medRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Ноя. 28, 2023
Identifying
causal
mutations
accelerates
genetic
disease
diagnosis,
and
therapeutic
development.
Missense
variants
present
a
bottleneck
in
diagnoses
as
their
effects
are
less
straightforward
than
truncations
or
nonsense
mutations.
While
computational
prediction
methods
increasingly
successful
at
for
known
genes,
they
do
not
generalize
well
to
other
genes
the
scores
calibrated
across
proteome.
To
address
this,
we
developed
deep
generative
model,
popEVE,
that
combines
evolutionary
information
with
population
sequence
data
achieves
state-of-the-art
performance
ranking
by
severity
distinguish
patients
severe
developmental
disorders
from
potentially
healthy
individuals.
popEVE
identifies
442
cohort
of
disorder
cases,
including
evidence
119
novel
without
need
gene-level
enrichment
overestimating
prevalence
pathogenic
population.
By
placing
on
unified
scale,
our
model
offers
comprehensive
perspective
distribution
fitness
entire
proteome
broader
human
provides
compelling
even
exceptionally
rare
single-patient
where
conventional
techniques
relying
repeated
observations
may
be
applicable.
Interactive
web
viewer
downloads
available
pop.evemodel.org.
Annual Review of Biomedical Data Science,
Год журнала:
2024,
Номер
7(1), С. 1 - 14
Опубликована: Апрель 10, 2024
Advances
in
biomedical
data
science
and
artificial
intelligence
(AI)
are
profoundly
changing
the
landscape
of
healthcare.
This
article
reviews
ethical
issues
that
arise
with
development
AI
technologies,
including
threats
to
privacy,
security,
consent,
justice,
as
they
relate
donors
tissue
data.
It
also
considers
broader
societal
obligations,
importance
assessing
unintended
consequences
research
biomedicine.
In
addition,
this
highlights
challenge
rapid
against
backdrop
disparate
regulatory
frameworks,
calling
for
a
global
approach
address
concerns
around
misuse,
surveillance,
equitable
distribution
AI's
benefits
burdens.
Finally,
number
potential
solutions
these
quandaries
offered.
Namely,
merits
advocating
collaborative,
informed,
flexible
balances
innovation
individual
rights
public
welfare,
fostering
trustworthy
AI-driven
healthcare
ecosystem,
discussed.
Alzheimer s & Dementia,
Год журнала:
2023,
Номер
19(12), С. 5970 - 5987
Опубликована: Сен. 28, 2023
Experimental
models
are
essential
tools
in
neurodegenerative
disease
research.
However,
the
translation
of
insights
and
drugs
discovered
model
systems
has
proven
immensely
challenging,
marred
by
high
failure
rates
human
clinical
trials.
medRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Ноя. 28, 2023
Identifying
causal
mutations
accelerates
genetic
disease
diagnosis,
and
therapeutic
development.
Missense
variants
present
a
bottleneck
in
diagnoses
as
their
effects
are
less
straightforward
than
truncations
or
nonsense
mutations.
While
computational
prediction
methods
increasingly
successful
at
for
known
genes,
they
do
not
generalize
well
to
other
genes
the
scores
calibrated
across
proteome.
To
address
this,
we
developed
deep
generative
model,
popEVE,
that
combines
evolutionary
information
with
population
sequence
data
achieves
state-of-the-art
performance
ranking
by
severity
distinguish
patients
severe
developmental
disorders
from
potentially
healthy
individuals.
popEVE
identifies
442
cohort
of
disorder
cases,
including
evidence
119
novel
without
need
gene-level
enrichment
overestimating
prevalence
pathogenic
population.
By
placing
on
unified
scale,
our
model
offers
comprehensive
perspective
distribution
fitness
entire
proteome
broader
human
provides
compelling
even
exceptionally
rare
single-patient
where
conventional
techniques
relying
repeated
observations
may
be
applicable.
Interactive
web
viewer
downloads
available
pop.evemodel.org.
