Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Biological Networks
Analysis
Introduction and Dijkstras algorithm
Genome 559: Introduction to Statistical and
Computational Genomics
Elhanan Borenstein
A quick review
The clustering problem:
partition genes into distinct sets with
high homogeneity and h
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Gene Ontology and
Functional Enrichment
Genome 559: Introduction to Statistical and
Computational Genomics
Elhanan Borenstein
A quick review
The parsimony principle:
Find the tree that requires the
fewest evolutionary changes!
A fundamentally different
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Clustering
kmean clustering
Genome 559: Introduction to Statistical and
Computational Genomics
Elhanan Borenstein
A quick review
The clustering problem:
partition genes into distinct sets with
high homogeneity and high separation
Clustering (unsupervi
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Clustering
Genome 559: Introduction to Statistical and
Computational Genomics
Elhanan Borenstein
Some slides adapted from Jacques van Helden
A quick review
Gene expression profiling
Which molecular processes/functions
are involved in a certain phenotype
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Gene Set
Enrichment Analysis
Genome 559: Introduction to Statistical and
Computational Genomics
Elhanan Borenstein
A quick review
Gene expression profiling
Which molecular processes/functions
are involved in a certain phenotype
(e.g., disease, stress re
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Parsimony
Small Parsimony and Search Algorithms
Genome 559: Introduction to Statistical and
Computational Genomics
Elhanan Borenstein
A quick review
The parsimony principle:
Find the tree that requires the
fewest evolutionary changes!
A fundamentally d
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Sequence comparison:
Score matrices
http:/faculty.washington.edu/jht/GS559_2013/
Genome 559: Introduction to Statistical
and Computational Genomics
Prof. James H. Thomas
FYI  informal inductive proof of best alignment path
Consider the last step in the b
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Parsimony
Genome 559: Introduction to Statistical and
Computational Genomics
Elhanan Borenstein
Who am I?
Faculty at Genome Sciences
Computational (systems) biologist
Training: CS, physics, hitech, biology
Research interests: Metagenomics and the Human M
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Whole genome alignments
http:/faculty.washington.edu/jht/GS559_2013/
Genome 559: Introduction to Statistical
and Computational Genomics
Prof. James H. Thomas
Extreme value distribution
characteristic
width
PS
x
1e
(e
x
)
S is data score, x is test score
p
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Computing a tree
http:/faculty.washington.edu/jht/GS559_2013/
Genome 559: Introduction to Statistical
and Computational Genomics
Prof. James H. Thomas
Defining what a tree means
rooted tree (all real trees are rooted):
branch
points or
"nodes"
unrooted tr
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Sequence comparison:
Local alignment
Genome 559: Introduction to Statistical
and Computational Genomics
Prof. James H. Thomas
http:/faculty.washington.edu/jht/GS559_2013/
Review global alignment
G
A
A
T
C
0
4
8
12
16
20
C
4
5
9
13
12
6
A
8
4
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Sequence comparison:
Significance of alignment scores
http:/faculty.washington.edu/jht/GS559_2013/
Genome 559: Introduction to Statistical
and Computational Genomics
Prof. James H. Thomas
Unscaled EVD equation
characteristic
width
PS
x
1e
(e
x
)
S is data
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Sequence comparison:
Dynamic programming
Genome 559: Introduction to Statistical
and Computational Genomics
Prof. James H. Thomas
http:/faculty.washington.edu/jht/GS559_2013/
Sequence comparison overview
Problem: Find the best alignment between a
query s
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Genome 559:
Introduction to Statistical and
Computational Genomics
Professors Jim Thomas and
Elhanan Borenstein
Logistics
Syllabus and web site:
http:/faculty.washington.edu/jht/GS559_2013/
Should I take this class?
Grading
Send homework by email ATTA
Introduction to Statistical and Computational Genomics
GS 599

Winter 2013
Sequence comparison:
Significance of similarity scores
http:/faculty.washington.edu/jht/GS559_2013/
Genome 559: Introduction to Statistical
and Computational Genomics
Prof. James H. Thomas
Review
How to compute and use a score matrix.
logodds of sumof
Introduction to Evolutionary Mechanisms
Evolution  what is it? Darwin and the Beagle Early evolutionary insights Influences on Darwin Darwins major hypotheses
Darwins achievements
Transformed biological science
Both style and content Still the corners
CretaceousTertiary Boundary
K/T boundary site in Italy 2.5cmthick clay layer shows high concentration of iridium
Boundary Sites
Some CretaceousTertiary boundary sites also contain
soot shockmetamorphosed quartz grains
http:/wwwdsa.uqac.ca/~mhiggin
What is life?
Metabolism Reproduction Evolution Life is a chemical system capable of Darwinian Evolution. "The arrangement of the atoms in the most vital parts of an organism and the interplay of these arrangements differ in a fundamental way from all th
What is Science?
Lecture 1
Assumption
The goal of science is to make general statements about the universe. Science aims to reduces all empirically obtained knowledge to several allencompassing theories
Scientific Thought
Science has been able to achie
Major Questions in Human Evolution
1. What caused evolution of upright posture 2. What is relationship of climate and human evolution 3. What is correct phylogeny of hominids 4. What caused evolution of dramatic brain size increase? 5. What was origin of