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Pattern discovery in adverse event data
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The Expanding Landscape of Alternative Splicing Variation in Human Populations.
Alternative splicing is a tightly regulated biological process by which the number of gene products for any given gene can be greatly expanded. Genomic variants in splicing regulatory sequences can disrupt splicing and cause disease. Recent developments in sequencing technologies and computational biology have allowed researchers to investigate alternative splicing at an unprecedented scale and resolution. Population-scale transcriptome studies have revealed many naturally occurring genetic variants that modulate alternative splicing and consequently influence phenotypic variability and disease susceptibility in human populations. Innovations in experimental and computational tools such as massively parallel reporter assays and deep learning have enabled the rapid screening of genomic variants for their causal impacts on splicing. In this review, we describe technological advances that have greatly increased the speed and scale at which discoveries are made about the genetic variation of alternative splicing. We summarize major findings from population transcriptomic studies of alternative splicing and discuss the implications of these findings for human genetics and medicine
Fast Quantum Algorithms for Trace Distance Estimation
In quantum information, trace distance is a basic metric of
distinguishability between quantum states. However, there is no known efficient
approach to estimate the value of trace distance in general. In this paper, we
propose efficient quantum algorithms for estimating the trace distance within
additive error between mixed quantum states of rank .
Specifically, we first provide a quantum algorithm using queries to the quantum circuits that prepare the
purifications of quantum states. Then, we modify this quantum algorithm to
obtain another algorithm using samples of
quantum states, which can be applied to quantum state certification. These
algorithms have query/sample complexities that are independent of the dimension
of quantum states, and their time complexities only incur an extra factor. In addition, we show that the decision version of low-rank trace
distance estimation is -complete.Comment: Final version. Improve proof details, add BQP-completeness. 31 pages,
2 algorithms, 2 tables, 2 figure
Model and Integrate Medical Resource Available Times and Relationships in Verifiably Correct Executable Medical Best Practice Guideline Models (Extended Version)
Improving patient care safety is an ultimate objective for medical
cyber-physical systems. A recent study shows that the patients' death rate is
significantly reduced by computerizing medical best practice guidelines. Recent
data also show that some morbidity and mortality in emergency care are directly
caused by delayed or interrupted treatment due to lack of medical resources.
However, medical guidelines usually do not provide guidance on medical resource
demands and how to manage potential unexpected delays in resource availability.
If medical resources are temporarily unavailable, safety properties in existing
executable medical guideline models may fail which may cause increased risk to
patients under care. The paper presents a separately model and jointly verify
(SMJV) architecture to separately model medical resource available times and
relationships and jointly verify safety properties of existing medical best
practice guideline models with resource models being integrated in. The SMJV
architecture allows medical staff to effectively manage medical resource
demands and unexpected resource availability delays during emergency care. The
separated modeling approach also allows different domain professionals to make
independent model modifications, facilitates the management of frequent
resource availability changes, and enables resource statechart reuse in
multiple medical guideline models. A simplified stroke scenario is used as a
case study to investigate the effectiveness and validity of the SMJV
architecture. The case study indicates that the SMJV architecture is able to
identify unsafe properties caused by unexpected resource delays.Comment: full version, 12 page
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