of variations observed within an individual’s genome are to be effectively assessed. Rapid advancements in areas such as functional genomics and systems biology are now providing new insights into such processes. However, accessing these methodologies requires the use of forms of mathematics that have not been traditionally used within genetic medicine. This module will develop and strengthen the trainee’s mathematical and modelling skills, and introduce them to functional genomics and systems biology strategies and the ways in which they can be applied in medicine for improved patient care. This module will enable the trainee to gain experience of the process and application of the skill of literature searching and the use of bioinformatic resources within a clinical setting. This module will enable the trainee to develop and strengthen their mathematical and modelling skills and introduce them to functional genomics and systems biology strategies and the ways in which they can be applied in medicine for improved patient care within an ethical and governance framework.

Competencies

#	Learning outcome	Competency	Action
# 1	Learning outcome 1	Competency Select a gene and perform a thorough literature search.	Action View
# 2	Learning outcome 1	Competency Identify bioinformatic resources for gene interactions and networks.	Action View
# 3	Learning outcome 1	Competency Identify biological pathways in which gene(s) operate.	Action View
# 4	Learning outcome 1	Competency Critically evaluate and integrate all information.	Action View
# 5	Learning outcome 1	Competency Produce a written summary of reference sequences and single-nucleotide polymorphisms (SNPs) within networks with phenotype information.	Action View
# 6	Learning outcome 1	Competency Identify and evaluate current state-of-the-art resources as appropriate.	Action View
# 7	Learning outcome 2	Competency Identify a disease area of interest following discussions with clinical teams, and perform a literature search around clinical phenotype, including any clinical databases.	Action View
# 8	Learning outcome 2	Competency Interrogate a range of bioinformatic resources for disease pathway interactions.	Action View
# 9	Learning outcome 2	Competency Critically evaluate and integrate all information.	Action View
# 10	Learning outcome 2	Competency Produce a written summary of the biological pathways with phenotypic information.	Action View
# 11	Learning outcome 2	Competency Identify and evaluate current state-of-the-art resources as appropriate.	Action View
# 12	Learning outcome 3	Competency Use network strategies from learning outcomes 1 and 2 to develop an enhanced testing strategy.	Action View
# 13	Learning outcome 3	Competency Determine if pathway-based gene testing is appropriate.	Action View
# 14	Learning outcome 3	Competency Document the analysis process, justify the recommendation and proposed gene panel (if recommended).	Action View

Assessments

You must complete:

• 2 case-based discussion(s)
• 2 of the following DOPS/ OCEs:

Generate a list of papers related to a specific disorder to form the basis of a systematic review Identify the biological pathway in which a specific gene operates using available databases	DOPS
Following a SOP run the NGS data for a batch of samples through an analysis pipeline and output a list of filtered variants for each sample.	DOPS
Evaluate the quality of a NGS run using suitable quality control tools e.g. FASTQC	DOPS
Run checks on the data processed and trigger appropriate actions before sending to Clinical Scientists	DOPS
Discuss a specific clinical condition with relevant clinical team	OCE
Present results of an NGS based analysis to an MDT meeting	OCE

Learning outcomes

1. Critically evaluate the literature and bioinformatic resources to identify biological pathways in which a gene(s) could participate.
2. Critically evaluate the literature and bioinformatic resources to identify biological pathways that play a role in a specific disease process e.g. host/pathogen interactions.
3. Develop pathways and network data to inform a service development, and enhance testing strategy for a specified patient population.

Learning outcomes

1. Discuss the role of gene networks in specific genetic diseases.
2. Describe the importance of genetic background in developing an understanding of the role of a specific allele or mutation.
3. Describe the range of resources available to describe metabolic networks.
4. Describe resources available that describe gene–gene and protein–protein interactions.
5. Describe the range of networks in which a particular gene might participate.
6. Describe the application of basic differential equation modelling techniques for describing metabolic networks.
7. Discuss the available repositories of models used in systems biology.
8. Describe the importance of parameter selection in modelling.
9. Describe a range of modelling strategies used to describe pathways.

Indicative content

Mathematics

• Basic calculus
• Building simple models using differential equations
• Software tools for solving simple differential equation models (Matlab, Copasi)

Bioinformatics pathway tools

• Databases of metabolic networks (Kegg, Panther, etc.)
• Databases of gene interactions (string, etc.)
• Gene ontology and pathway analysis
• Strategies for determining whether a pathway is over-represented in a set of genes (Fisher exact t-test, methods based on gene lists)

Systems biology

• Introduction to Systems Biology Markup Language (SBML)
• Repositories of pathway models
• Determining model parameters from the literature
• Stability analysis of ordinary differential equations (ODE) models (Jacobians)

Activities

• Work with a clinical team(s) to identify current knowledge and understanding of specific clinical disorders and reflect on the role of clinical bioinformatics within a clinical service.
• Observe the use of clinical bioinformatics in a range of settings, for example research, industry, or mainstream medicine, and discuss the impact of clinical bioinformatics on the prevention and treatment of disease, identifying your learning needs and developing an action plan to address them.
• Based on your clinical experiential learning, discuss with your training officer how to bridge the potential gap between molecular medicine and clinical medicine.
• Attend a local research meeting and present and defend the service development you have proposed, reflecting and responding to feedback from colleagues.