Systems Oncology: bioinformatics and computer modelling in cancer (OncoSys_f_Eng)2.5 ECTS
(englische Bezeichnung: Systems Oncology: bioinformatics and computer modelling in cancer)
(Prüfungsordnungsmodul: Introduction to simulation, network and data analysis in cancer and oncotherapy)

Lehrveranstaltungen:

• • Systems Oncology: bioinformatics and computer modelling in cancer
    (Vorlesung, 3 SWS, Julio Vera-Gonzalez, Bitte erfragen Sie den Veranstaltungsort bei Prof. Dr. Julio Vera-Gonzalez: julio.vera-gonzalez@uk-erlangen.de)

Inhalt:

In Cancer Systems Biology quantitative biomedical data from experimental models and patients are investigated using advanced data analysis and computational modelling and simulation of molecular and cell-to-cell interaction networks. The aim is to detect processes deregulated in cancer for understanding their role in cancer progression and development, support cancer drug discovery and personalized treatments.
In this lectures series we introduce the basics of bioinformatics and computational modelling in Cancer Systems Biology, and its integration with data and network analysis. The lectures have practical sessions on computer modelling and simulation of cancer.
Topics included are:

• Foundations of Cancer Biology
  

• Basics of Cancer Bioinformatics and Systems Biology
  

• High throughput data analysis, integration, and mining in cancer
  

• Computational model calibration, simulation and analysis
  

• ODE models of cancer networks
  

• Boolean models of cancer networks
  

• Multi-level modelling in cancer
  

• Tumor growth models
  

• Pharmacokinetics and pharmacodynamics models in cancer
  

• Tumor epitopes detection and analysis

Lernziele und Kompetenzen:

The students:

• Learn computational workflows for bioinformatics and computational modelling applied to cancer
  

• Derive, calibrate, and analyze computational models
  

• Learn methods for making model-based inferences in cancer networks
  

• Derive, calibrate, and simulate computational models for cancer networks, tumor growth models and pharmacokinetics/pharmacodynamics models
  

• Understand the potential of computational modelling of cancer networks in anticancer therapy discovery
  

Verwendbarkeit des Moduls / Einpassung in den Musterstudienplan:

1. Data Science (Master of Science)
   (Po-Vers. 2021w | Gesamtkonto | Anwendungsfächer | Medical Data Science | Introduction to simulation, network and data analysis in cancer and oncotherapy)

Studien-/Prüfungsleistungen:

Introduction to simulation, network and data analysis in cancer and oncotherapy (Prüfungsnummer: 845913)

(englischer Titel: Introduction to simulation, network and data analysis in cancer and oncotherapy)

Prüfungsleistung, mündliche Prüfung, Dauer (in Minuten): 30, benotet, 2.5 ECTS

Anteil an der Berechnung der Modulnote: 100.0 %

Erstablegung: SS 2022, 1. Wdh.: WS 2022/2023

1. Prüfer:

Julio Vera-Gonzalez