Programming in Bioinformatics
Code:
53272
ECTS:
2.0
Lecturers in charge:
izv. prof. dr. sc.
Janko Diminić
Lecturers:
izv. prof. dr. sc.
Janko Diminić
- Seminar
izv. prof. dr. sc. Janko Diminić - Practicum
prof. dr. sc. Antonio Starčević - Lectures
izv. prof. dr. sc. Janko Diminić - Practicum
prof. dr. sc. Antonio Starčević - Lectures
Take exam:
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1. komponenta
| Lecture type | Total |
|---|---|
| Lectures | 10 |
| Seminar | 5 |
| Practicum | 10 |
Description:
Goals
Through this course, students should become familiar with Java programming language. Skills adopted in this course should enable them to solve basic bioinformatic tasks and develop their own algorithms within Eclipse integrated development environment.
Summary
IT skills are among the most wanted ones on the job market today. Biology is not an exception. Programming skills are becoming very important in routine lab work. Java programming language enables relatively fast coding and there is a huge repository of ready-to-use libraries such as BioJava for example. Some common tasks in this new field called bioinformatics include dealing with DNA and protein sequences, translation, query, handling Big Data coming from various high-throughput devices and finally creating custom biological databases.
Through this course, students should become familiar with Java programming language. Skills adopted in this course should enable them to solve basic bioinformatic tasks and develop their own algorithms within Eclipse integrated development environment.
Summary
IT skills are among the most wanted ones on the job market today. Biology is not an exception. Programming skills are becoming very important in routine lab work. Java programming language enables relatively fast coding and there is a huge repository of ready-to-use libraries such as BioJava for example. Some common tasks in this new field called bioinformatics include dealing with DNA and protein sequences, translation, query, handling Big Data coming from various high-throughput devices and finally creating custom biological databases.
Learning outcomes:
Literature:
Optional literature:
- Python for Bioinformatics (Chapman & Hall/CRC Mathematical and Computational Biology), Python for Bioinformatics (Chapman & Hall/CRC Mathematical and Computational Biology) ISBN-978-1138035263, Sebastián Bassi, , .
1. semester
Molekularna biotehnologija - A1
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Regular
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Molecular Biotechnology
Elective course
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Regular
studij
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Molecular Biotechnology
3. semester
Bioprocesno inženjerstvo - B1
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Regular
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Bioprocess Engineering
Elective course
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Regular
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Bioprocess Engineering
Prehrambeno inženjerstvo - B1
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Food Engineering
Elective course
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Regular
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Food Engineering
Upravljanje sigurnošću hrane - B1
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studij
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Food Safety Management
Elective course
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Regular
studij
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Food Safety Management
Molekularna biotehnologija - A1
-
Regular
studij
-
Molecular Biotechnology
Elective course
-
Regular
studij
-
Molecular Biotechnology
Consultations schedule: