BIOSTATISTICS AND BIOINFORMATICS

Paper Code: 
BTE 125
Credits: 
05
Contact Hours: 
75
Objective: 

This course will enable the students to -

  1. Appreciate the significance of statistical analysis of biological data.
  2. Learn the methods of statistical analysis.
  3. know about Bioinformatics as a tool in Biotechnology

Course Outcomes (COs):

Course

Learning outcome (at course level)

Learning and teaching strategies

Assessment Strategies

Paper Code

Paper Title

BTE125

 

Biostatistics & Bioinformatics

 

Upon completion of the course students will be able to:

CO 16. Analyze, interpret, study and characterize biological data stored in various databases available on internet.  

CO 17. Acquire knowledge about the existing software effectively and to apply  in computer modeling

CO 18. Learn problem-solving skills, including the ability to develop new algorithms and analysis methods

CO 19. Acquirean understanding of the intersection of life and information sciences.

Approach in teaching:

Interactive Lectures, Discussion, Tutorials, Reading assignments

Learning activities for the students:

Self-learning assignments, Effective questions, Presentation, Giving tasks

Class test, Semester end examinations, Quiz, Solving problems in tutorials, Assignments, Presentation

 

11.00
Unit I: 
Sampling and classification of data

Sampling - Sampling procedure, types of sampling, Classification and tabulation of data, frequency distribution, probability, addition and multiplication theorem of probability. A brief idea of normal, Poisson and binomial distribution.

14.00
Unit II: 
Measures of central tendency and dispersion

Measure of central tendency-Mean, median and mode, Measures of dispersion - range , mean deviation ,standard deviation, coefficient of variation, Skewness and kurtosis

16.00
Unit III: 
Tests of significance

Hypothesis testing, Nulls hypothesis and alternative hypothesis, level of significance. Chi-square test, t-test, F-test, ANOVA-one way and two way classifications. Simple correlation and simple regression.

15.00
Unit IV: 
Overview of bioinformatics

Overview of bioinformatics – introduction, The internet and the biologist, Database types-Primary and Secondary databases, sequence databases - nucleotide and protein sequence databases (NCBI, ENBL, DDBJ, UNIPORT, PIR), Structure databases (PDB, MMDB, CSD, NDB)

Sequence analysis

19.00
Unit V: 
Sequence similarity searching

Concept of similarity searching, methods of similarity searching (BLAST, FASTA) statistical significance of sequence comparisons, application of similarity searching in gene identification and functional assingment. Information retrieval from biological databases. Computer tools for finding and retrieving sequences, pair wise and multiple alignments. Genomics and Genome project

ESSENTIAL READINGS: 
  1. Biostatistics: A Foundation for Analysis in Health Sciences, (6th edition), W W Daniel, John Wiley and Sons Inc., 1995.
  2. Essential Bioinformatics, Jin Xiong, John Wiley and Sons. 2006.
  3. Introduction to Bioinformatics, A Teresa and D P Smith, Prentice Hall, 1999.
  4. Statistical Methods in Biology, N T J Bailey, Cambridge University Press, 1995.
  5. Statistics for Biologist, R C Campbell, Cambridge University Press, 1989.
REFERENCES: 
  1. 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.
  2. Fundamentals of Biostatistics, Khan,  Publishing Corporation, 1999
  3. Instant notes, Bioinformatics, Westhead, Parish, and Twyman, (1st edition), Bios Scientific Publishers Ltd., 2003.
  4. Introduction to Bioinformatics, A M Lesk, Oxford University Press, 2002. 
  5. Molecular databases for Protein sequence and Structure studies, J A Sillince and M  Sillince, Springer Verlag, 1991
  6. Practical statistics for Experimental Biologists, A C Swardlaw,  John Wiley and sons Inc., 1985
  7. Sequence Analysis Primer, Gribskov and Devereux, Stockton Press, 1989

 

Academic Year: 
2020-2021
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