Biostatistics and Bioinformatics

Paper Code: 
BTE 602
Credits: 
03
Contact Hours: 
45
Objective: 

This course will enable the students to -

  1. understand the importance of statistical analysis of biological data
  2. learn various methods of statistical analysis
  3. get aquatinted to the computational aspect of Biotechnology

Course Outcomes (COs): 

Course

Learning outcome (at course level)

Learning and teaching strategies

Assessment Strategies

Paper Code

Paper Title

BTE602

Biostatistics and Bioinformatics

 

CO 67 recognize the definition of statistics, its subject and its relation with the other sciences.

CO 68 define the principal concepts about biostatistics.

CO 69 Learn the classification of data, frequency distribution and graphical distribution of dataMeasures of central tendencies

CO 70 Learnmean deviation, variance, standard deviation and coefficient of variationHypothesis testing by student t and chi-square test.

CO 71 Understand probability, binomial, poison, normal distribution and their applications& solve problems on problem distribution.

CO 72To learnhow bioinformatics data is stored and organized in various databases like  NCBI and how to locate and extract data from key bioinformatics databases.

CO 73 Learn similarity searching by BLAST & FASTA.

Approach in teaching:

Interactive Lectures, Discussion, Tutorials, Reading assignments, presentations

 

Learning activities for the students:

Self-learning assignments, Effective questions, Seminar presentation, Giving tasks.

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

 

 
8.00
Unit I: 
Basics of Biostatistics

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

 

9.00
Unit II: 
Measure of central tendency and dispersion

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

10.00
Unit III: 
Tests of Significance

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

9.00
Unit IV: 
Bioinformatics- I

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

 

 

9.00
Unit V: 
Bioinformatics- II

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

 

ESSENTIAL READINGS: 
  1. Fundamentals of Biostatistics, Khan,  Publishing Corporation, 1999
  2. Statistical Methods in Biology, 3rd edition, N T J Bailey, Cambridge University Press, 1995
  3. Statistics for Biologist, R C Campbell, Cambridge University Press, 1989
  4. Textbook of Bioinformatics, Prof. Vinay Sharma, Rastogi Publications, 2008

 

REFERENCES: 
  1. Bioinformatics, Higgins & Taylor, OUP, 2000
  2. Biostatistics: A Foundation for Analysis in Health Sciences, 6th edition, W W Daniel, John Wiley and Sons Inc., 1995
  3. Introduction to Bioinformatics, A Teresa and D P Smith, Prentice Hall Publisher, 1999
  4. Molecular databases for Protein Sequence and Structure studies, J A Sillince and M. Sillince, Springer Verlag, 1991
  5. Practical statistics for Experimental Biologists, A C Swardlaw,  John Wiley and sons Inc., 1985
  6. Sequence analysis primer, Gribskov and Devereux, Stockton Press, 1989

 

Academic Year: 
2020-2021
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