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2 Οκτ 2013 (πριν από 3 χρόνια και 10 μήνες)

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EMBER

EMBnet

teams

:

University

of

Manchester

(United

Kingdom),

Swiss

Institute

of

Bioinformatics

(Switzerland),

University

of

Nijmegen

(The

Netherlands),

University

of

the

Western

Cape

(South

Africa),

European

Bioinformatics

Institute

(United

Kingdom),

Instituto

Gulbenkian

de

Ciencia

(Portugal),

ULB

University

of

Bruxelles

(Belgium),

Canada

Institute

for

Marine

Biosciences

(Canada),

Research

Institute

for

Genetic

engineering

and

Biotechnology

(Turkey),

Expert

Center

for

Taxonomic

Identification

(The

Netherlands)
.


The

project

coordinator

is

Professor

Terri

Attwood

from

the

University

of

Manchester
:

the

principal

authors

include

Ioannis

Selimas,

from

the

Manchester

group

and

Marc

Brugman

from

the

Expert

Centre

for

Taxonomic

Identification
.

Ember is a new tutorial on sequence analysis and bio computing developed
by several EMBnet teams within an EC framework. The course can be used by
independent users as well as material for academic purposes and is
structured by chapters of gradually increasing difficulty. Each chapter has
several sections: AIM, INFO (presenting theoretical aspects of the subjects
tackled), INSTRUCTIONS (presenting practical exercises on line) Quiz and
References
.


EUROPEAN MULTIMEDIA BIOINFORMATICS EDUCATIONAL RESOURCE

a new tutorial on sequence analysis and bio computing

Figure

1
.

Ember

presentation

page
:

here

chapter

3

of

the

tutorial,

containing

a

det ai l ed

pr esent at i on

of

the

most

important

secondary

databases
:

PROSITE,

eMOTIF,

PRINTS,

BLOCKS,

Pfam

and

InterPro
.


The

information

presented

is

supported

by

multiple

web

links,

illustrative

animations

and

practical

exercises
.

The

tutorial

is

addressed

to

a

wide

variety

of

researchers

(Master

and

PhD

students,

post
-
docs,

junior

and

senior

researchers)

from

all

Molecular

Biology

and

Bioinformatics

departments,

covering

broad

analysis

areas

such

as
:




DNA

analysis
:

DNA

translation

(chapter

1
),

similarity

searches

(chapter

2
),

multiple

alignments

(chapter

4
),

restriction

mapping

(chapter

13
)
;

determination

of

gene

structure

through

intron/exon

prediction

(chapter

10
)
;

inference

of

protein

coding

sequence

through

open

reading

frame

(ORF)

analysis

(chapter

10
)
;


Protein

analysis
:

retrieving

protein

sequences

from

databases

(chapter

1
)
;

classifying

proteins

into

families

(chapter

3
)
;

searching

primary

and

secondary

protein

databases

(chapter

3
)
;

finding

the

best

alignment

between

two

or

more

proteins

(chapter

4
)
;

computing

amino
-
acid

composition,

molecular

weight,

isoelectric

point,

and

other

parameters

(chapter

5
)
;

computing

hydrophobicity/hydrophilicity

p r o f i l e s,

l o c a t i n g

m e m b r a n e
-
s p a n n i n g

s e g m e n t s

( c h a p t e r

5
)
;

p r e d i c t i n g

e l e m e n t s

of

secondary

structure

(chapter

5
)
;

visualizing

the

protein

structure

in

3
D

(chapter

6
)
;

predicting

a

protein

3
D

structure

from

its

sequence

(chapters

7

and

8
)
;

finding

evolutionary

relationships

between

proteins

(chapter

12
)
.


Genome

analysis
:

analysing

genomic

sequences
;

locating

genes

in

a

genome
;

displaying

genomes
;

parsing

a

eukaryotic

genome

sequence
:

GenScan

(chapter

10
),

etc
.


The

tutorial

presents

a

wide

variety

of

tools

and

websites

for

multiple

types

of

analysis
:

similarity

searches

tools

(BLAST,

PSI
-
BLAST)
;

protein

family

analysis

through

databases

searches

(PROSITE,

eMOTIF,

BLOCKS,

PRINTS,

Pfam)
;

multiple

alignment

tools

(Clustal,

DIALIGN,

T
-
COFFEE,

CINEMA,

Jalview)
;

physicochemical

parameters

and

profile

prediction

(ProtParam

and

ProtScale)
;

transmembrane

helix

prediction

(MEMSAT,

TMpred)
;

secondary

structure

prediction

(Jpredet,

NNPREDICT)
;

3
D

prediction,

comparison

and

visualisation

(RasMol,

QuickPDB,

Cn
-
3
D)
;

homology

modelling

(Swiss

Model,

Geno
-
3
D)
;

fold

recognition

(GenThreader,

3
D
-
PSSM)
;

phylogenetic

analysis

(Pylip)
;

SRS

(sequence

retrieval),

etc
.





Figure

7
.

“Human

Genome”

case

study

chapter

proposes

a

complex

analysis

using

advanced

bioinformatics

tools

in

concrete

research

applications
.

Using

a

genomic

fragment

of

the

human

chromosome

6
,

the

students

are

invited

to

find

potential

genes

in

this

fragment

with

GenMark

and

GENESCAN

software
.

They

can

then

compare

the

results

and

assess

their

reliability

using

GeneQuiz,

an

integrated

system

for

large
-
scale

biological

sequence

analysis,

and

current

database

annotation

in

Human

Genome

project

-

Ensembl
.

Figure

6
.

In

the

“Sickle

cell

haemoglobin”

case

study

chapter

the

users

can

compare

sickle

cell

and

normal

β

globin

sequences

to

reveal

the

nature

of

the

sickle

cell

mutation
.
The

exercise

integrates

several

databases

searches

and

multiple

tools
:
SRS,

CLUSTALW,

Restriction

map

as

well

as

an

advanced

RasMol

session

by

scripting

files

to

visualise

the

mutant

haemoglobin

and

the

interaction

between

mutant

β

chains

and

further

amino

acid

side

chains

in

the

vicinity

of

mutated

Val
6

residue
.


In

this

representation,

the

two

central

mutant

β

chains

are

highlighted

as

white

and

orange

wireframes
.

Also

highlighted

are

the

side

chains

of

the

central

Val
6

mutation

and

porphyrin

prosthetic

group

(in

CPK

coloured

space
-
filling

models)
.

Both

the

porphyrin

prosthetic

groups

(blue)

and

the

mutant

Val
6

residues

(red)

are

represented

as

space

filling

models
.

Highlighted

in

yellow

are

the

side
-
chains

in

the

vicinity

of

Val
6

at

the

interface

of

the

two

haemoglobin

molecules
.

Viorica Ghita*, Valérie Ledent*, Robert Herzog*, Terry Attwood
#
, Ioannis Selimas
#
, Marc Brugman
$

*
Belgian

EMBnet

Node



BEN
.

Laboratoire

de

Bioinformatique
.

Université

Libre

de

Bruxelles
.

Campus

de

la

Plaine



Bat

NO
.

Bd

du

Triomphe
.

1050

Bruxelles
.

#
UMBER,

the

University

of

Manchester

Specialist

Node

of

EMBnet,

School

of

Biological

Sciences,

Oxford

Road,

M
13

9
PL,

Manchester
.

$
University

of

Amsterdam,

Mauritkade

61
,

1092

AD

Amsterdam,

The

Netherlands

Figure

2
.

The

tutorial

presents

the

most

important

tools

for

multiple

sequence

alignment,

rich

information

about

manual

and

automatic

multiple

alignment

tools,

exercises

and

links

to

various

software

and

alignment

databases

(chapter

4
)
.

Figure

3
.

Physicochemical

parameters

computation

tools

for

molecular

weight,

theoretical

pI,

amino

acid

composition,

atomic

composition,

extinction

coefficient,

hydropathy,

chain

flexibility,

solvent
-
accessible

surface

area,

etc
.
,

software

tools

to

predict

the

transmembrane

topology

of

proteins

and

some

secondary

structure

prediction

software

are

presented

in

tutorial

(chapter

5
)
.

Figure

4
.

Figure

4
.

A

detailed

presentation

of

Protein

Data

Bank,

the

principal

repository

of

biological

macromolecule

structures,

and

some

structure

classification

resources

(CATH,

SCOP,

EC
-
>PDB)

are

presented

in

Chapter

6

“Fold

classification”,

as

well

as

visualisation

and

comparison

of

protein

3
D

structure

with

various

Molecular

Structure

Viewers
:

RasmOl,

QuickPDB,

Deep

View,

Cn
-
3
D
.

Figure

5
.

Different

protein

structure

viewers,

presented

in

the

tutorial,

displaying

the

ubiquitin
-
like

signalling

protein,

Nedd
8

(PDB

ID
:

1
NND)
.

(A)

Deep

View,

(B)

Rasmol,

(C)

QuickPDB

and

(D)

CN
3
D
.

(A)

illustrates

classical

ball

and

stick

mode,

(B)

cartoon

mode,

(C)

a

wireframe

α
-
carbon

trace,

with

a

small

section

of

the

structure

highlighted

in

blue,

and

(D)

a

hybrid

display

with

amino

acid

chains

in

cartoon

mode

and

non
-
amino

acid

atoms

in

space
-
filling

mode
.