Functional Omics

Code:

BIOL4036

Acronym:

BIOL4036

Level:

400

Keywords
Classification	Keyword
OFICIAL	Biology

Instance: 2018/2019 - 2S

Active?	Yes
Responsible unit:	Department of Biology
Course/CS Responsible:	Master in Bioinformatics and Computational Biology

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
E:BBC	1	PE_Bioinformatics and Computational Biology	1	-	6	42	162
M:BBC	10	The study plan since 2018	1	-	6	42	162

Teaching language

Suitable for English-speaking students

Objectives

This curricular unit aims to provide an integrative view of cellular and biological organization, by addressing research hypothesis by a holistic approach.

At the end of this course it is expected that the student will:

- Understand the basics of the techniques commonly used in each omics (proteomics, genomics, transcriptomics, metagenomics, and metabolomics) and their associated methodologies;

- Get acquainted with the bioinformatics resources and databases associated to the different omics;

- Acknowledge the potential to gather and integrate omics metadata to address scientific questions;

- Understand, the potential of omics for basic and applied science, namely in the fields of biotechnology and biomedicine;

- Be able to design experimental set-ups using omics tools.

Learning outcomes and competences

The learning should be centered on an advanced training in the use of bioinformatic applications specific to each omics, to allow:

i) The acquisition of state-of-the-art knowledge, including concepts, tools and applications concerning the different omics;

ii) The development of an analytical atitude, which simultaneously allows teachers to diagnose the main difficulties faced by students and instruct new practices to reinforce learning;

iii) Consolidate the competencies defined in the objectives of this curricular unit and stimulate students' interest and motivation, through the analyses of case studies, scientific papers and of experimental data sets provided by the instructor;

iv) To favor an integrative perspective of the different omics, namely proteomics, genomics, transcriptomics, metagenomics and metabolomics, resulting in a holistic approach that accommodates the various levels of biological organization from genes and proteins to cells, organisms and ecosystems.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Not applicable.

Program

1 - Proteomics:

1.1 - Based on mass spectrometry, highlighting: i) sample preparation; ii) acquisition of data; iii) analysis of results.

1.2 - Focus on the methodology of protein identification and quantification.

1.3 - Procedures for obtaining and interpreting results using appropriate databases and software tools.

2 - Genomics, Transcriptomics and Metagenomics

2.1 - Sequences and related information

2.1.1 - Types of molecular data

2.1.2 - Databases and metadata

2.1.3 - Sequence databases of and other specialized resources

2.2 - Genomics 

2.2.1 - Genome, sequencing, assembly, annotation and changes 

2.2.2 - Comparative genomics

2.3 - Transcriptomics

2.3.1 - Microarrays and RNA-seq

2.3.2 - RNA-seq: introduction, advances, methods and applications

2.4- Metagenomics and Metabarcoding

2.4.1 - Objectives, challenges, data analysis and interpretation

3 - Metabolomics:

3.1 - Introduction to Metabolomics. Metabolom as object of study. The state of the art in the analysis of the metabolites in a biological system;

3.2 - Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS).

3.3 - Flowchart of a metabolomic analysis. Its importance.

3.4 - Information on the treatment of the enormous amount of data generated by NMR and MS, through the use of bioinformatic tools. Chemical analysis. Exploratory analysis of its biological and biochemical meaning.

Mandatory literature

Ankney JA, Muneer A, Chen X ; Relative and Absolute Quantitation in Mass Spectrometry-Based Proteomics., Annu Rev Anal Chem (Palo Alto Calif) 11, 49-77, 2018
Barsnes H, Vaudel M ; SearchGUI: A Highly Adaptable Common Interface for Proteomics Search and de Novo Engines., J Proteome Res 17, 2552-2555, 2018
Beckonert O, Keun HC, Ebbels TM, Bundy J, Holmes E, Lindon JC, Nicholson JK ; ., Nat Protoc 2(11):2692-703, 2007
Chan EC, Pasikanti KK, Nicholson JK; ., Nat Protoc 6(10):1483-99, 2011
Cox J, Mann M ; Quantitative, high-resolution proteomics for data-driven systems biology. , Annu Rev Biochem 80, 273-99, 2011
Dunn WB, et al. ; ., Nat Protoc 6:1060-1083, 2011
Monteiro MS, Carvalho M, Bastos ML, Guedes de Pinho P.; Metabolomics analysis for biomarker discovery: advances and challenges., Curr Med Chem. 2013;20(2):257-71, 2013
Tyanova S, Temu T, Cox J ; The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. , Nat Protoc 11, 2301-2319, 2016

Teaching methods and learning activities

This course is organized in theoretical-practical classes consisting in expository lectures, problem solving exercises and hands-on activities, altogether favoring interaction with the students. The lectures are complemented with laboratory activities that include the contact with the technological platforms used to obtain data concerning the different omics and the execution of in silico routines for data collection, treatment and analysis, in order to provide the students with a general knowledge of the pipelines used to retrieve data, and their contact with reference databases needed for assertive data analyses.Whenever relevant, learning can be enhanced by blend-learning strategies using Moodle or Sigarra, which will favor students’ knowledge acquisition.

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Trabalho escrito	25,00
Trabalho laboratorial	30,00
Apresentação/discussão de um trabalho científico	30,00
Teste	15,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Apresentação/discussão de um trabalho científico	60,00
Frequência das aulas	42,00
Trabalho escrito	40,00
Trabalho laboratorial	20,00
Total:	162,00

Eligibility for exams

The following tasks are required:

1- Presentation / discussion of a scientific work

2 - Frequency of 3/4 of classes

3 - Performing the written work

 

Calculation formula of final grade

Each module defined in the programmatic contents, i.e. proteomics; genomics / transcriptomics / metagenomics ; and metabolomics, will have an evaluation component, with the following structure and weight: 

Proteomics = 25% of final grade
- The evaluation will consist of a written report / work. 

Genomics / transcriptomics / metagenomics = 60% of the final classification
- Oral presentation / discussion of a scientific work (30%).
- Execution of a practical work and preparation of the report (30%). 

Metabolomics = 15% of final grade
- The assessment will consist of a written test.

Examinations or Special Assignments

Not applicable.

Internship work/project

Not applicable.

Special assessment (TE, DA, ...)

Not planned.

Classification improvement

Not planned.

Observations

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