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{{Paper
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https://ceur-ws.org/Vol-1718/preface.pdf
Workshop
Notes
Second
international
workshop
on
Advances
in
Bioinformatics
and
Artificial
Intelligence:
Bridging
the
Gap
(BAI)
New-‐York
city,
USA,
July
11,
2016
http://bioinfo.uqam.ca/IJCAI_BAI2016/
Editors
:
Names
Affiliations
Abdoulaye
Baniré
Diallo
University
of
Quebec
at
Montreal
(Canada)
Diallo.abdoulaye@uqam.ca
http://labo.bioinfo.uqam.ca
Engelbert
Mephu
Nguifo
LIMOS,
Blaise
Pascal
University
(France)
mephu@isima.fr
http://www.isima.fr/mephu
Mohammed
Zaki
Rensselaer
Polytechnic
Institute,
NY
(USA)
zaki@cs.rpi.edu
http://www.cs.rpi.edu/~zaki/
Proceedings
managers
:
Wajdi
Dhifli
ISSB,
University
of
Evry-‐Val-‐d'Essonne,
Evry,
(France)
Jerry
Lonlac
Konlac
LIMOS,
Blaise
Pascal
University,
Clermont-‐Ferrand
(France)
Preface
The
goal
of
this
workshop
called
Bioinformatics
and
Artificial
Intelligence
(BAI)
is
to
bring
together
active
scholars
and
practitioners
at
the
frontiers
of
Artificial
Intelligence
(AI)
and
Bioinformatics.
AI
holds
a
tremendous
repertoire
of
algorithms
and
methods
that
constitute
the
core
of
different
topics
of
bioinformatics
and
computational
biology
research.
BAI
goals
are
twofolds
:
-‐ How
can
AI
techniques
contribute
to
bioinformatics
research
?,
and
-‐ How
can
bioinformatics
research
raise
new
fundamental
questions
in
AI
?
Contributions
clearly
points
out
answers
to
one
of
these
goals
focusing
on
AI
techniques
as
well
as
focusing
on
biological
problems.
Aims
and
Scope
:
AI
has
played
an
increasingly
important
role
in
the
analysis
of
sequence,
structure
and
functional
patterns
or
models
from
sequence
databases.
Bioinformatics
aims
to
store,
organize,
explore,
extract,
analyze,
interpret,
and
utilize
information
from
biological
data.
The
main
outcome
of
this
workshop
is
to
present
latest
results
in
this
exciting
area
at
the
intersection
of
biology
and
AI.
AI
approaches
can
revolutionize
new
age
of
bioinformatics
and
computational
biology
with
discoveries
in
basic
biology,
evolution,
metagenomics,
system
biology,
regulatory
genomics,
population
genomics
and
diseases,
structural
bioinformatics,
protein
docking,
next-‐generation
sequencing
(NGS)
data
processing,
chemoinformatics,
etc.
Bioinformatics
provides
opportunities
for
developing
novel
AI
methods.
Some
of
the
grand
challenges
in
bioinformatics
include
protein
structure
prediction,
homology
search,
epigenetics,
multiple
alignment
and
phylogeny
construction,
genomic
sequence
analysis,
gene
finding
and
gene
mapping,
as
well
as
applications
in
gene
expression
data
analysis,
drug
discovery
in
pharmaceutical
industry,
etc.
Two
questions
were
at
the
heart
of
this
workshop
:
-‐ How
can
AI
techniques
contribute
to
Bioinformatics
research,
and
in
particular
dealing
with
biological
problems
?
-‐ How
can
Bioinformatics
raise
new
fundamental
research
problem
for
AI
research
?
This
one-‐day
workshop
aims
at
bringing
together
scholars
and
practitioners
active
in
Artificial
Intelligence
driven
Bioinformatics,
to
present
and
discuss
their
research,
share
their
knowledge
and
experiences,
and
discuss
the
current
state
of
the
art
and
the
future
improvements
to
advance
the
intelligent
practice
of
computational
biology.
Workshop
topics
:
Topics
of
interest
lie
at
the
intersection
of
AI
and
Bioinformatics.
They
include,
but
are
not
limited
to,
the
following
inter-‐linked
topics:
Artificial
Intelligence
:
-‐ Constraints,
satisfiability
and
search
-‐ Knowledge
representation,
reasoning
and
logic
-‐ Machine
learning
and
data
mining
-‐ Planning
and
scheduling
-‐ Agent-‐based
and
multi-‐agent
systems
-‐ Web
and
knowledge-‐based
information
systems
-‐ Natural
language
processing
-‐ Uncertainty
Bioinformatics
:
-‐ Comparative
genomics
-‐ Evolution
and
phylogenetics
-‐ Epigenetics
-‐ Functional
genomics
-‐ Genome
organization
and
annotation
-‐ Genetic
variation
analysis
-‐ Metagenomics
-‐ Pathogen
informatics
-‐ Population
genetics,
variation
and
evolution
-‐ Protein
structure
and
function
prediction
and
analysis
-‐ Proteomics
-‐ Sequence
analysis
-‐ Systems
biology
and
networks
Workshop
contributions
:
This
year,
the
papers
submitted
to
the
workshop
were
carefully
peer-‐reviewed
by
at
least
three
members
of
the
program
committee
and
among
the
12
submissions,
7
papers
with
the
highest
scores
were
selected.
We
would
like
to
thank
all
the
PC
members
and
the
reviewers
for
their
reviews,
as
well
as
all
the
authors
for
their
contributions.
The
workshop
was
a
one
day
format
with
one
keynote
speakers,
two
invited
speaker,
and
seven
oral
presentations.
Keynote
Speaker
:
The
keynote
speaker
was
Dr.
Dmitri
Chklovskii,
leader
of
the
neuroscience
group
at
Simons
Foundation,
New-‐York
(USA).
His
talk
was
entitled
:
«
Biologically
inspired
machine
learning
».
Inspired
by
experimental
neuroscience
results
they
developed
a
family
of
online
algorithms
that
reduce
dimensionality,
cluster
and
discover
features
in
streaming
data.
The
novelty
of
their
approach
is
in
starting
with
similarity
matching
objective
functions
used
offline
in
Multidimensional
Scaling
and
Symmetric
Nonnegative
Matrix
Factorization.
They
derived
online
distributed
algorithms
that
can
be
implemented
by
biological
neural
networks
resembling
brain
circuits.
Such
algorithms
may
also
be
used
for
Big
Data
applications.
Invited
Speakers
:
The
first
invited
speaker
was
Dr.
Laxmi
Parida,
Distinguished
Research
Staff
Member
and
Manager
of
the
Computational
Genomics
Group
at
IBM,
New-‐York
(USA).
Her
talk
was
entitled
:
«
Watson
for
Genomics:
a
cognitive
approach
to
clinical
oncology
»
.
The
confluence
of
genomic
technologies,
algorithmics
and
cognitive
computing
has
brought
us
to
the
doorstep
of
widespread
usage
of
personalized
medicine.
She
talked
about
Watson
for
Genomics
that
attempts
to
integrate
the
current
state
of
knowledge
of
molecular
oncology
and
pharmacogenomics
with
the
ever-‐expanding
body
of
literature
to
assist
physicians
in
analyzing
and
acting
on
patient
genomic
profiles.
The
second
invited
speaker
was
Achille
Fokoué,
research
staff
member
at
IBM
New-‐York
(USA),
who
gives
a
talk
on
Tiresias,
a
system
for
predicting
Drug-‐Drug
Interactions
Through
Similarity-‐Based
Link
Prediction.
Drug-‐Drug
Interactions
(DDIs)
are
a
major
cause
of
preventable
adverse
drug
reactions
(ADRs),
causing
a
significant
burden
on
the
patients'
health
and
the
healthcare
system.
It
is
widely
known
that
clinical
studies
cannot
sufficiently
and
accurately
identify
DDIs
for
new
drugs
before
they
are
made
available
on
the
market.
In
addition,
existing
public
and
proprietary
sources
of
DDI
information
are
known
to
be
incomplete
and/or
inaccurate
and
so
not
reliable.
As
a
result,
there
is
an
emerging
body
of
research
on
in-‐silico
prediction
of
drug-‐drug
interactions.
He
presents
Tiresias,
a
framework
that
takes
in
various
sources
of
drug-‐related
data
and
knowledge
as
inputs,
and
provides
DDI
predictions
as
outputs.
The
process
starts
with
semantic
integration
of
the
input
data
that
results
in
a
knowledge
graph
describing
drug
attributes
and
relationships
with
various
related
entities
such
as
enzymes,
chemical
structures,
and
pathways.
The
knowledge
graph
is
then
used
to
compute
several
similarity
measures
between
all
the
drugs
in
a
scalable
and
distributed
framework.
The
resulting
similarity
metrics
are
used
to
build
features
for
a
large-‐scale
logistic
regression
model
to
predict
potential
DDIs.
We
highlight
the
novelty
of
our
proposed
approach
and
perform
thorough
evaluation
of
the
quality
of
the
predictions.
The
results
show
the
effectiveness
of
Tiresias
in
both
predicting
new
interactions
among
existing
drugs
and
among
newly
developed
and
existing
drugs.
Oral
presentations
:
The
seven
accepted
papers
were
then
presented,
among
which
six
new
contributions
(in
this
proceedings)
and
one
highlight
(from
the
journal
of
computational
biology)
devoted
on
prediction
of
ionizing
radiation
resistance
in
Bacteria
using
a
multiple
instance
learning
model.
Workshop
Program
:
Time
Event
08:00-‐08:45
Registration
08:45-‐09:00
Opening
ceremony
09:00-‐10:00
Keynote
speaker:
Dmitri
Chklovskii
Biologically
inspired
machine
learning.
10:00-‐10:30
César
Aguilar
and
Olga
Acosta.
Design
of
a
Extraction
System
for
Definitional
Contexts
from
Biomedical
Corpora
10:30-‐11:00
Coffee
Break
11:00-‐11:30
Sylvester
Olubolu
Orimaye,
Jojo
Sze-‐Meng
Wong
and
Judyanne
Sharmini
Gilbert
Fernandez.
Deep-‐Deep
Neural
Network
Language
Models
for
Predicting
Mild
Cognitive
Impairment
11:30-‐12:00
Ricardo
Souza
Jacomini,
David
Correa
Martins-‐Jr,
Felipe
Leno
Da
Silva
and
Anna
Helena
Reali
Costa.
A
Framework
for
Scalable
Inference
of
Temporal
Gene
Regulatory
Networks
based
on
Clustering
and
Multivariate
Analysis
12:00-‐12:30
Highlight
presentation
:
Sabeur
Aridhi,
Haitham
Sghaier,
Manel
Zoghlami,
Mondher
Maddouri
and
Engelbert
Mephu
Nguifo.
Prediction
of
ionizing
radiation
resistance
in
bacteria
using
a
multiple
instance
learning
model
12:30-‐14:00
Lunch
14:00-‐14:40
Invited
speaker:
Laxmi
Parida
Watson
for
Genomics:
a
cognitive
approach
to
clinical
oncology.
14:40-‐15:10
Sidak
Pal
Singh,
Sopan
Khosla,
Sajal
Rustagi,
Manisha
Patel
and
Dhaval
Patel.
SL-‐FII:
Syntactic
and
Lexical
Constraints
with
Frequency
based
Iterative
Improvement
for
Disease
Mention
Recognition
in
News
Headlines
15:10-‐15:40
Michael
Benedikt,
Rodrigo
Lopez-‐Serrano
and
Efthymia
Tsamoura.
Biological
Web
Services:
Integration,
Optimization,
and
Reasoning
15:40-‐16:00
Coffee
Break
16:00-‐16:30
Samuel
Sloate,
Vincent
Hsiao,
Nina
Charness,
Ethan
Lowman,
Christopher
J.
Maxey,
Sam
Guannan
Ren,
Nathan
Fields
and
Leora
Morgenstern.
Extracting
Protein-‐Reaction
Information
from
Tables
of
Unpredictable
Format
and
Content
in
the
Molecular
Biology
Literature
16:30-‐17:10
Invited
speaker:
Achille
Fokoue.
Tiresias:
A
system
for
predicting
Drug-‐Drug
Interactions
Through
Similarity-‐Based
Link
Prediction.
17:10-‐17:30
Discussion
and
Closing
session
Program
committee
:
Firstname
Name
Affiliation
Sabeur
Aridhi
Aalto
University,
School
of
Science,
Finland.
Abdoulaye
Baniré
Diallo
University
of
Quebec
at
Montreal
(UQAM),
Canada
Simon
De
Givry
INRA
–
UBIA,
France
Marcilio
De
Souto
LIFO/University
of
Orleans,
France
Wajdi
Dhifli
University
of
Quebec
At
Montreal,
Canada
Jason
Ernst
UCLA,
USA
Anna
Gambin
Institute
of
Informatics,
Warsaw
University,
Poland
Tu
Bao
Ho
Japan
Advanced
Institute
of
Science
and
Technology
Frédérique
Lisacek
Swiss
Institute
of
Bioinformatics,
Swizerland
Mondher
Maddouri
URPAH,
Faculty
of
sciences
El
Manar,
Tunis,
Tunisia
Osamu
Maruyama
Kyushu
University,
Japan
Engelbert
Mephu
Nguifo
LIMOS
-‐
Blaise
Pascal
University
–
CNRS,
France
Claire
Nédellec
INRA,
France
Gaurav
Pandey
Mount
Sinai
School
of
Medicine
David
Ritchie
INRIA,
France
Sushmita
Roy
University
of
Wisconsin,
Madison,
USA
Dechang
Xu
Harbin
Institute
of
Technology,
China
Mohammed
Zaki
RPI,
NY,
USA
Additional
reviewers
:
Thanks
to
the
following
additional
reviewers
for
their
help
during
the
reviewing
process
:
Eselle
Chaix,
Wojciech
Jaworski,
Om
Prakash
Pandey,
Jacek
Sroka,
Ana
Stanescu.
Acknowledgements
:
We
would
like
to
thank
the
following
people
for
their
involvement
on
workshop
duties
:
Wajdi
Dhifli
and
Jerry
Lonlac
Konlac.
Special
thanks
to
Wajdi
Dhifli
especially
for
the
workshop
website
management.
We
would
also
like
to
thank
all
authors
for
contributing
to
our
workshop
and
for
their
great
presentation
at
the
workshop.
Furthermore,
we
thank
all
reviewers
and
subreviewers
for
their
time
and
efforts
in
helping
us
build
an
interesting
program.
Abdoulaye
Baniré
Diallo
Engelbert
Mephu
Nguifo
Mohammed
Zaki
(Eds.)