Acquire the basic knowledge of biological systems and problems related to their understanding, also in relation to deviations from normal functioning and thus to the insurgence of pathologies. Take care of the modeling aspect as well as of numerical simulation, especially for problems formulated by means of equations and discrete systems. Acquire the knowledge of the major bio-informatics algorithms useful to analyze biological data
Curriculum
teacher profile teaching materials
• Mathematical Biology, J.D. Murray (Population models - Epidemic models)
• Population Ecologies: First Principles Deborah Goldberg and John H.Vandermeer
(Simple population models, CAP1)
• Non Linear Dynamics and Chaos, S. Strogatz (Stability of dynamical systems)
• Computational Physics, M. Newman (Euler and RK methods)
• Networks, M. Newman (ER and CM random graphs, Epidemics on Networks)
• Understanding Bioinformatics, Marketa Zvelebil & Jeremy O. Baum
• Biological sequence analysis, R. Durbin et al. (CAP 1,2,6,7)
• Bioinformatics Algorithms: an Active Learning Approach, Pavel A. Pevzner and Phillip Compeau
• Bioinformatics - an Introduction, Jeremy Ramsden
• Understanding Bioinformatics, Marketa Zvelebil, Jeremy O. Baum
• Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids
• Statistical Methods in Bioinformatics, An Introduction, Warren J. Ewens , Gregory Grant
Mutuazione: 20410568 IN470 - METODI COMPUTAZIONALI PER LA BIOLOGIA in Scienze Computazionali LM-40 Mastrostefano Enrico
Core Documentation
• Python:https://github.com/steguar/DAIL/blob/main/Lecture_1/Lecture_1_Python_crash_ course.ipynb• Mathematical Biology, J.D. Murray (Population models - Epidemic models)
• Population Ecologies: First Principles Deborah Goldberg and John H.Vandermeer
(Simple population models, CAP1)
• Non Linear Dynamics and Chaos, S. Strogatz (Stability of dynamical systems)
• Computational Physics, M. Newman (Euler and RK methods)
• Networks, M. Newman (ER and CM random graphs, Epidemics on Networks)
• Understanding Bioinformatics, Marketa Zvelebil & Jeremy O. Baum
• Biological sequence analysis, R. Durbin et al. (CAP 1,2,6,7)
• Bioinformatics Algorithms: an Active Learning Approach, Pavel A. Pevzner and Phillip Compeau
• Bioinformatics - an Introduction, Jeremy Ramsden
• Understanding Bioinformatics, Marketa Zvelebil, Jeremy O. Baum
• Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids
• Statistical Methods in Bioinformatics, An Introduction, Warren J. Ewens , Gregory Grant
teacher profile teaching materials
• Mathematical Biology, J.D. Murray (Population models - Epidemic models)
• Population Ecologies: First Principles Deborah Goldberg and John H.Vandermeer
(Simple population models, CAP1)
• Non Linear Dynamics and Chaos, S. Strogatz (Stability of dynamical systems)
• Computational Physics, M. Newman (Euler and RK methods)
• Networks, M. Newman (ER and CM random graphs, Epidemics on Networks)
• Understanding Bioinformatics, Marketa Zvelebil & Jeremy O. Baum
• Biological sequence analysis, R. Durbin et al. (CAP 1,2,6,7)
• Bioinformatics Algorithms: an Active Learning Approach, Pavel A. Pevzner and Phillip Compeau
• Bioinformatics - an Introduction, Jeremy Ramsden
• Understanding Bioinformatics, Marketa Zvelebil, Jeremy O. Baum
• Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids
• Statistical Methods in Bioinformatics, An Introduction, Warren J. Ewens , Gregory Grant
Mutuazione: 20410568 IN470 - METODI COMPUTAZIONALI PER LA BIOLOGIA in Scienze Computazionali LM-40 Mastrostefano Enrico
Core Documentation
• Python:https://github.com/steguar/DAIL/blob/main/Lecture_1/Lecture_1_Python_crash_ course.ipynb• Mathematical Biology, J.D. Murray (Population models - Epidemic models)
• Population Ecologies: First Principles Deborah Goldberg and John H.Vandermeer
(Simple population models, CAP1)
• Non Linear Dynamics and Chaos, S. Strogatz (Stability of dynamical systems)
• Computational Physics, M. Newman (Euler and RK methods)
• Networks, M. Newman (ER and CM random graphs, Epidemics on Networks)
• Understanding Bioinformatics, Marketa Zvelebil & Jeremy O. Baum
• Biological sequence analysis, R. Durbin et al. (CAP 1,2,6,7)
• Bioinformatics Algorithms: an Active Learning Approach, Pavel A. Pevzner and Phillip Compeau
• Bioinformatics - an Introduction, Jeremy Ramsden
• Understanding Bioinformatics, Marketa Zvelebil, Jeremy O. Baum
• Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids
• Statistical Methods in Bioinformatics, An Introduction, Warren J. Ewens , Gregory Grant