Introduction to Bioinformatics October 13, 03 1 - DSIMB

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Introduction
to
Bioinformatics
October 13, 03
1
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
1
)
Introduction to Bioinformatics
http://www.
bioinformaticscourses
.com/
bioinform/
Helge
Weissig,
Ph.D.
helgew
@
bioinformaticscourses
.com
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
2
)
Course Objectives
o
Provide
a
broad
overview
of
the
field
o
Introduce
some
of
the
most
commonly
used
online
Bioinformatics
tools
o
Present
basic
algorithmic
concepts
o
Practice
query,
retrieval
and
analysis
of
sequences
and
structures
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
3
)
Course Schedule
o
Lecture
1
o
Course Introduction
o
NCBI Entrez
o
Lecture
2
o
The BLAST Algorithm
o
Using BLAST online
o
Lecture
3
o
ORF Finder
o
GENSCAN
o
Principles and use of
PSI-BLAST
o
Lecture
4
o
Multiple Sequence
Alignments with
ClustalW
o
Protein analysis (Prosite
,
Pfam
,
PRINTS,
Blocks)
o
Lecture
5
o
Databases and interface
design
o
Programming Languages
o
Lecture
6
o
Structural Bioinformatics
primer
o
Finding and analyzing
structures with the PDB
Introduction
to
Bioinformatics
October 13, 03
2
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
4
)
Introduction to Bioinformatics
Lecture 1

Course
Introduction

NCBI
Resources
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
5
)
Textbook
Bioinformatics
for
Dummies
Jean-Michel
Claverie
&
Cedric

Notredame
Wiley
Publishing,
Inc.
ISBN
0-7645-1696-5
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
6
)
The systematic development and
application of computing systems
and computational solution
techniques to the analysis of
biological data obtained by
experiments, modeling, database
search, and instrumentation
What is Bioinformatics?
Introduction
to
Bioinformatics
October 13, 03
3
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
7
)
The systematic development and
application of computing systems
and computational solution
techniques to models of biological
phenomena
What is Computational Biology?
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
8
)
Components of Bioinformatics
Biological
Data
Computers
Algorithms
Outset
?
this
that
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
9
)
Biological Data
“central
dogma
of
molecular
biology

DNA
RNA
Protein
Phenotype
Introduction
to
Bioinformatics
October 13, 03
4
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
10)


A

{
A
,
C
,
G
,
T
}


A

a
1
...
a
n
,

a
x

A
“A
string
in
a
four-letter
alphabet

Molecular Biology and
Computational Abstractions
DNA
RNA
Protein
Phenotype
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
11)
“A
string
in
a
four-letter
alphabet

Molecular Biology and
Computational Abstractions [2]
DNA
RNA
Protein
Phenotype


B

{
A
,
C
,
G
,
U
}


B

b
1
...
b
n
,

b
x

B
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
12)
“A
string
in
a
twenty-letter
alphabet

Molecular Biology and
Computational Abstractions [3]
DNA
RNA
Protein
Phenotype


C

A

Y


,
[
B
,
J
,
O
,
U
,
X
]

C


C

c
1
...
c
n
,

c
x

C
Introduction
to
Bioinformatics
October 13, 03
5
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
13)
“Information
transfer

Molecular Biology and
Computational Abstractions [4]
DNA
RNA
Protein
Phenotype
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
14)
Information Transfer During
Evolution
Evolutionary
Distance
Phylogenetic
Tree
Horizontal
Transfer
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
15)
Information Theory Primer

Information is measured in bits

1
bit
:=
choice
between
two
equally
possible outcomes
=> DNA: 2 bits per base
Introduction
to
Bioinformatics
October 13, 03
6
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
16)
Information Theory Primer [2]

Information
measured
in
bits

Is
additive

Is
well
supported
mathematically

Measures
sequence
conservation

Is
calculated
as
a
decrease
in
uncertainty:

Rate
of
information
transmission:

Credits
&
details:
http://www.
lecb.
ncifcrf
.
gov/~toms/

H


p
i
log
2
p
i
i

1
n

[bits]

R



H
[bits/symbol]
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
17)
0.00E+00
2.00E+09
4.00E+09
6.00E+09
8.00E+09
1.00E+10
1.20E+10
1.40E+10
1.60E+10
1.80E+10
1982
1985
1988
1991
1994
1997
2000
Year
0.00E+00
2.00E+06
4.00E+06
6.00E+06
8.00E+06
1.00E+07
1.20E+07
1.40E+07
1.60E+07
Base Pairs
Sequences
Information Growth: Sequences
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
18)
1.E+04
1.E+05
1.E+06
1.E+07
1.E+08
1.E+09
1.E+10
1995
1997
1998
2001
0
10000
20000
30000
40000
Base Pairs
Genes
Bacterium
Eukaryotic Cell
Animal
Human
Information Growth: Genomes
Introduction
to
Bioinformatics
October 13, 03
7
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
19)
Information
Growth:
Macromolecular Structures
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
20)
Information Complexity
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
21)
Information Complexity [2]
Genes, Proteins,
RNAs
, and others
Complexity
Complete Genomes
Biochemical Pathways & Processes
Cellular & Developmental Processes
Tissue and
Organismal
Physiology
Ecological Processes and Populations
Introduction
to
Bioinformatics
October 13, 03
8
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
22)
Bioinformatics Applications
Genes
and
Gene
Structures
Reconstructing
Phylogeny,
Homology,
and
Comparitive
Approaches
Predicting
Protein
Sequence
Simulating
and
Understanding
Gene
Expression
Networks
Assembled
Genomes
Genes, Proteins,
RNAs
, and others
Sequence Variation of
Populations
Predicting
Three-Dimensional
Structures
of
Proteins
and
RNAs
Predicting
Functions
Modeling
Structures
of
Multi-
molecular
complexes
Predicting
Effects
of
Variation
Complexity
Modeling
Catalysis,
Molecular
Dynamics
Morphogenesis
and
Development
Simulation
of
Metabolic
and
Signal
Transduction
Pathways
Complete
Genomes
Biochemical
Pathways &
Processes
Cellular &
Developmental
Processes
Tissue and
Organismal
Physiology
Ecological
Processes and
Populations
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
23)
Bioinformatics Applications [2]
Genes
and
Gene
Structures
Reconstructing
Phylogeny,
Homology,
and
Comparitive
Approaches
Predicting
Protein
Sequence
Simulating
and
Understanding
Gene
Expression
Networks
Assembled
Genomes
Genes, Proteins,
RNAs
, and others
Sequence Variation of
Populations
Predicting
Three-Dimensional
Structures
of
Proteins
and
RNAs
Predicting
Functions
Modeling
Structures
of
Multi-
molecular
complexes
Predicting
Effects
of
Variation
Complexity
Modeling
Catalysis,
Molecular
Dynamics
Morphogenesis
and
Development
Simulation
of
Metabolic
and
Signal
Transduction
Pathways
Complete
Genomes
Biochemical
Pathways &
Processes
Cellular &
Developmental
Processes
Tissue and
Organismal
Physiology
Ecological
Processes and
Populations
Experiment
Computation
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
24)
Bioinformatics Applications:
Genomic Scale Experiments
Introduction
to
Bioinformatics
October 13, 03
9
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
25)
Others
HAP1
CYB2
ROX1
GPD2
CYT1
CYC7
+
+
-
-
-
+
Bioinformatics Applications:
Genomic Scale Experiments [2]
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
26)
Bioinformatics Applications:
Proteomic Scale Experiments
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
27)
Bioinformatics Application Areas
o
Data
archival
and
retrieval
o
Databases,
LIMS,
experimental
automation
o
Cross-species
comparisons
o
Experiments
in
yeast
are
easier
than
in
mice
where
they
are
easier
than
in
humans
o
Whole
Genome
characterization
o
Functional
annotation!
o
Drug
design
o
Protein/
ligand
interaction
studies
o
Designing
inhibitors
o
Docking,
structural
modeling
Introduction
to
Bioinformatics
October 13, 03
10
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
28)
Bioinformatics challenges
o
Biological
Redundancy
and
multiplicity:
o
Different
sequences
with
similar
structures
o
Organisms
with
similar
genes
o
Multiple
functions
of
single
genes
o
Grouping
of
genes
in
pathways
o
Sequence
redundancy
in
genomes
o
Significance
of
relationships
and
similarities
o
Signal
versus
Noise
o
Lack
of
Data
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
29)
Introduction to
NCBI’s Entrez
o
Overview:
o
Database
structure
o
Basic
Searching
o
Using
related
links/neighbors
o
Details,
Limits,
Preview
….
o
Entrez
field
qualifiers
o
Advanced
Boolean
queries
o
Practical
examples
and
hands-on
work!
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
30)
Introduction to
NCBI’s Entrez
[2]
What is

Entrez
???
Why is

Entrez
important???
Ë

cross-disciplinary
reference
database
Ë

convenient
query
and
retrieval
capabilities
Entrez
allows
the
retrieval
of
molecular
biology
data
and
bibliographic
citations
from
the

NCBI's
integrated
databases.
http://www.
ncbi
.
nlm.nih.
gov/
Entrez
/
Introduction
to
Bioinformatics
October 13, 03
11
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
31)
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
32)
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
33)
Introduction
to
Bioinformatics
October 13, 03
12
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
34)
Entrez
Databases
NCBI
Entrez's
integrated
databases
include:
o
PubMed
:
The
biomedical
literature
(
PubMed
)
o
Nucleotide
sequence
database
(
Genbank
)
o
Protein
sequence
database
o
Structure:
three-dimensional
macromolecular
structures
o
Genome:
complete
genome
assemblies
o
PopSet
:
population
study
data
sets
o
OMIM:
Online

Mendelian
Inheritance
in
Man
o
Taxonomy:
organisms
in

GenBank
o
Books:
online
books
o
ProbeSet
:
gene
expression
and

microarray
datasets
o
3D
Domains:
domains
from
Entrez
Structure
o
UniSTS
:
markers
and
mapping
data
o
SNP:
single
nucleotide
polymorphisms
o
CDD:
conserved
domains
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
35)
Entrez
Database Connections
PubMed
Nucleotide
Protein
Genomes
Structures
PopSet
Intra-Database Links:
Related Entries
Inter-database
Links
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
36)
Choose
a
database
Introduction
to
Bioinformatics
October 13, 03
13
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
37)
Enter
Query
Term
Click
“Go”

Button
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
38)
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
39)
Details
screen
Exact
query
syntax
Introduction
to
Bioinformatics
October 13, 03
14
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
40)
Number
of
Entries/Page
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
41)
Format,
Neighbors
&
Links
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
42)
Links
Pop-Up
Introduction
to
Bioinformatics
October 13, 03
15
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
43)
Entries
added
to
Clipboard
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
44)
Clipboard
screen
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
45)
!!!
???
Introduction
to
Bioinformatics
October 13, 03
16
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
46)
Same
as
without
quotes
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
47)
???
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
48)
!!!
Introduction
to
Bioinformatics
October 13, 03
17
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
49)
Wildcard

*

Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
50)
Indexed
terms
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
51)
Preview/Index
screen
Introduction
to
Bioinformatics
October 13, 03
18
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
52)
Index
for
“kinase

Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
53)
Boolean
term
inserted
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
54)
Limits
screen
Introduction
to
Bioinformatics
October 13, 03
19
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
55)
Database
dependent
fields
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
56)
Careful!!
Sticky!!
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
57)
Field
qualifier
Introduction
to
Bioinformatics
October 13, 03
20
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
58)
“Advanced
Boolean
Query

Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
59)
History
screen
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
60)
Introduction
to
Bioinformatics
October 13, 03
21
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
61)
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
62)
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
63)
Basic Searching (Summary)
o
Choose
database
o
Enter
query
term
o
Hit “
Go”
button
o
Examples:
o
camp
activated
protein
kinase
o
“camp
activated
protein
kinase

o
“camp
activated

“protein
kinase

o
“camp
dependent
protein
kinase”
o
“immunoglob
*

Introduction
to
Bioinformatics
October 13, 03
22
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
64)
Details, Limits, Preview

o
Details:
review
Entrez
’s
interpretation
of
the
query
term
o
Limits:
ways
to
restrict
a
search
to
a
defined
subset
of
the
database.
o
Indexes:
alphabetical
lists
of
terms
from
searchable
database
fields
o
History:
review,
recall
and
combine
past
searches
o
Clipboard:
temporarily
store
results
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
65)
Entrez
Field Qualifiers
o
Format:
term [qualifier]
o
Where:
o
Term

is
the
string
to
search
for
o
Qualifier

specify
the
field
to
search
in
G
DB
specific
G
one
of
WORD,
TITL,
MESH,
MAJR,
AUTH,
JOUR,
ECNO,
GENE,
DATE,
PDAT,
MDAT,
PAGE,
VOL,
KYWD,
ORGN,
ACCN,
PROT,
SLEN,
SQID,
SUBS,
PROP,
FKEY,
and
PTYP
o
Example:
Bourne
PE
[AUTH]
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
66)
Entrez
Field Qualifiers [2]
ACCN
accession
number
DATE
publication
year
FKEY
feature
key
JOUR
journal
name
MAJR
MeSH
major
topic
PAGE
first
page
PROP
property
PTYP
publication
type
TITL
title
word
SLEN
sequence
length
WORD
text
word
AUTH
author
name
ECNO
EC
number
GENE
gene
name
KYWD
keyword
MDAT
modification
date
ORGN
organism
PDAT
publication/creation
date
PROT
protein
name
SQID
sequence
id
SUBS
substance
VOL
volume
Introduction
to
Bioinformatics
October 13, 03
23
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
67)
Advanced Boolean Queries
o
Format:
term
[field]
operator
term
[field]

o
Where
Operator

is
any
of
:
o
AND

(intersection)
o
OR
(union)
o
BUTNOT

(difference)
o
Example:
Taylor
P
[AUTH]
AND

protein
kinase

o
Ranges:
term1:term2
[field]
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
68)
Using “Related
” Links
(aka
“Neighbors
”)
o
PubMed
Neighbors
o
Text &
MeSH
o
Protein
and
Nucleotide
Neighbors
o
BLAST
o
Macromolecular
Structure
Neighbors
o
VAST
o
Non
similarity
based:
references
within
text/annotation
o
VERY
helpful
in
identifying
related
records
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
69)
PubMed
specific
qualifier
Introduction
to
Bioinformatics
October 13, 03
24
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
70)
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
71)
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
72)
Exercises
o
1.
Work
through
the
Entrez
tutorial
at
http://www.
ncbi
.nlm
.nih
.
gov
/Database/tut1.html
o
2.
Find
references
about
shingles
and
facial
paralysis.
Display
the
records
in
the
format
that
shows
the
abstract
and
the
MeSH
headings.
How
does
PubMed
map
the
term,
shingles?
o
3. Find
murine
nucleic
acid
sequences
involved
in
apoptosis
and
cancer.
Display
all
of
the
retrieved
records
on
one
Web
page.
o
4.
Find
protein
sequences
related
to
AIDS
with
publications
in
Nature.
Save
this
search
strategy
so
the
search
can
be
run
again
at
a
later
date.
o
5.
Find
all
mouse
or
human
nucleotide
sequences
added
to
Entrez
in
1997.
How
many
structures
correspond
to
your
result
set?
Introduction
to
Bioinformatics
October 13, 03
25
Introduction to Bioinformatics•
http://www.
bioinformaticscourses.com/
bioinform/ •￿© Helge Weissig, 2003 (
73)
Reading Assignments
o
Review
Chapters
1
&
2
o
Study
Chapters
3,
5,
7
&
8