Biomedical Engineering

PAOLA PACI
PAOLA PACI

This course aims to provide students with a practical and hands-on experience with common modeling and analysis tools of "omics" data in molecular biology and medicine. It would be expected that after completing this course a student would be able to model, analyze and interpret using Matlab, large scale genomic data like, for example, transcriptomics data of a patient using the appropriate methodology. Furthermore, students will understand the basic biological theory behind these analysis tecniques and critically analyze the results.

General Objectives
• Provide students with a solid theoretical and practical foundation in bioinformatics.
• Enable students to use bioinformatics tools to analyze biological data.
• Promote understanding of molecular biology through the use of computational technologies.

Specific Objectives
• Familiarize students with major biological databases and bioinformatics software.
• Teach how to analyze and interpret genomic and transcriptomic data.
• Provide skills to perform statistical analyses applied to biology.

Knowledge and Understanding
• Knowledge of the basics of bioinformatics and the main technologies used in the analysis of biological data.
• Understanding of fundamental biological principles, such as DNA structure, transcription, translation, and genetic variability.

Applying Knowledge and Understanding
• Be able to use bioinformatics tools and software to analyze DNA, RNA, and protein sequences.
• Apply statistical techniques to interpret results from bioinformatics analyses.

Critical and Judgmental Skills
• Develop the ability to critically assess the results of bioinformatics analyses.
• Be able to make informed decisions about the methodological approach to use based on the type of available data.

Communication Skills
• Be able to communicate the results of bioinformatics analyses clearly and precisely, both in written and oral form.
• Present data effectively, using tables, graphs, and other visualizations.

Learning Skills
• Be able to independently keep up-to-date with the latest developments in the field of bioinformatics.
• Develop the ability to learn new bioinformatics techniques and tools independently.

Basic knowledge of computer science.

1-Introduction to bioinformatics
2-Elements of molecular biology
3-Biological Databases
4-UCSC Genome Browser e Table Browser
5-Review of descriptive statistics
6-Hypothesis tests and hypergeometric hypothesis test
7-Enrichment analysis
8-Introduction to R programming
9-Biomart with R
10-Introduction to TGCA
11-Elements of NGS
12-Elements of network theory
13-Practice

course's slides

reference literature provide during the course

The course includes both a theoretical and a practical part.
The student will use his own computer whenever possible.
Homework will be assigned which must be delivered by the end of the course.

Attendance at the course is optional.

The student must deliver a project agreed with the teacher.
The final exam will concern the oral discussion of the chosen project.
The final evaluation will reflect both the judgment on the work done at home regarding the tasks assigned during the course,
and a judgment on the student's capacity for reasoning, synthesis and self-employment.

What does DEGs means?

• 4 hours
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• 10 hours
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• 10 hours
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• 4 hours
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• 20 hours
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• 1 hour
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• 4 hours
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• 14 hours
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• 12 hours