Course: Omics Project: Integromics credits: 10

Course code
BFVM23PRJOMICS
Name
Omics Project: Integromics
Study year
2023-2024
ECTS credits
10
Language
English
Coordinator
F. Feenstra
Modes of delivery
  • Lecture
Assessments
  • Omics Project: Integromics 1 - Assignment

Learning outcomes

  1. You formulate a clear, verifiable hypothesis on the basis of a client’s research question; identify and understand possible Omics techniques necessary for answering a research question and hypothesis  

  1. You evaluate datasets for utility in answering a client’s hypothesis  

  1. You pre-process datasets in order to be able to do inter-dataset analysis 

  1. You apply and validate data science techniques in pre-processing data and meta-analysis across datasets  

  1. You identify business and economics factors applicable to the research question and integrate them with the final conclusion (where applicable) 

  1. You present findings in a clear and scientific manner to the target audience (client, researchers, peers)  

Content

This course introduces the integration of various "omics" techniques that are used to address research questions that cannot be answered by a single analysis. These techniques are both quantitative and high throughput, generating large datasets that can be analysed using advanced statistical and machine learning methods. The course begins by introducing state-of-the-art lab techniques in areas such as (meta)genomics, transcriptomics, metabolomics, proteomics, epigenomics, foodomics, imaging, and epidemiology. Students will have the opportunity to select a research project from partner research centres such as UMCG, AVEBE, KCBBE, and the Digital Society Hub that provide multiple datasets, and formulate and test hypotheses using appropriate data science techniques (Statistcs/Machine Learnng/Artificial Intelligence). A key aspect of this course is effectively communicating the methods and findings to peers and clients. 

This course builds upon the technologies mastered in the first research project, and when appropriate, visualizations and web techniques from the first project will be utilized to report and clarify findings. 

Included in programme(s)

School(s)

  • Institute for Life Science & Technology
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