Q4034 - ECTS

The aim of this course is to give to the student a broad view of the Computational Biochemistry field. The course will focus on molecular dynamics of biological macromolecules. The students will learn to prepare, execute and analyse molecular dynamics simulations of biomolecules

M4091 - ECTS

It is expected that at the end of the course the students will attain knowledge on:

a)     a) data collection

b)    b)  most used statistical models in the context of Science and Engineering, 

           including its application with the free software R/SPSS

c)     c) the choice of the statistical model given different contexts

d)     d) the interpretation of the results obtained by the application of the learnt methods.

BIOL4026 - ECTS

Students should acquire basic knowledge in the field of Molecular Biology and develop the necessary skills for the execution, analysis and interpretation of results derived from the use of Molecular Biology and Bioinformatics techniques.

CC4060 - ECTS Students will obtain a global perspective on the different steps of a Data Science project. For each of these steps, some of the main techniques and methods will be presented while further details will be addressed in more specific courses.

CC4042 - ECTS Introduction to programming using the Python language. Values, types and expressions. Functions and procedures. Conditionals and selection. Iteration and recursion. Basic data structures and algorithms: data processing, text.
Scientific programming with python.

Database modelling using the entity/relationship model.
Relational database implementaion with SQL. Database queries using the SQL language.

BIOL4029 - ECTS The aim of this course is to equip graduate students with advanced knowledge on NGS data analysis through bioinformatics and computational biology, both from a theoretical and practical point of view. The course is specially designed to help students interested in developing their careers in new sequencing technologies to solve biological problems related to proteins, genes, genomes and their interactions.

CC4047 - ECTS

COVID-19: Online Teaching Activities
Due to this situation the evaluation criteria has been changed. Check the new criteria below.

Bioinformatics is an interdisciplinary field that combines the fields of computer science, biology and biomedical science and statistics. Bioinformatics is devoted to the application and development of new computational methods for expanding the use of biological, biomedical or epidemiological data. Recent developments in high-throughput technologies have led to a real revolution in the biological and biomedical research with bioinformatics playing a central role in the analysis of massive amounts of data. This course will focus on the main algorithms developed to address Bioinformatics tasks. An emphasis will be made on algorithms for sequence processing and analysis, both on nucleic-acids or amino-acid sequences.

Our goal is that students will be able to understand how these algorithms work and how this can be developed and applied to address new computational tasks in biological sequence analysis.

BIOL4035 - ECTS

1. Consolidate knowledge on the bases of genetic diversity and the factors that influence its population distribution
2. Mastering the methods and techniques of genetics applied in forensic expertise, from those used in laboratory routine to those necessary for the interpretation of results
3. Have a comprehensive overview on the situations involving identification, kinship and taxonomy issues, in samples either of human origin or from other species, and achieve the skills needed to deal with common and complex cases encountered in forensic casework
4. Understand the limits of the genetic contribution to answer to the problems posed in different investigations and comprehend the role of the expert in those investigations

M4094 - ECTS

The course presents the main concepts and techniques of digital image processing and analysis. The main goal is that in the end of the course the students will be able to plan and implement algorithms for information extraction from images.

The course orientation focus on the understanding of concepts and methods, and its effective use in synthetic and experimental data analysis. The course makes an extensive use of advance computational tools (MATLAB).

B4002 - ECTS

Introduction and training in bioinformatics tools focusing on the user's standpoint. Case-studies in the context of ongoing research projects.

CC4062 - ECTS

Q4100 - ECTS The main objective of the lectures is to provide a broad overview of Molecular Bioinformatics.
In the practical classes the students will develop small research projects.

BIOL4067 - ECTS

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.

CC4063 - ECTS

Networks are a fundamental tool for modeling complex social, technological, and biological systems. Having into account the emergeng o large scale network data, this course focuses on the analysis of these networks, which provide multiple computational, algorithmic, and modeling challenges. The course will cover recent research on the structure and analysis of such networks, as well as models and algorithms that abstract their main properties.

CC4064 - ECTS

Students should be able to use the fundamental data structures and associated basic algorithms, illustrating their application through the two most widely used programming languages for Bioinformatics (Python). Concepts of object-oriented programming will be introduced as well as some more common strategies in more advanced algorithms in bioinformatics.

B4024 - ECTS

The students should understand key concepts in molecular evolution and integrate this knowledge towards the development of working hypothesis to explain specific scientific questions. In addition the students should acquire the know-how to choose the most adequate methodologies to validate or refuse the different evolutionary hypotheses.

BIOL4053 - ECTS 1. Understanding the usefulness and the limitations of ecological models in the analysis of modern environmental problems.

2. Understanding the steps in the construction of ecological models, and identifying the main data types and sources in ecological modeling.

3. Conceptualizing, calibrating, evaluating and spatializing ecological models for specific applications.

4. Implementing scenarios of environmental change and interpreting the predictions of models on ecological grounds.

CC4061 - ECTS Identification and application of data mining techniques to extract knowledge from different data sources (e.g. text, web).

CC4022 - ECTS This course is centered on the synergies in the association of machine learning / deep learning, logic, statistucs and search / optimization methods. Based on the latest developments on search, deep learning, and reinforcement learning; these methods are considered to provide computers with quasi-human-level performance. The aim is to allow useful available information to be efficiently extracted from massive data sets (machine learning) and turned into actionable decisions (operations). Applications range from computer vision and speech recognition to high-level decision support systems, including human health, transportation and logistics, commerce and information services, and energy networks.

The course will deepen competences acquired in "Algorithm Design and Analysis" and in "Artificial Intelligence".

BIOL4032 - ECTS

The course aims to give students an understanding of the importance of phylogenetics for systematics, comparative biology, biomedical issues and conservation planning. Widely used methodologies are discussed and compared, along with the relative philosophies behind each method. 

CC4014 - ECTS

Introduce the students to advanced concepts on the theory and practice of computational models for parallel and distributed memory architectures. Hands-on experience on programming distributed memory architectures with MPI, and programming shared memory architectures using processes, threads and OpenMP.

BIOL4034 - ECTS

To understand the use of genetics in forensics.
To master the communication of information between the court and the experts.
To understand and evaluate the ethical and professional deontology in forensic expertise.

BIOL4031 - ECTS

The main objective of the course is to provide students a deep understanding of the use of molecular tools in the study and comprehension of biological diversity. Complementing the different theoretical aspects related with the development, measurement and analysis of molecular markers a special effort will be dedicated to the contact with diverse laboratory techniques and analytical tools related with molecular data, with special emphasis on the DNA and RNA level.

M4116 - ECTS

This course aims to give an overview of the various methods of mathematical modeling in Systems Biology.

The systems approach to biology is a new methodological paradigm that transformed research in biology in the 21st century. The key idea is that we can study the interactions of all components of a biological system to reveal their emergent properties. Recently won a new impact, mainly due to the remarkable progress of experimental and computational methods (Bioinformatics), ever more ingenious and powerful. It is supported accumulated in biological knowledge, more detailed, the creation of new experimental techniques in genomics and proteomics, new technologies to make extensive measurements DNA sequence, expression and regulation of genes, protein-protein interactions, modeling tradition math biological processes and the exponential growth of Bioinformatics (as a prerequisite for the construction of huge databases and analysis of large-scale systems).

Biology has become increasingly multidisciplinary with biologists, computer scientists, engineers, mathematicians, physicists and doctors, to join efforts to develop high-efficiency technologies and computational and mathematical tools, guided by current needs of biology and medicine.

BINF/BC5000 - ECTS The students are challenged to develop a research proposal in a subject framed within the field of Bioinformatics and Computational Biology supervised by researchers of Mathematics or Computer Science and Biology or Biochemistry.

CC4016 - ECTS This module will present generic computer vision topics to the students, namely: image capturing technology, core image and video processing algorithms, basic pattern recognition algorithms, computer vision application fields.

CC4056 - ECTS

This course will introduce the concepts of Data Visualization with a focus on Data Science and Visual Analytics. It spans over a multi-disciplinary domain that combines data visualization with machine learning and their automated techniques to help people make sense of data.

Students will be introduced to the design of visual representations that support tasks that take the user from raw data into insights. Topics include basic concepts of information visualization; visual analytics of evolving phenomena; analysis of spatial and temporal data sets; visual social media analytics; and the visual analytics of text and multimedia collections.

Students will prototype visual analytics applications using existing frameworks and libraries, coupling machine learning and visualization methods. Students will gain competency in performing data analysis through visualization tasks in different application domains.

In particular:

• Create graphs appropriate to the type of context and problem to be explored
• Create and enhance graphics using R and Python tools
• Integrate graphics developed in R / Python into interactive environments.
• Design and develop a Big Data access dashboard for interactive manipulation of multiple graphs.

BINF/BC5001 - ECTS

A master's degree Dissertation in Bioinformatics or Computational Biology should preferably consist of original research carried out by the student on a topic that might contribute to enhance knowledge in Bioinformatics or Biology Computational.