Biostatistics and Bioinformatics (BBK 3008) - VDU Biochemijos ir biotechnologijų katedra
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Biostatistics and Bioinformatics (BBK 3008)

Course code

Course group

Volume in ECTS credits

Course hours

BBK 3008

C

3

80

Course type (compulsory or optional)

Compulsory

Course level (study cycle)

Bachelor

Semester the course is delivered

Autumn

Study form (face-to-face or distant)

Face-to-face

Course title in Lithuanian

BIOSTATISTIKA IR BIOINFORMATIKA

Course title in English

BIOSTATISTICS AND BIOINFORMATICS

Short course annotation in Lithuanian

Dalyko tikslas – supažindinti studentus su statistinių metodų taikymu biologijos ir gyvosios gamtos moksluose bei genetinės informacijos kodavimu, bioinformacinėmis duomenų bazėmis, sekų analize. Kurso metu studentai supažindinami su rizikos vertinimu, logistine regresija, išgyvenamumo analize, bioinformatikos pagrindais, sekų analize, proteinų, struktūra, jos vizualizacija bei modeliavimu. Studentams supažindinami su biostatistikos teoriniais pagrindais ir metodų taikymu biochemijos duomenų analizėje. Išklausę kursą studentai sugebės taikyti statistikos metodus, naudotis duomenų bazėmis bei analizuoti DNA duomenis.

Short course annotation in English

The aim of course is the introduction of students with risk assessment, logistic regression, survival analysis and its application for biological data, with sequence alignment methods, protein structures, visualization and modeling of structures. After completion of this course student will be competent to application of statistical methods in biological data, will have a perspective to what is bioinformatics, the knowledge of some key methods and tools commonly used, and ability to talk to others about the bioinformatics needs.

Prerequisites for entering the course

Theory of probability and statistics

Course aim

The aim of the course is to provide an introduction to biostatistics and applications of these methods and bioinformatics

Content (topics)

 1. Testing statistical hyphotheses, statistical tests
 2. Compare of two and more populations, regression analysis
 3. Risk assessment
 4. Logistic regression
 5. Survival analysis
 6. Introduction to bioinformatics
 7. Sequence alignment methods, protein structures and its modelling

Practical work (contents):

The use of t- and chi-square tests; correlation and regression analysis; logistic regression; risk assessment; survival analysis, sequence aligments, protein structures, visualization and modeling of structures

Distribution of workload for students (contact and independent work hours)

Lectures – 30 hours, laboratory work in computer class – 15 hours, individual work – 35 hours.

Structure of cumulative score and value of its constituent parts

Final assessment sums the assessments of written final examination (50%), written mid-term examination (20%) and assessment of laboratory works (30%).

Recommended reference materials

No.

 

Publication year

Authors of publication and title

Publishing house

Number of copies in

University library

Self-study rooms

Other libraries 

Basic materials

1.

2010

J. Venclovienė „Statistiniai metodai medicinoje” (Statistical methods in medicine)

Kaunas: VDU  

20

 

 

2.

2005

M.Gail, K. Kricberg, J. Samet, A. Tsiatis, W. Wong Statistics for biology and health

Springer

 

 

 

Course programme designed by

Prof. dr.Jonė Venclovienė, Faculty of Natural Sciences, Department of Environmental Sciences, Doc.dr.Janne Ravantti, Helsinki University

Additional information