BIOINFORMATICS AND BIOSTATISTICS

Paper Code: 
DMBL 601B
Credits: 
04
Contact Hours: 
60
Objective: 

 

Course Outcomes (COs):

Learning outcome

(at course level)

Learning and teaching strategies

Assessment Strategies

On completion of this course, the learner will:

CO 49 B: recognize the definition of statistics, its subject and its relation with the other sciences. Understand probability.

CO 50 B: Learn the classification of data, frequency distribution and graphical distribution of data. Measures of central tendencies

CO 51B: Learn Hypothesis testing by student t and chi-square test.

CO 52 B: To learn how bioinformatics data is stored and organized in various databases like NCBI and how to locate and extract data from key bioinformatics databases.

CO53 B: Learn similarity searching by BLAST & FASTA.

Interactive Lectures, Discussion, Tutorials, Reading assignments, presentations

Self-learning assignments, Effective questions

Giving tasks.

C A test, Semester end examinations, Quiz, Solving problems in tutorials, Assignments, Classroom interaction

 

9.00
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)

 

 

9.00
Unit II: 
Bioinformatics- II

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

 

8.00
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.

 

9.00
Unit IV: 
Measure of central tendency and dispersion

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

 

10.00
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: 

SUGGESTED READINGS:

  • 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

 

e RESOURCES:

 

JOURNALS:

  • International Journal of Molecular Biotechnology
  • Indian Journal of Biotechnology
  • Current Science
  • Bioinformatics

 

 

Academic Year: 
2023-2024
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