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FC6 - Departamento de Ciência de Computadores FC5 - Edifício Central FC4 - Departamento de Biologia FC3 - Departamento de Física e Astronomia e Departamento GAOT FC2 - Departamento de Química e Bioquímica FC1 - Departamento de Matemática

Courses

Bachelor in Bioinformatics

General information

Official Code: 9687
Acronym: L:BIOINF
Description: A Bioinformática é uma disciplina na interface das revoluções em curso na Biologia e Ciência de Computadores. Tem como objetivo analisar e compreender dados biológicos e biomédicos, em particular ao nível celular e molecular. Envolve o desenvolvimento e a aplicação de algoritmos e ferramentas computacionais, nomeadamente de inteligência artificial e machine learning, para organizar, analisar e extrair informações relevantes de grandes conjuntos de dados biológicos, contribuindo para avanços em áreas como a genómica e outras ómicas, genética, biologia de sistemas, patologia, ecologia, evolução, epidemiologia, entre outras.

Certificates

  • Bachelor in Bioinformatics (180 ECTS credits)

Courses Units

Linear Algebra and Analytic Geometry

M1002 - ECTS

Upon completing this course, the student should master the main concepts of Linear Algebra and Analytic GeometryNamely, he must understand, be able to work with and use the main properties of the concepts of matrix, determinant, real vector space and linear function.

Cell Biology

BIOL1023 - ECTS The Cell is the fundamental unit of life and its structure and functions are central to Biology. The Curricular Unit (UC) Cell Biology (BC) aims to provide the knowledge necessary to understand the architecture of the cell and the integrated functioning of cellular life. It is also the objective of this UC to work its contents in an application context, and to provide hands-on contact with different types of cells, organelles and cellular processes, as well as with some of the fundamental techniques and methodologies for the construction of the knowledge in Cell Biology (eg, optical microscopy and cell fractionation).

Calculus I

M1001 - ECTS

To become acquainted with the basic concepts and techniques of calculus at the level of real-valued functions of a single real variable, as well as sequences and series.

 

Introduction to Computers

CC1002 - ECTS

Provide students with an overview about Computer Science, in particular, the fundamental concepts about the organization and operation of digital computers and operating systems.

Programming I

CC1015 - ECTS

In this course the students will:
1. Get acquainted with personal computers in the GNU/Linux operating system and their usage;
2. Learn how to write computer programs using Python and execute them in a terminal.
3. Acquire competence in the implementation of simple algorithms;
4. Acquire good code structuring and programming style;
5. Learn some basic data structures and algorithms;
6. Get acquainted with program debugging and testing.

Molecular Biology

BIOL1024 - ECTS

Artificial Intelligence and Data Science

CC1023 - ECTS This will address the state-of-the-art topics of Artificial Intelligence (AI) and Data Science (DS), giving students a technical knowledge, although not in-depth, about its concepts, problems and applications.

Regarding the AI ​​and DS areas, the objectives of the course are:

- Provide a historical perspective of its emergence and evolution.
- Identify its relevance and impact in the society.
- Study the relationship with other sciences and interactions with society.
- Know the different stages of development processes.
- Ability to develop small prototyping projects in AI and DS.

Fundamentals of Chemistry

Q/BIOQ1001 - ECTS

The main objective of this course is to show the importance of Chemistry and its pervasive influence in other branches of Science. For that, fundamental topics will be addressed that allow students to understand the structure and properties of matter and to interpret the phenomena of chemical transformation.

Bioinformatics Laboratories

BIOINF1001 - ECTS The aim of this course is to provide students with an introduction to the techniques, tools and practical resources available for bioinformatics. Students should acquire skills for the selection and advanced use of the most appropriate tools to carry out research activities, including access to the main public sequence databases, advanced search and retrieval of gene expression datasets, differential expression analysis and enrichment functional, protein sequence alignment. Know open source repositories (e.g. CRAN, Bioconductor, GitHub), develop scripts and pipelines for automatic data processing using the Bash and Python programming languages, in particular the tools available in the BioPython modules. Students will also develop skills for a critical analysis of the results obtained, their validation and communication.

Programming II

CC1028 - ECTS

The purpose of this course is to develop the ability of using a programing language to develop complex programs and automatize practical tasks of data exploration, and to offer an introduction to  data extraction, processing, and visualization.

Databases

CC2005 - ECTS

Provide the students with the fundamentals and practice necessary for the design, implementation and analysis of relational databases. 

Data Structures

CC1007 - ECTS It is intended that the student reinforces his programmings skills, gets to know some of the main data structures and associated algorithms and gains basic knowledge on the conception and analysis of algorithms.

Formal and Population Genetics

BIOL2008 - ECTS

To provide students with basic concepts and methodologies in Formal and Population Genetics.

Microbiology

BIOL1006 - ECTS

The students are expected to acquire basic knowledge on general microbiology.

 

Practical classes are aimed to carry out selected experiments on basic general microbiology

 

 

Machine Learning I

CC2008 - ECTS

This course introduces Machine Learning (ML), providing students with a brief historical background and reference to some of its most relevant applications.

It is intended that students make first contact with various tasks and approaches involved in ML problems and that they can, in this way, identify the most appropriate strategies.

Machine Learning II

CC3043 - ECTS This UC consists of an introduction to some of the algorithmic foundations of deep and reinforcement learning.

It is intended that students have a first contact with such concepts and with concrete methods of implementing such algorithms.

They should be able to carefully select suitable algorithms and details of model architectures and learning techniques for each of the tasks presented.

They should know how to estimate the performance of the applied methods and use this information for iterative model design.

Web Technologies

CC3008 - ECTS

The goal of this curricular unit is to familiarize students with the concepts and technologies used in the development of web-centered applications. This includes learning about the different types of web applications, the different technologies that can be used to build them, and the best practices for designing and developing web applications.

Human Biology

BIOL2003 - ECTS

To provide students with basic knowledge on human origins and evolution and with a conceptual background allowing them to understand current patterns of genetic and biological diversity in human populations. Students will be introduced to a variety of analytical tools in anthropological research

Large Scale Data Science

CC3047 - ECTS Introduction to the use of cloud computing infrastructures for processing massive amounts of data ("big data") in real-world problems.

Evolution

BIOL3023 - ECTS The learning objective of this course in Evolution is to provide students with the basic knowledge of evolutionary biology so that they realize this is the leitmotif and unifier element of all biological sciences. In particular, it is expected that students become able to understand the evolutionary processes that led to the patterns of biological diversity as we presently know.

Computational Models

CC1004 - ECTS

Teach fundamental concepts and results about three computational models (finite automata, pushdown automata, Turing machines) and the related classes of formal languages, with emphasis on regular and context free languages.

Security and Privacy

CC2009 - ECTS This course unit has the goal of providing students with an integrated perspective of the security and privacy fundamentals; it targets to endow students with the principles of IT security and data privacy.
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