Drug Discovery Today,
Journal Year:
2024,
Volume and Issue:
29(6), P. 103990 - 103990
Published: April 23, 2024
The
enormous
growth
in
the
amount
of
data
generated
by
life
sciences
is
continuously
shifting
field
from
model-driven
science
towards
data-driven
science.
need
for
efficient
processing
has
led
to
adoption
massively
parallel
accelerators
such
as
graphics
units
(GPUs).
Consequently,
development
bioinformatics
methods
nowadays
often
heavily
depends
on
effective
use
these
powerful
technologies.
Furthermore,
progress
computational
techniques
and
architectures
continues
be
highly
dynamic,
involving
novel
deep
neural
network
models
artificial
intelligence
(AI)
accelerators,
potentially
quantum
future.
These
are
expected
disruptive
a
whole
drug
discovery
particular.
Here,
we
identify
three
waves
acceleration
their
applications
context:
(i)
GPU
computing,
(ii)
AI
(iii)
next-generation
computers.
Bioinformatics Advances,
Journal Year:
2023,
Volume and Issue:
3(1)
Published: Jan. 1, 2023
Abstract
Summary
The
transformer-based
language
models,
including
vanilla
transformer,
BERT
and
GPT-3,
have
achieved
revolutionary
breakthroughs
in
the
field
of
natural
processing
(NLP).
Since
there
are
inherent
similarities
between
various
biological
sequences
languages,
remarkable
interpretability
adaptability
these
models
prompted
a
new
wave
their
application
bioinformatics
research.
To
provide
timely
comprehensive
review,
we
introduce
key
developments
by
describing
detailed
structure
transformers
summarize
contribution
to
wide
range
research
from
basic
sequence
analysis
drug
discovery.
While
applications
diverse
multifaceted,
identify
discuss
common
challenges,
heterogeneity
training
data,
computational
expense
model
interpretability,
opportunities
context
We
hope
that
broader
community
NLP
researchers,
bioinformaticians
biologists
will
be
brought
together
foster
future
development
inspire
novel
unattainable
traditional
methods.
Supplementary
information
data
available
at
Bioinformatics
Advances
online.
Nature,
Journal Year:
2024,
Volume and Issue:
629(8010), P. 136 - 145
Published: April 3, 2024
Abstract
Human
centromeres
have
been
traditionally
very
difficult
to
sequence
and
assemble
owing
their
repetitive
nature
large
size
1
.
As
a
result,
patterns
of
human
centromeric
variation
models
for
evolution
function
remain
incomplete,
despite
being
among
the
most
rapidly
mutating
regions
2,3
Here,
using
long-read
sequencing,
we
completely
sequenced
assembled
all
from
second
genome
compared
it
finished
reference
4,5
We
find
that
two
sets
show
at
least
4.1-fold
increase
in
single-nucleotide
when
with
unique
flanks
vary
up
3-fold
size.
Moreover,
45.8%
cannot
be
reliably
aligned
standard
methods
emergence
new
α-satellite
higher-order
repeats
(HORs).
DNA
methylation
CENP-A
chromatin
immunoprecipitation
experiments
26%
differ
kinetochore
position
by
>500
kb.
To
understand
evolutionary
change,
selected
six
chromosomes
31
orthologous
common
chimpanzee,
orangutan
macaque
genomes.
Comparative
analyses
reveal
nearly
complete
turnover
HORs,
characteristic
idiosyncratic
changes
HORs
each
species.
Phylogenetic
reconstruction
haplotypes
supports
limited
no
recombination
between
short
(p)
long
(q)
arms
across
reveals
novel
share
monophyletic
origin,
providing
strategy
estimate
rate
saltatory
amplification
mutation
DNA.
Progress in Energy and Combustion Science,
Journal Year:
2024,
Volume and Issue:
102, P. 101142 - 101142
Published: Jan. 19, 2024
Lithium-ion
batteries
play
a
pivotal
role
in
wide
range
of
applications,
from
electronic
devices
to
large-scale
electrified
transportation
systems
and
grid-scale
energy
storage.
Nevertheless,
they
are
vulnerable
both
progressive
aging
unexpected
failures,
which
can
result
catastrophic
events
such
as
explosions
or
fires.
Given
their
expanding
global
presence,
the
safety
these
potential
hazards
serious
malfunctions
now
major
public
concerns.
Over
past
decade,
scholars
industry
experts
intensively
exploring
methods
monitor
battery
safety,
spanning
materials
cell,
pack
system
levels
across
various
spectral,
spatial,
temporal
scopes.
In
this
Review,
we
start
by
summarizing
mechanisms
nature
failures.
Following
this,
explore
intricacies
predicting
evolution
delve
into
specialized
knowledge
essential
for
data-driven,
machine
learning
models.
We
offer
an
exhaustive
review
spotlighting
latest
strides
fault
diagnosis
failure
prognosis
via
array
approaches.
Our
discussion
encompasses:
(1)
supervised
reinforcement
integrated
with
models,
apt
faults/failures
probing
causes
protocols
at
cell
level;
(2)
unsupervised,
semi-supervised,
self-supervised
learning,
advantageous
harnessing
vast
data
sets
modules/packs;
(3)
few-shot
tailored
gleaning
insights
scarce
examples,
alongside
physics-informed
bolster
model
generalization
optimize
training
data-scarce
settings.
conclude
casting
light
on
prospective
horizons
comprehensive,
real-world
prognostics
management.
Genome Medicine,
Journal Year:
2023,
Volume and Issue:
15(1)
Published: June 14, 2023
Advances
in
clinical
genetic
testing,
including
the
introduction
of
exome
sequencing,
have
uncovered
molecular
etiology
for
many
rare
and
previously
unsolved
disorders,
yet
more
than
half
individuals
with
a
suspected
disorder
remain
after
complete
evaluation.
A
precise
diagnosis
may
guide
treatment
plans,
allow
families
to
make
informed
care
decisions,
permit
participate
N-of-1
trials;
thus,
there
is
high
interest
developing
new
tools
techniques
increase
solve
rate.
Long-read
sequencing
(LRS)
promising
technology
both
increasing
rate
decreasing
amount
time
required
diagnosis.
Here,
we
summarize
current
LRS
technologies,
give
examples
how
they
been
used
evaluate
complex
variation
identify
missing
variants,
discuss
future
applications
LRS.
As
costs
continue
decrease,
will
find
additional
utility
space
fundamentally
changing
pathological
variants
are
discovered
eventually
acting
as
single-data
source
that
can
be
interrogated
multiple
times
service.
