Autenticação

Utilizador:

Senha:

Iniciar sessão

Esqueceu-se da senha?

Modeling of Biological Processes

Code:

BINF029

Sigla:

MPB

Áreas Científicas
Classificação	Área Científica
OFICIAL	Biotecnologia

Ocorrência: 2022/2023 - 1S

Ativa?	Yes
Unidade Responsável:	Departamento de Engenharia Química e Biológica
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	26	Study Plan	3	-	5	60	135

Língua de trabalho

Portuguese

Objetivos

The goal of this UC is to provide knowledge about mathematical modeling used to simulate biological/biochemical systems from a kinetic and metabolic perspective. This mathematical interpretation stems from the systems biology, in which systems can be modeled through the use of differential equations encompassing not only kinetics and flows, but also regulation processes and compartmentalization. This UC also includes pharmacokinetic application models, which were introduced at the UC “Metabolism and Regulation”. Skills developed by students includes the bio-mathematical analysis of biological systems using computational tools and databases in the area of systems biology.

Resultados de aprendizagem e competências

-

Modo de trabalho

Presencial

Programa

1. Mathematical modelling of enzymatic reactions: enzyme kinetics; mechanisms of activation and inhibition;
mathematical modelling of one enzyme systems – mass and potency action laws, Henri-Michaelis-Menten law
2. Modelling metabolic networks I: description of metabolic and dynamic systems; analysis of metabolic control
systems; simulation by differential equations and analysis of metabolic fluxes; representation by graphs.
3. Modelling metabolic networks II: model reconstruction and integration of omics data with cell models.
4. Modelling metabolic networks III: single gene model and probabilistic model for prokaryotic genes; regulatory
models.
5. Modelling compartments I: flow and transporters
6. Modelling compartments II: pharmacokinetics and drug metabolism.

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	49,00
Frequência das aulas	45,00
Trabalho de investigação	20,00
Trabalho escrito	20,00
Total:	135,00

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.