PA183 Project in Systems Biology

Faculty of Informatics
Autumn 2024
Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 26. 9. to Thu 19. 12. Thu 14:00–15:50 A418
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 29 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Learning outcomes
At the end of the course students should be able to:
use public databases of biological knowledge;
construct an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
infer hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.

PA183 Project in Systems Biology

Faculty of Informatics
Autumn 2023
Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
RNDr. Matej Troják, Ph.D. (assistant)
Guaranteed by
doc. RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 10:00–11:50 A418
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 70 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Learning outcomes
At the end of the course students should be able to:
use public databases of biological knowledge;
construct an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
infer hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Autumn 2022
Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
RNDr. Matej Troják, Ph.D. (assistant)
Guaranteed by
doc. RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 12:00–13:50 A418
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 70 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Learning outcomes
At the end of the course students should be able to:
use public databases of biological knowledge;
construct an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
infer hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Autumn 2021
Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
RNDr. Matej Troják, Ph.D. (assistant)
Guaranteed by
doc. RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 16. 9. to Thu 9. 12. Thu 10:00–11:50 A418
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 69 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Learning outcomes
At the end of the course students should be able to:
use public databases of biological knowledge;
construct an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
infer hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Autumn 2020
Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
RNDr. Matej Troják, Ph.D. (assistant)
Guaranteed by
doc. RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 12:00–13:50 A418
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 69 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Learning outcomes
At the end of the course students should be able to:
use public databases of biological knowledge;
construct an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
infer hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Autumn 2019
Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
RNDr. Matej Troják, Ph.D. (assistant)
Guaranteed by
doc. RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 16:00–17:50 A418
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 69 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Learning outcomes
At the end of the course students should be able to:
use public databases of biological knowledge;
construct an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
infer hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught last offered.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Autumn 2018
Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
RNDr. Matej Troják, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 40 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Learning outcomes
At the end of the course students should be able to:
use public databases of biological knowledge;
construct an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
infer hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is taught every week.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Autumn 2017
Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
RNDr. Matej Troják, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Mon 17:00–19:50 A418
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 40 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Learning outcomes
At the end of the course students should be able to:
use public databases of biological knowledge;
construct an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
infer hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Autumn 2016
Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
RNDr. Matej Troják, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable of Seminar Groups
PA183/OS01: Thu 14:00–16:50 A418, D. Šafránek
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 40 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Autumn 2015
Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable of Seminar Groups
PA183/OS01: Thu 16:00–17:50 A418, D. Šafránek
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 40 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Autumn 2014
Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable of Seminar Groups
PA183/OS01: Wed 16:00–17:50 A418, D. Šafránek
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 39 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Autumn 2013
Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable of Seminar Groups
PA183/OS01: Thu 16:00–17:50 C516, D. Šafránek
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 39 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Autumn 2012
Extent and Intensity
2/0/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Fri 12:00–13:50 C516
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 42 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Spring 2012
Extent and Intensity
2/0/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 16:00–17:40 C516
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 42 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Spring 2011
Extent and Intensity
2/0/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Timetable
Fri 12:00–13:50 C518
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 40 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Spring 2010
Extent and Intensity
2/0/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Timetable
Fri 12:00–13:50 B411
Prerequisites
The subject expects knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous study of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data in terms of developing a relevant in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 40 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Spring 2023

The course is not taught in Spring 2023

Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
RNDr. Matej Troják, Ph.D. (assistant)
Guaranteed by
doc. RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 69 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Learning outcomes
At the end of the course students should be able to:
use public databases of biological knowledge;
construct an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
infer hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught every week.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Spring 2022

The course is not taught in Spring 2022

Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
RNDr. Matej Troják, Ph.D. (assistant)
Guaranteed by
doc. RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 69 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Learning outcomes
At the end of the course students should be able to:
use public databases of biological knowledge;
construct an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
infer hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught every week.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Spring 2021

The course is not taught in Spring 2021

Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
RNDr. Matej Troják, Ph.D. (assistant)
Guaranteed by
doc. RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 69 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Learning outcomes
At the end of the course students should be able to:
use public databases of biological knowledge;
construct an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
infer hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught every week.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.

PA183 Project in Systems Biology

Faculty of Informatics
Spring 2020

The course is not taught in Spring 2020

Extent and Intensity
0/0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
RNDr. Matej Troják, Ph.D. (assistant)
Guaranteed by
doc. RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Prerequisites
The subject requires knowledge of elementary modeling and simulation methods for biological systems dynamics. Previous undertaking of the related subjects PB050 and PA054 is welcome, but not necessary. Students who finished laboratory exercises of PV225 can use the obtained data for development of a related in silico model.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 69 fields of study the course is directly associated with, display
Course objectives
At the end of the course students should be able to:
search in public databases of biological knowledge;
create an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
predict hypotheses regarding emergent properties of the modeled biological system.
Learning outcomes
At the end of the course students should be able to:
use public databases of biological knowledge;
construct an in silico model of a biological system;
apply methods of computational systems biology to model analysis;
infer hypotheses regarding emergent properties of the modeled biological system.
Syllabus
  • Overview of key notions
  • Setting of project topics
  • Project realization
  • Final student presentation
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
    not specified
  • KLIPP, Edda. Systems biology : a textbook. Weinheim: Wiley-VCH Verlag, 2009, xxi, 569. ISBN 9783527318742. info
  • VRIES, Gerda de. A course in mathematical biology : quantitative modeling with mathematical and computational methods. Philadelphia: Society for Industrial and Applied Mathematics, 2006, xii, 309. ISBN 0898716128. info
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
Teaching methods
Group projects, student presentations. Discussions.
Assessment methods
final report of the group project (2 pages A4), oral presentation of the results
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught every week.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
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