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Programming Applied to Bioinformatics

Code: BINF031     Sigla: PAB     Level: 1

Áreas Científicas
Classificação Área Científica
OFICIAL Informática

Ocorrência: 2022/2023 - 1S

Ativa? Yes
Página Web: https://stuntspt.gitlab.io/pab_22-23/
Unidade Responsável: Departamento de Matemática e Informática
Curso/CE Responsável: Undergraduate in Bioinformatics

Ciclos de Estudo/Cursos

Sigla Nº de Estudantes Plano de Estudos Anos Curriculares Créditos UCN Créditos ECTS Horas de Contacto Horas Totais
BINF 42 Study Plan 1 - 5 60 135

Docência - Responsabilidades

Docente Responsabilidade
Alberto Fernandes de Oliveira Junior

Docência - Horas

Theorethical and Practical : 1,50
Practical and Laboratory: 2,00
Type Docente Turmas Horas
Theorethical and Practical Totais 1 1,50
Francisco Rente de Pina Martins 1,50
Practical and Laboratory Totais 2 4,00
Francisco Rente de Pina Martins 4,00
Mais informaçõesA ficha foi alterada no dia 2022-11-25.

Campos alterados: Componentes de Avaliação e Ocupação, Fórmula de cálculo da classificação final

Língua de trabalho

Portuguese
Obs.: Slides em Inglês

Objetivos

The curricular unit “Programming Applied to Bioinformatics” aims to convey the notion of algorithms as the formalization of a solution to a well-defined problem in a sequence of elementary actions. At the end, the student should be able to: analyze a given algorithm and predict the final result of its execution; design algorithms in natural language and pseudo-code; Understand and know: computer programming as a way of describing algorithms in a formal language that can be executed on a general-purpose computer; elementary principles of programming: variables; decision instructions; cycle instructions; lists and arrays; the traditional computer program development cycle: design, programming and testing. Apply knowledge of these basic principles to an appropriate programming language; be able to translate a given algorithm into a complete program; be able to solve a given problem by designing, programming and testing it.

Resultados de aprendizagem e competências

By the end of the CU students should be able to read, understand and write code in the "Python" language, as well as be able to design and implement simple programming tasks with application in bioinformatics

Modo de trabalho

Presencial

Pré-requisitos (conhecimentos prévios) e co-requisitos (conhecimentos simultâneos)

Not applicable

Programa

The general purpose computer and its components;
Characteristics of different programming languages ​– historical perspective.
Introduction to programming language paradigms
Elements of programming languages: Elementary type variables. Expressions and attribution of values. Instruction
execution flow. Decision instructions. Cycle instructions.
Use of functions
Use of external libraries
Data input and output
Introduction to software development: Application design. Programming techniques. Program testing

Bibliografia Obrigatória

Model, M.L.; Bioinformatics Programming Using Python: Practical Programming for Biological Data, O'Reilly Media, 2010. ISBN: 978-0-596-15450-9
Jones, N.C., Pevzner, P.A.; An Introduction to Bioinformatics Algorithms (Computational Molecular Biology), The MIT Press, 2004. ISBN: 978-0-262-10106-6
Lubanovic, B; Introducing Python: Modern computing in simple packages (First edition), O’Reilly Media, 2014. ISBN: 978-1449359362
Downey, A. ; Think Python (2nd edition, updated for Python 3), O’Reilly Media, 2016. ISBN: 978-1491939369

Métodos de ensino e atividades de aprendizagem

1. 1.5 theoretical hours per week to expose the concepts and demonstrate their application with examples, in order
to familiarize students with programming in bioinformatics.
2. 2 h weekly practices organized for students to self-develop the appropriate code in order to obtain a number of
functional scripts per class.

Software

Python 3.X

Palavras Chave

Technological sciences > Technology > Information technology
Natural sciences > Biological sciences > Biology > Computational biology

Tipo de avaliação

Distributed evaluation with final exam

Componentes de Avaliação

Designation Peso (%)
Participação presencial 20,00
Teste 40,00
Trabalho escrito 40,00
Total: 100,00

Componentes de Ocupação

Designation Tempo (Horas)
Estudo autónomo 39,50
Frequência das aulas 56,00
Trabalho escrito 39,50
Total: 135,00

Obtenção de frequência

Classroom participation, delivery of two written assignments (programs) and performing a writen evaluation test.

Fórmula de cálculo da classificação final

Assignment 1 (20%) + Assignment 2 (20%) + Evaluation test (40%) + Classroom context (20%).
Alternatively: 100% written exam.
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