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Risk Factors for Thyroid Cancer, a Systematic Review

Thyroid cancer accounted for 1 out of every 20 female cancer diagnoses worldwide in 2018; the etiology of this disease is not well understood, and preventive programs are not established.  It is well known that thyroid cancer incidence has been increasing since the 1980s, largely attributed to the increase in diagnosis of papillary thyroid cancer and

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FatPlants: A Comprehensive Website Platform of Plant Fat Related Genes, Proteins and Metabolism

Increasing seed oil content by plant breeding has resulted in trade-offs or penalties with respect to protein content, seed size, or seed set. The molecular basis for this impasse is mostly speculative. Use of current global profiling approaches to better understand both the metabolic consequences of higher oil and the basis for reduced yield must

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Development of A Blockchain Framework for Virtual Clinical Trials

Clinical trials are essential for discovering new treatments, but there are multiple challenges to patient recruitment, patient engagement, and cost containment. Virtual clinical trials (VCT) are an innovative approach that provides potential solutions by conducting home-based, rather than site-based, clinical trials. Virtual clinical trials are still the exception rather than general practice due to technical

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Identifying Patient-specific Flow of Signal Transduction Perturbed by Multiple Single-nucleotide Alterations

Background: Identifying patient-specific flow of signal transduction perturbed by multiple single-nucleotide alterations is critical for improving patient outcomes in cancer cases. However, accurate estimation of mutational effects at the pathway level for such patients remains an open problem. While probabilistic pathway topology methods are gaining interest among the scientific community, the overwhelming majority do not account

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Analysis of Healthy Coping Feedback Messages from Diabetes Mobile Apps

To analyze Healthy Coping-related feedback messages from diabetes mobile apps against the theoretical framework based on behavioral change theories. We searched apps using the search terms: “diabetes,” “blood sugar,” “glucose,” and “mood” from iTunes and Google Play stores. We entered a range of values on three Healthy Coping domains: 1) diabetes-related measures, 2) physical exercise/activity,

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Data-Driven Patients Stratification and Drug Repositioning

Cancer is a heterogeneous disease and represents a great example of the need for selecting patient-centric rather than disease-centric treatment. De novo drug discovery is a time-consuming and high-cost process with a low success rate. Drug repositioning (DR) reduces the time, cost, and risk of developing new drugs because it recommends new uses for drugs

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Data Analytics Using the Cerner Real-world COVID-19 Data to Answer Clinical Questions

Cerner Real World data allows researchers and data scientists to explore clinical data via HealtheDataLab. Recently, Cerner granted many of their client institutions access to de-identified patient’s data for COVID-19 research to help fight the pandemic.  The de-identified patient data was dataset contains COVID-19 related encounters, demographics, chronic conditions, medication, and lab results. This large-scale

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Improving interpretation of Genome-Wide Association Studies (GWAS) by quantifying Marker Recurrence

To understand biological differences within groups of people or animals, we often turn to DNA. A genome-wide association study (GWAS) can assess the genetic contribution of biological differences between individuals. However, the scale of input data continues to expand in three ways: the sequence coverage of genomes, the number of individuals sequenced, and the number

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Implementing GeoARK: The Geospatial Analytical Research Knowledgebase

This research focuses on the development and implementation of an interface to the Geospatial Analytical Research Knowledgebase (GeoARK), a spatially enabled big data informatics approach assembled around applications in health research and analytics. Example applications in telehealth reach, COVID-19 risk in rural situations, pathways for zoonotic disease spread, and contextual leukemia research will be provided.

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An R-based platform for the visualization and analysis of single molecule tracking experiments

Single molecule tracking (SMT) is a technique of single-molecule fluorescence imaging that allows for the exploration of molecular motion at a high spatiotemporal resolution on living cells. This is widely used to define dynamics of individual tumor cell-surface receptors. Spatiotemporal regulation of many of these receptors varies across cancer types, playing a key role in

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