IV110 Project in Sequence Analysis
Faculty of InformaticsAutumn 2024
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
In-person direct teaching - Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
Mgr. Eva Budinská, Ph.D. (seminar tutor)
Mgr. Jan Kotrs (seminar tutor) - Guaranteed by
- doc. Ing. Matej Lexa, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Mon 23. 9. to Mon 16. 12. Mon 10:00–12:50 B410
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 36 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Learning outcomes
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- English
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bioinformatics project I
Faculty of InformaticsAutumn 2023
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
Mgr. Marie Krátká (seminar tutor)
Mgr. Eva Budinská, Ph.D. (seminar tutor)
Mgr. Vojtěch Bystrý, Ph.D. (seminar tutor) - Guaranteed by
- doc. Ing. Matej Lexa, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Mon 10:00–12:50 B410
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 74 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Learning outcomes
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bioinformatics project I
Faculty of InformaticsAutumn 2022
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
Mgr. Marie Krátká (seminar tutor) - Guaranteed by
- doc. Ing. Matej Lexa, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Mon 14:00–15:50 B410
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 74 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Learning outcomes
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bioinformatics project I
Faculty of InformaticsAutumn 2021
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- Mgr. Monika Čechová, Ph.D. (lecturer)
doc. Ing. Matej Lexa, Ph.D. (lecturer) - Guaranteed by
- doc. Ing. Matej Lexa, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Wed 15. 9. to Wed 8. 12. Wed 12:00–13:50 B204
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 74 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Learning outcomes
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2020
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- doc. Ing. Matej Lexa, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Tue 8:00–9:50 C511
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 74 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Learning outcomes
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2019
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- doc. Ing. Matej Lexa, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Thu 18:00–19:50 B204
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 74 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Learning outcomes
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2018
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Mon 17. 9. to Mon 10. 12. Mon 12:00–13:50 A319
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 37 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2017
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Tue 8:00–9:50 B411
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 37 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2016
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Mon 8:00–9:50 C525
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 37 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2015
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Wed 16:00–17:50 B411
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 37 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2014
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Thu 8:00–9:50 C416
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 36 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2013
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Fri 10:00–11:50 G330
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 36 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2012
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
doc. RNDr. Radka Svobodová, Ph.D. (seminar tutor) - Guaranteed by
- prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Tue 12:00–13:50 B411
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 36 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2011
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
doc. RNDr. Radka Svobodová, Ph.D. (seminar tutor) - Guaranteed by
- prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Tue 10:00–11:50 B411
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2010
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
doc. RNDr. Radka Svobodová, Ph.D. (seminar tutor) - Guaranteed by
- prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Tue 8:00–9:50 B410
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2009
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Wed 8:00–9:50 B411
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 45 fields of study the course is directly associated with, display
- Course objectives
- In this course the students will:
be able to select appropriate bioinformatic tools for a given problem
be able to carry out independent analysis of bioinformatic data
present their results to their colleagues - Syllabus
- Discussion of interesting problems to solve
- Preparation of student proposals
- Programming phase
- Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student projects, their presentation and class discussion
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2008
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Wed 8:00–9:50 B204
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 38 fields of study the course is directly associated with, display
- Course objectives
- Upon inspection of suggested subjects and a period of discussion, the students will select an appropriate bioinformatic problem to solve on a computer. They will present the results of their work in a student mini conference either in the form of a poster or an oral presentation with software demonstration. IV110 is primarily for Bc. students. The rules for MSc. degree bioinformatics require registration in IV114. The two courses currently meet together, but the project difficulty may be higher in IV114. At the end of the course, the student will become familiar with computational tools used in bioinformatics. He/she will be able to carry out independent analysis of bioinformatic data.
- Syllabus
- - Discussion of interesting problems to solve - Preparation of student proposals - Programming phase - Student mini-conference
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Assessment methods
- writen project proposal and summary of results, oral presentation
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2007
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Thu 8:00–9:50 B411
- Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 38 fields of study the course is directly associated with, display
- Course objectives
- Upon inspection of suggested subjects and a period of discussion, the students will select an appropriate bioinformatic problem to solve on a computer. They will present the results of their work in a student mini conference either in the form of a poster or an oral presentation with software demonstration. IV110 is primarily for Bc. students. The rules for MSc. degree bioinformatics require registration in IV114. The two courses currently meet together, but the project difficulty may be higher in IV114.
- Syllabus
- - Interesting problems to solve - Preparation of student proposals - Programming phase - Student mini-conference
- Assessment methods (in Czech)
- Student bude hodnocen na základě písemného návrhu projektu (1-2 strany A4) a závěrečné prezentace dle pravidel, které budou upřesněny na začátku semestru.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually.
IV110 Bionformatics project I
Faculty of InformaticsAutumn 2006
The course is not taught in Autumn 2006
- Extent and Intensity
- 1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics - Prerequisites
- IV107 Bioinformatics I plus elementary programming skills (e.g. UNIX + C/C++/Java + Perl/Python) or teacher's consent
- 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 18 fields of study the course is directly associated with, display
- Course objectives
- Upon inspection of suggested subjects and a period of discussion, the students will select an appropriate bioinformatic problem to solve on a computer. They will present the results of their work in a student mini conference either in the form of a poster or an oral presentation with software demonstration.
- Syllabus
- - Interesting problems to solve - Preparation of student proposals - Programming phase - Student mini-conference
- Assessment methods (in Czech)
- Student bude hodnocen na základě písemného návrhu projektu (1-2 strany A4) a závěrečné prezentace dle pravidel, které budou upřesněny na začátku semestru.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- The course is taught annually.
The course is taught: every week.
- Enrolment Statistics (recent)