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Lecturer(s)
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Course content
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Biopython The ability to parse bioinformatics files into Python utilizable data structures, including support for the following formats: - Blast output both from standalone and WWW Blast - Clustalw - FASTA - GenBank - PubMed and Medline - ExPASy files, like Enzyme and Prosite - SCOP, including 'dom' and 'lin' files - UniGene - SwissProt Files in the supported formats can be iterated over record by record or indexed and accessed via a Dictionary interface. Code to deal with popular on-line bioinformatics destinations such as: - NCBI Blast, Entrez and PubMed services - ExPASy Swiss-Prot and Prosite entries, as well as Prosite searches Interfaces to common bioinformatics programs such as: - Standalone Blast from NCBI - Clustalw alignment program - EMBOSS command line tools A standard sequence class that deals with sequences, ids on sequences, and sequence features. Tools for performing common operations on sequences, such as translation, transcription and weight calculations. Code to perform classification of data using k Nearest Neighbors, Naive Bayes or Support Vector Machines. Code for dealing with alignments, including a standard way to create and deal with substitution matrices. Code making it easy to split up parallelizable tasks into separate processes. GUI-based programs to do basic sequence manipulations, translations, BLASTing, etc. Extensive documentation and help with using the modules, including this file, on-line wiki documentation, the web site, and the mailing list. Integration with BioSQL, a sequence database schema also supported by the BioPerl and BioJava projects.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Work with text (with textbook, with book), Demonstration, Individual preparation for exam
- Class attendance
- 56 hours per semester
- Preparation for classes
- 10 hours per semester
- Preparation for exam
- 9 hours per semester
- Preparation for credit
- 25 hours per semester
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Learning outcomes
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Biopython is a set of freely available tools for biological computation written in Python by an international team of developers. Active participation and understanding of the presented topics and creating single-handed software project.
- The ability to parse bioinformatics files into Python utilizable data structures, including support for the following formats: - Files in the supported formats can be iterated over record by record or indexed and accessed via a Dictionary interface. - Code to deal with popular on-line bioinformatics destinations such as: - Interfaces to common bioinformatics programs such as: - A standard sequence class that deals with sequences, ids on sequences, and sequence features. - Tools for performing common operations on sequences, such as translation, transcription and weight calculations. - Code to perform classification of data using k Nearest Neighbors, Naive Bayes or Support Vector Machines. - Code for dealing with alignments, including a standard way to create and deal with substitution matrices. - Code making it easy to split up parallelizable tasks into separate processes.
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Prerequisites
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Basics of programming in any programming language, programming algorithms, UML basics. Python Basics UAI/735I
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Assessment methods and criteria
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Student performance assessment, Combined exam, Analysis of the qualification work
The condition for credits is 80% attendance (or appologized) and 80% of homeworks (We will create a credit system of 100 points max - it means that you must have 80 points from homeworks minimum to be. [The situation can be can checked in moodle.]
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Recommended literature
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Programming in Python 3: A Complete Introduction to the Python Language - Mark Summerfield.
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Python programming for biology : bioinformatics and beyond / Tim J. Stevens and Wayne Boucher. -- 1st pub. -- Cambridge : Cambridge University Press, 2015..
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