Genetics and Genomics

• Teachers
• Weekly hours
• Learning Outcomes
• Objectives
• Contents
• Activities
• Teaching methodology
• Evaluation methodology
• Bibliography

Teachers

Person in charge

• Ferran Casals Lopez ( )

Others

• Alejandro Sánchez Gracia ( )
• Marta Riutort León ( )

Weekly hours

Learning Outcomes

Learning Outcomes

Knowledge

• K1 - Recognize the basic principles of biology, from cellular to organism scale, and how these are related to current knowledge in the fields of bioinformatics, data analysis, and machine learning; thus achieving an interdisciplinary vision with special emphasis on biomedical applications.
• K6 - Recognize the ethical problems that arise from advances in the knowledge and in the application of biological concepts and their computational processing.

Skills

• S2 - Computationally analyze DNA, RNA and protein sequences, including comparative genome analyses, using computation, mathematics and statistics as basic tools of bioinformatics.
• S6 - Identify and interpret relevant data, within the area of study, to make judgments that include social, scientific or ethical reflections.
• S8 - Make decisions, and defend them with arguments, in the resolution of problems in the areas of biology, as well as, within the appropriate fields, health sciences, computer sciences and experimental sciences.
• S9 - Exploit biological and biomedical information to transform it into knowledge; in particular, extract and analyze information from databases to solve new biological and biomedical problems.

Competences

• C6 - Detect deficiencies in the own knowledge and overcome them through critical reflection and the choice of the best action to expand this knowledge.
• C7 - Detect, from within the scope of the degree, inequalities based on sex and gender in society; integrate the different needs and preferences based on sex and gender in the design of solutions and problem solving.

Objectives

1. Ability to describe the molecular and cellular organization and function of hereditary material
   Related competences: K1, C6,
2. Understanding the mechanisms of inheritance and the genetic basis of disease.
   Related competences: K1, K6, S6, C7, C6,
3. To choose and apply instrumental, analytical, molecular and informatics techniques
   Related competences: S2, S6, S8, S9, C7, C6,
4. Analyze a genetic problem and search for tools to address and solve it.
   Related competences: K1, K6, S2, S6, S8, S9, C7, C6,

Contents

1. Introduction to Genetic Analysis.
   Main mechanisms of genetic inheritance.
2. Crossover and recombination.
   Genetic maps.
3. Genetic variation.
   Functional annotation and interpretation.
4. Medical genomics.
   Rare and complex disorders.
5. Transcriptomics.
   Expression analysis.

Activities

Activity Evaluation act

Teaching methodology

Evaluation methodology

Bibliography

Basic:

• Introduction to Genetic Analysis Twelfth Edition - Anthony Griffiths (Author), John Doebley (Author), Catherine Peichel (Author), David Wassarman (Author), WH FREEMAN, ISBN: 978-1-319-11478-7
  
• Vogel and Motulsky's Human Genetics: Problems and Approaches - Friedrich Vogel , Springer, ISBN: 978-3540164111