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Modeling of Biological Processes

Code: BINF029     Sigla: MPB

Áreas Científicas
Classificação Área Científica
OFICIAL Biotecnologia

Ocorrência: 2021/2022 - 1S

Ativa? Yes
Unidade Responsável: Biotecnologia
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 23 Study Plan 3 - 5 60 135

Docência - Responsabilidades

Docente Responsabilidade
Sónia Alexandra Paiva dos Santos

Docência - Horas

Theorethical: 1,50
Practical and Laboratory: 2,00
Type Docente Turmas Horas
Theorethical Totais 1 1,50
Sónia Alexandra Paiva dos Santos 0,20
Rafael Sousa Costa 1,30
Practical and Laboratory Totais 1 2,00
Sónia Alexandra Paiva dos Santos 0,30
Rafael Sousa Costa 1,20

Língua de trabalho

Portuguese

Objetivos

This UC goal is to provide students with the mathematical skills to model and simulate biological/biochemical systems from a kinetic/metabolic perspective. This stems from the biochemical systems theory, in which biochemical systems can be modelled using differential equations, encompassing not only kinetics and flows but also regulation processes and compartmentation. This UC also includes models of pharmacokinetic origin.

Resultados de aprendizagem e competências

-

Modo de trabalho

Presencial

Programa

1. Modelling enzymatic reactions: enzyme kinetics; mechanisms of activation and inhibition; mathematical modelling of one enzyme systems – mass action laws, power laws and Henri-Michaelis-Menten law
2. Modelling metabolic networks I: using mass action laws and power laws to describe a 1-compartment metabolic system; system analysis under the framework of metabolic control analysis
3. Modelling metabolic networks II: understanding parallel alternative pathways and what triggers switching among them
4. Modelling metabolic networks III: the role of genes, single gene, probabilistic prokaryotic gene and eukaryotic cis-regulatory control modelling
5. Modelling metabolic networks IV: the case of drugs
6. Modelling compartments I: flow between compartments; transporters
7. Modelling compartments II: a basic overview of the cell as a multitude of communicating compartments; inter-compartment signalling as an approach to extracellular modelling
8. Modelling compartments III: pharmacokinetics

Bibliografia Obrigatória

Fell, D.; Understanding the Control of Metabolism (Frontiers in Metabolism)
Bower, J.M., Bolouri, H.; Computational Modeling of Genetic and Biochemical Networks
Britton, N.F.; Essential Mathematical Biology
Peters, S.A.; Physiologically-Based Pharmacokinetic (PBPK) Modeling and Simulations: Principles, Methods, and Applications in the Pharmaceutical Industry Hardcover,

Métodos de ensino e atividades de aprendizagem

Theoretical demonstrative lectures. Practical exercises class that will be focused on show-casing in a large number of simple examples the various mathematical models that arise in this area.
Students will develop two writen works that will give training on modeling and use of software. Work 1 is a mini-report with computational analysis of a metabolic model using relevant software in Metabolic Engineering. Work 2 is the critical analysis of a scientific article (replication of results in silico) based on a theme taught by the teacher.

Tipo de avaliação

Distributed evaluation with final exam

Componentes de Avaliação

Designation Peso (%)
Teste 70,00
Trabalho escrito 22,50
Apresentação/discussão de um trabalho científico 7,50
Total: 100,00

Componentes de Ocupação

Designation Tempo (Horas)
Apresentação/discussão de um trabalho científico 1,00
Estudo autónomo 47,00
Frequência das aulas 52,50
Trabalho de investigação 15,00
Trabalho escrito 20,00
Total: 135,50

Obtenção de frequência

Not applicable.

Fórmula de cálculo da classificação final

Continuous evaluation
Final classification = 35% Test 1 + 35% Test 2 + 15% Work 1 + 15% Work 2


Exam Period and Special Exam Period
100% Exam or
70% Exam + 15% Work 1 + 15% Work 2

- The delivery of Works 1 and 2 is mandatory during continuous assessment.
- Work 2 will be presented orally, in a group, and a student can be assigned a null classification if he does not present himself in his oral discussion, even if he has signed the work; Students in the same group may be given a different classification based on their commitment, the quality of their oral presentation and the mastery of the topic.
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