Course details
Bioinformatics
BIF Acad. year 2020/2021 Summer semester 5 credits
This course introduces students to basic principles of molecular biology, present algorithms pro biological data analysis, describes their time complexity and shows direction how to design the new methods very effectively. Particularly, the following algorithms will be discussed: methods for sequence alignment, evolutionary models, construction of phylogenetic trees, algorithms for gene identification using machine learning and approaches for prediction of 2D and 3D protein structure. Lectures will be supplement with practical examples using available biological databases.
Guarantor
Course coordinator
Language of instruction
Completion
Time span
- 26 hrs lectures
- 12 hrs pc labs
- 14 hrs projects
Assessment points
- 58 pts final exam (written part)
- 16 pts mid-term test (written part)
- 12 pts labs
- 14 pts projects
Department
Lecturer
Instructor
Subject specific learning outcomes and competences
Students will be able to take advantages of large biological database and design new efficient algorithms for their analysis.
Understanding the relations between computers (computing) and selected molecular processes.
Learning objectives
To understand the principles of molecular biology. To perceive the basic used algorithms and to well informed about relevant biological databases. To be able to design new effective methods for biological data analysis.
Why is the course taught
Biological data analysis requires a knowledge of basic bioinformatics algorithms and tools (sequence alignment, phylogenetic tree construction, assembling/mapping of sequencing data, etc.). The goal of this course is to provide this information for the students and prepare them for a future profession in the area of bioinformatics.
Syllabus of lectures
- Introduction to bioinformatics
- Basis of molecular biology
- Tools of molecular biology
- Biological databases
- Sequence alignment, dynamic programing, BLAST, FASTA
- Evolutionary models
- Construction of phylogenetic trees
- DNA assembling
- Genomics and gene searching
- Proteins and their prediction
- Computation of RNA secondary structure
- Proteomics, regulatory networks
- Polymorphism of genes
Syllabus of computer exercises
- Biological databases
- Analysis of genome sequences
- Sequence alignment
- Phylogenetic trees
- Gene prediction
- Protein structure analysis
Syllabus - others, projects and individual work of students
A project will be assigned to each student. Implementation, presentation and documentation of the project will be evaluated.
Progress assessment
Mid-term exam, project, computer lab assignments.
Exam prerequisites:
None.
Controlled instruction
Presence in any form of instruction is not compulsory. An absence (and hence loss of points) can be compensated in the following ways:
- presence in another laboratory group dealing with the same task.
- showing a summary of results to the tutor at the next lab.
- sending a short report (summarizing the results of the missed lab and answering the questions from the assignment) to the tutor, in 14 days after the missed lab.
Exam prerequisites
None.
Course inclusion in study plans
- Programme IT-MGR-2, field MBI, 1st year of study, Compulsory
- Programme IT-MGR-2, field MBS, MGM, MIN, MIS, MMM, MPV, MSK, any year of study, Elective
- Programme MITAI, field NADE, NCPS, NEMB, NGRI, NHPC, NIDE, NISD, NISY, NMAL, NMAT, NNET, NSEC, NSEN, NSPE, NVER, NVIZ, any year of study, Elective
- Programme MITAI, field NBIO, 1st year of study, Compulsory