National University of Sciences and Technology
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CSE-877 Statistics in Bioinformatics
Campus RCMS
Programs PG
Session Spring Semester 2017
Course Title Statistics in Bioinformatics
Course Code CSE-877
Credit Hours 3-0
Pre-Requisutes
Course Objectives This is a 3 credit hours course designed for students with a background in biological sciences who have covered the pre-requisite courses of Computational Drug Design and Advanced Computational Biology. The course aims to provide students with the background knowledge of probability distributions and statistical knowledge applicable in analysis of molecular biology data. Furthermore, it will use the R statistical package for the implementation of these concepts. R is a widely used for data analysis and visualization in the scientific community and this will provide students with a useful set of skills to apply in their own research work.
Detail Content
  • Distributions: putting particular focus on Binomial, Negative Binomial, Multinomial,
  • Poisson, and Gaussian distributions and their applications in moleuclar biology.
  • Data display and decommentive statistics
  • Univariate and multivariate statistics
  • Hypothesis testing
  • Correlation and Regression analysis
  • Particularly looking at Regression, Anova, PCA and HCA.
  • Linear models.
  • Micro Array Analysis
  • Analyzing sequences
  • Markov models
Text/Ref Books
  • Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids by: Richard Durbin, Sean R. Eddy, Anders Krogh, Graeme Mitchison (13 May 1998) Key: citeulike:163532
  • R programming for bioinformatics, by Robert Gentleman, Boca Raton, Chapman & Hall/CRC, 2009, ISBN 1-42006-367-7
  • Applied Statistics for Bioinformatics using R, by Wim P. Krijnen
  • Computer Simulation and Data Analysis in Molecular Biology and Biophysics: An Introduction Using R, by Victor A. Bloomfield, 2009 (Springer)
Time Schedule Spring Semester 2017
Faculty/Resource Person Dr Zamir Hussain
PhD (Bahauddin Zikaria University)
Discipline: Statistics
Specialization: Statistics