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
.
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