Information technologies and statistical methods in biology

Course: BIOLOGY (Bachelor) FULL-TIME

Structural unit: Biology And Medicine Institute Science Educational Center

Title
Information technologies and statistical methods in biology
Code
Module type
Обов’язкова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2022/2023
Semester/trimester when the component is delivered
3 Semester
Number of ECTS credits allocated
3
Learning outcomes
PR02. Apply modern information technologies, software Internet tools and resources for information support professional activity. PR03. plan, execute, analyze data and present experimental results research in the field of biology. PR06. Apply models, methods and data from physics, chemistry, ecology, mathematics in the learning process and providing professional activity PR07. Have techniques self-education and self-improvement. Be able to project a trajectory professional and personal growth development, applying the acquired knowledge.
Form of study
Prerequisites and co-requisites
1. Knowledge of the theoretical foundations of informatics and mathematics. Pass successfully completed the "Higher Mathematics" course. 2. The ability to independently apply knowledge of the basics of computer science and mathematics, perform practical work. 3. Have computer skills.
Course content
The educational discipline is devoted to the study of the role of modern information technologies in biology and methods of statistical analysis of biological data. The main concepts, algorithms and fields of application are considered bioinformatics. Knowledge of theoretical and applied aspects is provided creation (using the R programming language as an example) and computer use programs, databases and modern information technologies in biological research, as well as practical skills in their application to obtain, analysis, presentation and storage of biological information. Discipline forms students have an idea of random variables and their distributions, basic principles of probability theory. Provides basic knowledge of general patterns planning of biological experiments, formation of selective statistics aggregates and their classification mechanisms. Particular attention is paid to the main ones reliability criteria of statistical evaluation and statistical verification hypotheses, methods of numerical and non-numerical data analysis.
Recommended or required reading and other learning resources/tools
1. Жолос О.В. Сучасні інформаційні технології у біології: навчальний посібник. - Київ, 2022. - 197 с. [Електронний ресурс] Режим доступу: https://biomed.knu.ua/images/stories/Kafedry/biofiziki/Library/Posibnyk_CITB_compressed.pdf 2. Медична інформатика та основи статистики: методичні рекомендації для виконання практичних робіт / О.В. Жолос, О.Ф. Мороз, О.Ю. Артеменко, К.І. Богуцька, Н.Є. Нурищенко, О.В. Оглобля. - Київ, 2023. – 125 с. [Електронний ресурс] Режим доступу: https://biomed.knu.ua/images/stories/Kafedry/biofiziki/Library/Medychna_informatyka_ta_osnovy_staty styky_metod_rekom_2023_compressed.pdf 2. Прилуцький Ю.І., Ільченко О.В., Цимбалюк О.В., Костерін С.О. Статистичні методи в біології. Київ: Наукова думка, 2017. - 211 с. 3. Baker M. Big biology: The ’omes puzzle // Nature. – 2013. – 494. - P. 416–419. 4. Буджак В.В. Біометрія: навчальний посібник. – Чернівці: Чернівецький національний університет, 2016. – 272 с.
Planned learning activities and teaching methods
Lectures, individual works, practical classes.
Assessment methods and criteria
- current evaluation / control: 1. Modular control work 1 – RN 1.1-1.3 (Topic 1) – 12 points/ 6 points 2. Modular control work 2 - RN 1.4; 1.5 (Topic 2) – 10 points/ 5 points 3. Modular control work 3 – RN 1.6; 1.7 (Topic 3) – 10 points/ 5 points 4. Reports on practical works - RN 2.1-2.3; 3.1 – 28 points/ 14 points - final assessment: in the form of an exam
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Alexander Viktorovych Zholos
Department of Biophysics and Medical Informatics
Biology And Medicine Institute Science Educational Center
Yurii Ivanovych Prylutskyi
Department of Biophysics and Medical Informatics
Biology And Medicine Institute Science Educational Center
Olexandr Yuriiovych Artemenko
Department of Biophysics and Medical Informatics
Biology And Medicine Institute Science Educational Center