BIOINFORMATICS AND BIOSTATISTICS

Paper Code: 
25DBTE601B
Credits: 
04
Contact Hours: 
60
Objective: 

This course will enable students to learn to apply statistical methods to analyze biological data and draw meaningful conclusions & develop proficiency in experimental design, hypothesis testing, and data interpretation. The student will learn bioinformatics tools for sequence analysis, protein structure prediction, and database searching.

Course Outcomes: 

Course

Learning outcome

(at course level)

Learning and teaching strategies

Assessment Strategies

Course Code

Course

title

25DBTE601B

Bioinformatics and Biostatistics

(Theory)

CO57B. Apply information technology to understand biological data and its management in form of primary and secondary databases.

CO58B. Analyze the information stored in structural databases; apply sequence similarity searching tools/methods to determine relatedness among species.

CO59B. Assess the different methods of data collection, classification and tabulation; Compute probabilities of events using theorems.

CO60B. Estimate the different measures of central tendency, dispersion, skewness and kurtosis and infer the values obtained.

CO61B. Formulate hypothesis for a research study and test it using appropriate statistical tests and interpret the findings of study.

CO62B. Contribute effectively in course-specific interaction

Approach in teaching:

Interactive Lectures,

Demonstrations

 

Learning activities for the students: Discussion,

Tutorials,

Assignments,

Reading journals

Class test, Semester end examinations, Quiz, Solving problems in tutorials, Assignments, Presentation, Individual and group projects

 

12.00
Unit I: 
Bioinformatics- I

Overview of bioinformatics- introduction, advantages and limitations, Database types- Primary and secondary databases, sequence databases- nucleotide and protein sequence databases (NCBI, EMBL, DDBJ, UNIPORT)

12.00
Unit II: 
Bioinformatics- II

Structure databases (PDB, MMDB), Concept of similarity searching, methods of similarity searching (BLAST, FASTA) and its use, multiple sequence alignment.

12.00
Unit III: 
Basics of Biostatistics

Sampling - Sampling procedure, types of sampling, Classification and tabulation of data, frequency distribution, probability, addition and multiplication theorem of probability, advantages and limitations of biostatistics.

 

12.00
Unit IV: 
Measure of central tendency and dispersion

Mean, median and mode, Measures of dispersion - Standard deviation, coefficient of variation, Skewness and Kurtosis.

 

 

12.00
Unit V: 
Tests of Significance

Hypothesis testing, Nulls hypothesis and alternative hypothesis, Chi-square test, F-test, ANOVA- one way and two way classifications.

 

 

ESSENTIAL READINGS: 
  • Biostatistics: A Foundation for Analysis in Health Sciences, (7th edition), W W Daniel, John Wiley and Sons Inc., 2001.
  • Essential Bioinformatics, JinXiong, John Wiley and Sons. 2006.
  • Introduction to Bioinformatics, A Teresa and D P Smith, Prentice Hall, 2006.
  • Statistical Methods in Biology, N T J Bailey, Cambridge University Press, 1995.
  • Introduction to Bioinformatics, A M Lesk, Oxford University Press, 2002.
  • Practical statistics for Experimental Biologists, A C Swardlaw, John Wiley and sons Inc., 1985

 

REFERENCES: 
  • Bioinformatics, A practical Guide to the Analysis of Genes and Proteins, (2nd edition), A D Baxevanis, and B F Ouellette, John Wiley and Sons, 2002.
  • Fundamentals of Biostatistics, Hammanth Rao & K. Janardan, I K International Publishing House Pvt. Ltd, 2013
  • Instant notes, Bioinformatics, Westhead, Parish, and Twyman, (1st edition), Bios Scientific Publishers Ltd., 2003.
  • Biostatistics: Basic Concepts and Methodology for the Health Sciences, 10ed, ISV. Wiley 2019
  • Bioinformatics Sequence and Genome Analysis 2ed CBS Publishers, 2005
  • Sequence Analysis Primer, Gribskov and Devereux, Stockton Press, 1989
Academic Year: 
2025-2026
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