Course Information

IV110 Project in Sequence Analysis

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)
Mgr. Pavla Holochová, 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 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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bioinformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bioinformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bioinformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II
• IV116 Applied bioinformatics: The Evolutionary relationships of genes and species

Further Comments

Study Materials
The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II

Further Comments

The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II

Further Comments

Study Materials
The course is taught annually.

IV110 Bionformatics project I

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

• IV105 Bionformatics seminar
• IV106 Bioinformatics seminar
• IV108 Bioinformatics II

Further Comments

The course is taught annually.
The course is taught: every week.

• Enrolment Statistics (recent)