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Date

Topics

Slides

Matlab

Homework
(not graded)

Exams

1

Aug 24

Why probability and statistics in comutational bioengineering? Lecture_1.pdf      
2

Aug 26

Random experiments. Sample space, Events, Venn diagramms. 

Definitions of probability:
Statistical (part 1)

Lecture2.pdf      
3

Aug 31

Definitions of probability:
Statistical (continued)

Definitions of probability:
Inductive. 

Paradoxes of inductive definition of probability

Combinatorics

Lecture3.pdf

coin_toss_template.m

coin_toss.m

   
4

Sep 2

Combinatorics (continued)

Probability axioms

Conditional probability

Independence of events

Circuit diagrams

Lecture4.pdf      
5

Sep 7

Circuit diagrams (continued)

Bayes' theorem

Specificity/Sensitivity of tests

Lecture5.pdf

circuit_template.m

circuit.m

   
6

Sep 9 

Bayes' theorem (continued)

Monty Hall problem

Lecture6.pdf

monty_hall_template.m

monty_hall.m

hw1.pdf


 

7

Sep 14

Discrete random varibales,

PMF. CDF, CCDF, 
Mean, Variance, Skewness

Uniform distribution

The distribution of the
Ct value in COVID-19
PCR tests

Lecture7.pdf

 

   
8

Sep 16

Bernoulli trials

Binomial Distribution

Secretary Problem

Lecture8.pdf

binomial_template.m

binomial.m

hw1_with_solutions.pdf  
9

Sep 21

Binomial Distribution (continued)

Poisson Distribution

Genome Assembly

Lecture9.pdf

poisson_template.m

poisson.m

   
10

Sep 23

Geometric distribution.

Phylogenetic trees and time to the most recent common ancestor. 

Mitochondrial Eve, Y-chromosome Adam and ancestry of nuclear DNA

Lecture10.pdf

 

   
11

Sep 28

Mitochondrial Eveen (continued)

Negative Binomial Distribution

Cancer: Driver and Passanger genes/mutations

Lecture11.pdf

geometric_negative_binomial_template.m

geometric_negative_binomial.m

   
12

Sep 30

Continuous random variables.

Probability Density Function, CDF, CCDF, Mean, Variance, Std

Uniform continuous distribution. 

Constant rate (Poisson) process.

Exponential distribution.

Lecture12.pdf

 

   
13

Oct 5

Erland, Gamma, Gaussian distributions Lecture13.pdf

exponential_gamma_template.m

exponential_gamma.m

   
14

Oct 7 

Gaussian (continued)

Fitting Gaussian distribution to the data on binding energies of protein-protein interactions 

Lecture14.pdf PINT_binding_energy.mat hw2.pdf  
15

Oct 12

Multiple random variables. Joint, Marginal, and Conditional PMFs or PDFs.

Statistical independence of variables

Lecture15.pdf      
16

Oct 14

Covariance

Correlation coefficients:
Pearson, Spearman

Lecture16.pdf

Excercise #1:
correlation_template.m
correlation.m

Exercise #2:
cancer_wdbc.mat
cancer_wdbc_cc_analysis_template.m
cancer_wdbc_cc_analysis.m

hw2_with_solutions.pdf  
17

Oct 19

Midterm preparation Lecture17.pdf       
 

Oct 21

Midterm        
18

Oct 26

Samples, histograms, 
median, quartiles, percentiles
Box-and-whisker plots
Lecture18.pdf

quartiles_template.m

quartiles.m

 

   
19

Oct 28

Sample mean. Its mean and variance (standard error). Central limit theorem.

Parameter point estimation (part one)..

Lecture19.pdf

central_limit_theorem_template.m

central_limit_theorem.m

hw3.pdf  
20

Nov 2

Parameter point estimation. Method of moments and Maximum Likelihood Estimator Lecture20.pdf

moment_estimators_template.m

moment_estimators.m

   
21

Nov 4

Sample variance; Confidence intervals of population mean and variance; Student-t and chi-squared distributions Lecture21.pdf

confidence_intervals_template.m

confidence_intervals.m

 

hw3_with_answers.pdf  
22

Nov 9

Confidence intervals (continued). Hypothesis testing Lecture22.pdf

dark_vs_milk_chocolate_analysis_template.m

dark_vs_milk_chocolate_analysis.m

hw4.pdf  
23

Nov 11

Pearson's chi-square Goodness of Fit (GOF) test Lecture23.pdf

m_and_m_analysis_template.m

m_and_m_analysis.m

   
24

Nov 16

Linear regression: two variables   Lecture24.pdf

regression_multiple_template.m

expression_table.mat

hw4_with_answers.pdf  
25

Nov 18

Multiple Linear Regression.
PCA (part one)
Lecture25.pdf

 

hw5.pdf  
26

Nov 30

PCA (part two)

Clustering 

Lecture26.pdf

cancer_wdbc_pca_analysis.m

clustering.m

   
27

Dec 2

Important nodes in networks: degree, PageRank,  betweenness-centraility.

Co-expression and disease-disease networks analyzed using Gephi software

Lecture27.pdf

gephi_network_analysis_exercise.docx

gephi_install_notes.docx

coexpression_network_random start.gephi

disease_disease_random_start.gephi

hw5_with_answers.pdf  
28 Dec 7 Final exam preparation Lecture28.pdf      

FINAL EXAM

Dec 10 

7pm-10pm

 305 Materials Science & Eng Bld

(the same room as classes)