Cells,
Journal Year:
2024,
Volume and Issue:
13(4), P. 340 - 340
Published: Feb. 14, 2024
Parkinson’s
Disease
(PD)
is
a
common
neurodegenerative
disease
which
manifests
with
motor
features,
such
as
bradykinesia,
resting
tremor,
rigidity,
and
postural
instability.
Using
the
non-invasive
technique
of
saliva
collection,
we
designed
systematic
review
to
answer
question
“Are
salivary
biomarkers
reliable
for
diagnosis
Disease?”.
Following
inclusion
exclusion
criteria,
30
studies
were
included
in
this
(according
PRISMA
statement
guidelines).
Mostly
proteins
reported
potential
saliva.
Based
on
meta-analysis,
PD
patients,
levels
total
alpha-synuclein
significantly
decreased,
those
oligomeric
increased.
Also,
according
pooled
AUC,
heme
oxygenase-1
demonstrated
significant
predictive
value
saliva-based
diagnosis.
In
conclusion,
some
biomarkers,
especially
alpha-synuclein,
can
be
altered
could
reliably
useful
early
differentiating
other
synucleopathies.
Computational and Structural Biotechnology Journal,
Journal Year:
2024,
Volume and Issue:
23, P. 2289 - 2303
Published: May 21, 2024
The
rapid
progression
of
genomics
and
proteomics
has
been
driven
by
the
advent
advanced
sequencing
technologies,
large,
diverse,
readily
available
omics
datasets,
evolution
computational
data
processing
capabilities.
vast
amount
generated
these
advancements
necessitates
efficient
algorithms
to
extract
meaningful
information.
K-mers
serve
as
a
valuable
tool
when
working
with
large
offering
several
advantages
in
speed
memory
efficiency
carrying
potential
for
intrinsic
biological
functionality.
This
review
provides
an
overview
methods,
applications,
significance
k-mers
genomic
proteomic
analyses,
well
utility
absent
sequences,
including
nullomers
nullpeptides,
disease
detection,
vaccine
development,
therapeutics,
forensic
science.
Therefore,
highlights
pivotal
role
addressing
current
problems
underscores
their
future
breakthroughs
research.
International Journal of Molecular Sciences,
Journal Year:
2024,
Volume and Issue:
25(2), P. 1168 - 1168
Published: Jan. 18, 2024
Alzheimer’s
Disease
(AD)
is
the
most
common
neurodegenerative
disease
which
manifests
with
progressive
cognitive
impairment,
leading
to
dementia.
Considering
noninvasive
collection
of
saliva,
we
designed
systematic
review
answer
question
“Are
salivary
biomarkers
reliable
for
diagnosis
Disease?”
Following
inclusion
and
exclusion
criteria,
30
studies
were
included
in
this
(according
PRISMA
statement
guidelines).
Potential
include
mainly
proteins,
metabolites
even
miRNAs.
Based
on
meta-analysis,
AD
patients,
levels
beta-amyloid42
p-tau
significantly
increased,
t-tau
lactoferrin
decreased
at
borderline
statistical
significance.
However,
according
pooled
AUC,
showed
a
significant
predictive
value
salivary-based
diagnosis.
In
conclusion,
potential
markers
such
as
beta-amyloid42,
tau
can
be
detected
saliva
could
reliably
support
early
disease.
Proteomes,
Journal Year:
2024,
Volume and Issue:
12(3), P. 25 - 25
Published: Sept. 6, 2024
High-throughput
omics
technologies
have
dramatically
changed
biological
research,
providing
unprecedented
insights
into
the
complexity
of
living
systems.
This
review
presents
a
comprehensive
examination
current
landscape
high-throughput
pipelines,
covering
key
technologies,
data
integration
techniques
and
their
diverse
applications.
It
looks
at
advances
in
next-generation
sequencing,
mass
spectrometry
microarray
platforms
highlights
contribution
to
volume
precision.
In
addition,
this
critical
role
bioinformatics
tools
statistical
methods
managing
large
datasets
generated
by
these
technologies.
By
integrating
multi-omics
data,
researchers
can
gain
holistic
understanding
systems,
leading
identification
new
biomarkers
therapeutic
targets,
particularly
complex
diseases
such
as
cancer.
The
also
electronic
health
records
(EHRs)
potential
for
cloud
computing
big
analytics
improve
storage,
analysis
sharing.
Despite
significant
advances,
there
are
still
challenges
complexity,
technical
limitations
ethical
issues.
Future
directions
include
development
more
sophisticated
computational
application
advanced
machine
learning
techniques,
which
addressing
heterogeneity
datasets.
aims
serve
valuable
resource
practitioners,
highlighting
transformative
advancing
personalized
medicine
improving
clinical
outcomes.
Pathogens,
Journal Year:
2025,
Volume and Issue:
14(2), P. 126 - 126
Published: Feb. 1, 2025
Fungal
infections
are
a
significant
global
health
challenge,
causing
approximately
3.8
million
deaths
annually,
with
immunocompromised
populations
particularly
at
risk.
Traditional
antifungal
therapies,
including
azoles,
echinocandins,
and
polyenes,
face
limitations
due
to
rising
resistance,
toxicity,
inadequate
treatment
options.
This
review
explores
innovative
strategies
for
preventing
managing
fungal
infections,
such
as
vaccines,
peptides,
nanotechnology,
probiotics,
immunotherapy.
Vaccines
offer
promising
avenues
long-term
protection,
despite
difficulties
in
their
development
complexity
immune
evasion
mechanisms.
Antifungal
peptides
provide
novel
class
of
agents
broad-spectrum
activity
reduced
resistance
risk,
whilst
nanotechnology
enables
targeted,
effective
drug
delivery
systems.
Probiotics
show
potential
vulvovaginal
candidiasis,
by
maintaining
microbial
balance.
Immunotherapy
leverages
system
modulation
enhance
defenses,
omics
technologies
deliver
comprehensive
insights
into
biology,
paving
the
way
therapeutic
vaccine
targets.
While
these
approaches
hold
immense
promise,
challenges
cost,
accessibility,
translational
barriers
remain.
A
coordinated
effort
among
researchers,
clinicians,
policymakers
is
critical
advancing
addressing
burden
effectively.
PLoS Computational Biology,
Journal Year:
2023,
Volume and Issue:
19(3), P. e1010921 - e1010921
Published: March 6, 2023
The
availability
of
patient
cohorts
with
several
types
omics
data
opens
new
perspectives
for
exploring
the
disease’s
underlying
biological
processes
and
developing
predictive
models.
It
also
comes
challenges
in
computational
biology
terms
integrating
high-dimensional
heterogeneous
a
fashion
that
captures
interrelationships
between
multiple
genes
their
functions.
Deep
learning
methods
offer
promising
multi-omics
data.
In
this
paper,
we
review
existing
integration
strategies
based
on
autoencoders
propose
customizable
one
whose
principle
relies
two-phase
approach.
first
phase,
adapt
training
to
each
source
independently
before
cross-modality
interactions
second
phase.
By
taking
into
account
source’s
singularity,
show
approach
succeeds
at
advantage
all
sources
more
efficiently
than
other
strategies.
Moreover,
by
adapting
our
architecture
computation
Shapley
additive
explanations,
model
can
provide
interpretable
results
multi-source
setting.
Using
from
different
TCGA
cohorts,
demonstrate
performance
proposed
method
cancer
test
cases
tasks,
such
as
classification
tumor
breast
subtypes,
well
survival
outcome
prediction.
We
through
experiments
great
performances
seven
datasets
various
sizes
some
interpretations
obtained.
Our
code
is
available
(
https://github.com/HakimBenkirane/CustOmics
).
Journal of Biomedical Informatics,
Journal Year:
2023,
Volume and Issue:
142, P. 104373 - 104373
Published: April 27, 2023
Cancer
is
the
second
leading
cause
of
death
globally,
trailing
only
heart
disease.
In
United
States
alone,
1.9
million
new
cancer
cases
and
609,360
deaths
were
recorded
for
2022.
Unfortunately,
success
rate
drug
development
remains
less
than
10%,
making
disease
particularly
challenging.
This
low
largely
attributed
to
complex
poorly
understood
nature
etiology.
Therefore,
it
critical
find
alternative
approaches
understanding
biology
developing
effective
treatments.
One
such
approach
repurposing,
which
offers
a
shorter
timeline
lower
costs
while
increasing
likelihood
success.
this
review,
we
provide
comprehensive
analysis
computational
biology,
including
systems
multi-omics,
pathway
analysis.
Additionally,
examine
use
these
methods
repurposing
in
cancer,
databases
tools
that
are
used
research.
Finally,
present
case
studies
discussing
their
limitations
offering
recommendations
future
research
area.
