Bioinformatics - Department of Spatial Information Science and ...

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2 Οκτ 2013 (πριν από 3 χρόνια και 2 μήνες)

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Bioinformatics

GIS Applications

Anatoly Petrov

Bioinformatics


(in

a

strict

sense)

a

branch

of

science

dealing

with

storage,

retrieval

and

analysis

or

prediction

of

the

composition

or

the

structure

of

biomolecules

(
sequence

analysis
)


-

nucleic

acids

(DNA,

RNA)

-

genomics


-

proteins

-

proteomics



(in

a

wider

sense)

the

intersection

of

biology

and

computer

science

(eg
.
,

computational

biogeography)

Bioinformatics

Institute
(VBI) sponsored a
major conference focused on the interface

between GIS and bioinformatics:
“GIS
Applications to Bioinformatics”

(May 16

17,
2001, Blacksburg, Virginia).

A Gene Map of the Human Genome

The Human Transcript Map

Chromosome X

3
-
dimentional reconstruction

of the amicyanin
-

an enzyme participating

in respiration

Chromosome structure

C
hromosomal

DNA

is

packaged

into

a

compact

structure

with

the

help

of

specialized

proteins

called

histones
.

The

fundamental

packing

unit

is

known

as

a

nucleosome
.

Sequence

features

that

appear

to

be

spatially

disconnected

according

to

a

linear

representation

of

a

genome,

may

actually

be

close

neighbors

due

to

the

folding

of

DNA

into

a

3
-
dimensional

molecule
.


Nucleosome

GenoSIS
-

Genome Spatial Information
System

Applications:



-
thematic mapping and visualization

-
exploratory spatial data analysis

(ESDA)

(
ESRI ArcGIS


visualization tool


+

Oracle Spatial



object
-
relational database)

Set of questions for the ESDA




Where

do

we

find

consensus

sequence

elements

(CSEs)?

How

many

elements

are

there

at

that

genomic

region?





Is

there

regularity

in

their

distribution?

What

is

the

nature

of

that

regularity?

Why

should

the

spatial

distributional

pattern

exhibit

regularity?






Are

CSEs

found

throughout

the

genome?

What

are

the

limits

to

where

they

are

found?

Why

do

those

limits

constrain

its

distribution?





Are

there

regulatory

elements

spatially

associated

with

a

gene

with

a

particular

molecular

function?

Do

these

regulatory

elements

and

genes

usually

occur

together

in

the

same

places?

Why

should

they

be

spatially

associated?





Has

a

particular

gene

always

been

there?

In

which

organism

did

it

first

emerge

or

become

obvious?

How

has

it

changed

spatially

(through

evolutionary

time)?





What

factors

have

influenced

its

duplication

or

deletion

in

the

genome?

What

factors

have

constrained

its

spread?




Using GIS for thematic genome mapping

Application of ArcView for genome mapping
and spatial analysis

Biogeography


Prediction (reconstruction) of species distribution


Ther
e

are

two

main

datasets

that

are

fundamental

in

obtaining

good

prediction

on

a

species

distribution

map
:

species

occurrence

data

and

environmental

information
.


-

In

the

past

(paleobiogeography

and

paleoclimatology
;



ex
.
,

NOAA’s

Paleoclimatology

Program)


-

At

present

(eg
.
,

Environment

Australia’s

Species

Mapper)


-

In

future

(eg
.
,

some

of

the

Lifemapper

products)

Methods

Algorithms


GARP,

environmental

envelope

(BIOCLIM),

e
-
ball,

“image”

(Bayesian

classification

method)

Habitat Digitizer Extension

(HDE) to ArcView

use
s

a

hierarchical

classification

scheme

to

delineate

habitats

by

visually

interpreting

georeferenced

images

such

as

aerial

photographs,

satellite

images,

and

side

scan

sonar
.


HDE
allows users to create custom classification schemes and rapidly
delineate and attribute polygons using simple menus.

Deducing potential species distribution


using BIOCLIM



Query database to retrieve records of


species locations.



For each species location, interpolate


values of essential climatic variables.



Calculate the climatic envelope bounding


all the species records.



At the resolution specified, identify all


other sites in the landscape that fall


within the climatic envelope.



Plot the sites identified on a base map.



Deliver the map to the user.


Environment Australia’s Species Mapper

Lifemapper

1
.

The

species

occurrence

data

is

gathered

from

a

number

of

biological

collection
s

housed

at

several

museums

and

herbaria

worldwide
.

Those

institutions

have

their

specimen

databases

linked

and

integrated

through

The

Species

Analyst

project
.


2
.

T
he

environmental

information

is

represented

as

a

set

of

geographic

layers
.

Each

layer

displays

one

particular

environmental

parameter,

such

as

temperature,

rainfall,

land

use,

elevation,

among

others
.


3
.

Using

data

from

those

two

datasets,

GARP

tries

to

find

nonrandom

correlations

between

species

occurrence

data

and

the

values

of

the

environmental

parameters

where

the

species

occur

or

do

not

occur
.


G

Genetic

A

Algorithm

for

R

Ruleset

P

Production

Paleobiogeography

Holocene

Evolution

of

the

Southern

Washington

and

Northern

Oregon

Shelf

and

Coast
.

3
-
D Flythrough

animation

NOAA’s Paleoclimatology Program

Pollen Viewer

THE END