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Computational Genomics

Code: BIOINF3002     Acronym: BIOINF3002

Instance: 2025/2026 - 2S Ícone do Moodle

Active? Yes
Responsible unit: Department of Biology
Course/CS Responsible: Bachelor in Bioinformatics

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
L:BIOINF 23 Official Study Plan 3 - 6 48 162

Teaching Staff - Responsibilities

Teacher Responsibility
Agostinho Antunes Pereira

Teaching - Hours

Theoretical classes: 1,85
Laboratory Practice: 1,85
Type Teacher Classes Hour
Theoretical classes Totals 1 1,846
Agostinho Antunes Pereira 0,615
José Fernando Melo Ferreira 0,461
Luís Filipe Costa de Castro 0,461
Laboratory Practice Totals 1 1,846
José Fernando Melo Ferreira 0,461

Teaching language

Suitable for English-speaking students

Objectives








This UC meets the most recent tools used in the global study of genomics, providing the student with a transversal and integrative view to understand the different degrees of organization of the eukaryotic cell/organism. The student's goals are:


 


• Master the fundamentals of the main methods/concepts used in genomics, including the integration of data from various omics (eg, genomics / transcriptomics / epigenomics / proteomics/ pangenomics) and respective methodologies and instrumental bases of analysis.


• Learn about methodologies associated with the acquisition of multiparametric data and bioinformatics-based tools to explore the different levels of omics under study, assisting in the decoding of eukaryotic genomes, and implementing software commonly used.


• Develop elementary knowledge and skills in an open source Unix-like operating system (Linux) and its application in genome analysis. Use of language and code programming (e.g., Python), in the context of biological research.


• Consider the potential of integrating these genomic/omic datasets into biological inference strategies.


• Understand, for each omic level, the applications in the context of Biology and Biomedicine.

Learning outcomes and competences

Acquisition of knowledge incorporating current topics at the various levels of genomics and other omics (general concepts, tools and applications) in eukaryotic models. The learning process is envisaged in a pyramid of functional/organistic complexity, giving the student an integrative view from the gene to the cell/tissue/organism (on an evolutionary scale and considering phylogenetic molecular clocks). The skills integrate areas of biology, biochemistry, biomedicine and bioinformatics, providing different omics methodologies for exploration by the student, applied alone or together to a biological problem. Scientific knowledge is integrated, reflecting the experience, pedagogical and scientific knowledge of the teachers involved in teaching this UC. The syllabus provides the student with a solid set of knowledge/skills in an integrative view of the potential of genomics to respond to problems in Biology, Health, Environment, etc.

Working method

Presencial

Program

Genomics: DNA analysis, cloning, sequencing, assemblage and annotation of genomes; Sequencing: structural and functional analysis of genes. Sequence analysis and RNA research; Expression of Genes in cDNA Libraries; Expression by RT-PCR and RNAseq. Integration of inferences from genomics, transcriptomics, epigenomics. Functional genomics, relevance of proteomics and proteogenomics. Importance of non-covalent interactions in biological systems. Properties and molecular structure of amino acids and proteins. Conformational freedom. Structure/Function relationship. In-silico algorithms for protein structural prediction and visualization/manipulation of 3D models. Computational languages in the context of biological research (e.g. Python and R). Use of nucleotides (genomes) and amino acids (proteins, PDB structures) databases. Cytomics: image/flow cytometry. Principle and applications. Sample processing; multiparametric analysis. Eukaryotic models. Chromosomal changes. Single cell genomics. Pangenomics - related lineages.

Mandatory literature

JC Setubal, PF Stadler, J Stoye; Comparative Genomics: Methods and Protocols, Humana New York, NY, 2024. ISBN: https://doi.org/10.1007/978-1-0716-3838-5
Jonathan Pevsner ; Bioinformatics and Functional Genomics, Wiley-Blackwell, 2015. ISBN: 978-1-118-58178-0
Debmalya Barh and Vasudeo Zambare ; OMICS: Applications in Biomedical, Agricultural, and Environmental Sciences., CRC Press Taylors & Francis Group, 2013. ISBN: 9781466562813
Bernd Mayer ; Bioinformatics for Omics Data: Methods and Protocols (Methods in Molecular Biology), Springer, 2011. ISBN: ISBN 978-1-61779-027-0

Teaching methods and learning activities

Theoretical classes and theoretical-practical classes.

Theoretical classes, of an expository nature, will be presented by projection of slides in “Powerpoint”, in combination with Problem-Based Learning (PBL) approaches. Whenever relevant, lectures will be promoted by key researchers in the area of genomics and other omics.

Theoretical-practical classes allow the acquisition of specific skills, namely those resulting from the execution of experimental work (e.g., laboratory, use of multiparametric data processing programs, biostatistics and in-silico analysis), preparation and presentation of oral communications and discussion of scientific articles in the area, whose appreciation will be evaluated. Study visits to centers of excellence in the field of omics. Theoretical-practical classes are mandatory.

Evaluation Type

Evaluation with final exam

Assessment Components

designation Weight (%)
Teste 100,00
Total: 100,00

Amount of time allocated to each course unit

designation Time (hours)
Frequência das aulas 48,00
Total: 48,00

Eligibility for exams

Presence in at least 2/3 of practical classes.

Calculation formula of final grade

The evaluation will consist in making a final exam.

EXAM: consists of a theoretical part (12 points) and a practical one (8 points).

For the exam it is required a minimum of thirty percent in each of the parts of the examination (theoretical and practical).

The approval at the UC is obtained with a final classification equal to or greater than 9.5 values.

Special assessment (TE, DA, ...)

Students who are legally exempt from course contact hours will take a special in-person test to assess their mastery of course skills and syllabus. Students should contact the instructor at the beginning of the semester to do so.

Classification improvement

Using the subsequent examination seasons, according to the Faculty general regulations.

Observations

Contact Professor: Agostinho Antunes
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