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https://www.readbyqxmd.com/read/28808136/eplant-visualizing-and-exploring-multiple-levels-of-data-for-hypothesis-generation-in-plant-biology
#1
Jamie Waese, Jim Fan, Asher Pasha, Hans Yu, Geoffrey Fucile, Ruian Shi, Matthew Cumming, Lawrence Kelley, Michael Sternberg, Vivek Krishnakumar, Erik Ferlanti, Jason Miller, Chris Town, Wolfgang Stuerzlinger, Nicholas J Provart
A big challenge in current systems biology research arises when different types of data must be accessed from separate sources and visualized using separate tools. The high cognitive load required to navigate such a workflow is detrimental to hypothesis generation. Accordingly, there is a need for a robust research platform that incorporates all data, and provides integrated search, analysis, and visualization features through a single portal. Here, we present ePlant (http://bar.utoronto.ca/eplant), a visual analytic tool for exploring multiple levels of Arabidopsis data through a zoomable user interface...
August 14, 2017: Plant Cell
https://www.readbyqxmd.com/read/28806228/legal-and-ethical-concerns-of-big-data-predictive-analytics
#2
Shirley S Paulson, Elizabeth Scruth
No abstract text is available yet for this article.
September 2017: Clinical Nurse Specialist CNS
https://www.readbyqxmd.com/read/28802713/detecting-exact-breakpoints-of-deletions-with-diversity-in-hepatitis-b-viral-genomic-dna-from-next-generation-sequencing-data
#3
Ji-Hong Cheng, Wen-Chun Liu, Ting-Tsung Chang, Sun-Yuan Hsieh, Vincent S Tseng
Many studies have suggested that deletions of Hepatitis B Viral (HBV) are associated with the development of progressive liver diseases, even ultimately resulting in hepatocellular carcinoma (HCC). Among the methods for detecting deletions from next-generation sequencing (NGS) data, few methods considered the characteristics of virus, such as high evolution rates and high divergence among the different HBV genomes. Sequencing high divergence HBV genome sequences using the NGS technology outputs millions of reads...
August 9, 2017: Methods: a Companion to Methods in Enzymology
https://www.readbyqxmd.com/read/28783079/an-ultra-low-power-turning-angle-based-biomedical-signal-compression-engine-with-adaptive-threshold-tuning
#4
Jun Zhou, Chao Wang
Intelligent sensing is drastically changing our everyday life including healthcare by biomedical signal monitoring, collection, and analytics. However, long-term healthcare monitoring generates tremendous data volume and demands significant wireless transmission power, which imposes a big challenge for wearable healthcare sensors usually powered by batteries. Efficient compression engine design to reduce wireless transmission data rate with ultra-low power consumption is essential for wearable miniaturized healthcare sensor systems...
August 6, 2017: Sensors
https://www.readbyqxmd.com/read/28782717/in-silico-approaches-for-unveiling-novel-glycobiomarkers-in-cancer
#5
Rita Azevedo, André M N Silva, Celso A Reis, Lúcio Lara Santos, José Alexandre Ferreira
Glycosylation is one of the most common and dynamic post-translational modification of cell surface and secreted proteins. Cancer cells display unique glycosylation patterns that decisively contribute to drive oncogenic behavior, including disease progression and dissemination. Moreover, alterations in glycosylation are often responsible for the creation of protein signatures holding significant biomarker value and potential for targeted therapeutics. Accordingly, many analytical protocols have been outlined for the identification of abnormally glycosylated proteins by mass spectrometry...
August 4, 2017: Journal of Proteomics
https://www.readbyqxmd.com/read/28771321/activity-based-detection-of-consumption-of-synthetic-cannabinoids-in-authentic-urine-samples-using-a-stable-cannabinoid-reporter-system
#6
Annelies Cannaert, Florian Franz, Volker Auwärter, Christophe P Stove
Synthetic cannabinoids (SCs) continue to be the largest group of new psychoactive substances (NPS) monitored by the European Monitoring Center of Drugs and Drugs of Abuse (EMCDDA). The identification and subsequent prohibition of single SCs has driven clandestine chemists to produce analogues of increasing structural diversity, intended to evade legislation. That structural diversity, combined with the mostly unknown metabolic profiles of these new SCs, poses a big challenge for the conventional targeted analytical assays, as it is difficult to screen for 'unknown' compounds...
August 3, 2017: Analytical Chemistry
https://www.readbyqxmd.com/read/28770216/translating-big-data-into-smart-data-for-veterinary-epidemiology
#7
Kimberly VanderWaal, Robert B Morrison, Claudia Neuhauser, Carles Vilalta, Andres M Perez
The increasing availability and complexity of data has led to new opportunities and challenges in veterinary epidemiology around how to translate abundant, diverse, and rapidly growing "big" data into meaningful insights for animal health. Big data analytics are used to understand health risks and minimize the impact of adverse animal health issues through identifying high-risk populations, combining data or processes acting at multiple scales through epidemiological modeling approaches, and harnessing high velocity data to monitor animal health trends and detect emerging health threats...
2017: Frontiers in Veterinary Science
https://www.readbyqxmd.com/read/28769780/automated-functional-analysis-of-astrocytes-from-chronic-time-lapse-calcium-imaging-data
#8
Yinxue Wang, Guilai Shi, David J Miller, Yizhi Wang, Congchao Wang, Gerard Broussard, Yue Wang, Lin Tian, Guoqiang Yu
Recent discoveries that astrocytes exert proactive regulatory effects on neural information processing and that they are deeply involved in normal brain development and disease pathology have stimulated broad interest in understanding astrocyte functional roles in brain circuit. Measuring astrocyte functional status is now technically feasible, due to recent advances in modern microscopy and ultrasensitive cell-type specific genetically encoded Ca(2+) indicators for chronic imaging. However, there is a big gap between the capability of generating large dataset via calcium imaging and the availability of sophisticated analytical tools for decoding the astrocyte function...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28748430/inicu-integrated-neonatal-care-unit-capturing-neonatal-journey-in-an-intelligent-data-way
#9
Harpreet Singh, Gautam Yadav, Raghuram Mallaiah, Preetha Joshi, Vinay Joshi, Ravneet Kaur, Suneyna Bansal, Samir K Brahmachari
Neonatal period represents first 28 days of life, which is the most vulnerable time for a child's survival especially for the preterm babies. High neonatal mortality is a prominent and persistent problem across the globe. Non-availability of trained staff and infrastructure are the major recognized hurdles in the quality care of these neonates. Hourly progress growth charts and reports are still maintained manually by nurses along with continuous calculation of drug dosage and nutrition as per the changing weight of the baby...
August 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/28745806/detection-and-quantification-of-overactive-bladder-activity-in-patients-can-we-make-it-better-and-automatic
#10
Thomas Niederhauser, Elena S Gafner, Tarcisi Cantieni, Michelle Grämiger, Andreas Haeberlin, Dominik Obrist, Fiona Burkhard, Francesco Clavica
AIMS: To explore the use of time-frequency analysis as an analytical tool to automatically detect pattern changes in bladder pressure recordings of patients with overactive bladder (OAB). To provide quantitative data on the bladder's non-voiding activity which could improve the current diagnosis and potentially the treatment of OAB. METHODS: We developed an algorithm, based on time-frequency analysis, to analyze bladder pressure during the filling phase of urodynamic studies...
July 26, 2017: Neurourology and Urodynamics
https://www.readbyqxmd.com/read/28744848/systems-and-precision-medicine-approaches-to-diabetes-heterogeneity-a-big-data-perspective
#11
Enrico Capobianco
Big Data, and in particular Electronic Health Records, provide the medical community with a great opportunity to analyze multiple pathological conditions at an unprecedented depth for many complex diseases, including diabetes. How can we infer on diabetes from large heterogeneous datasets? A possible solution is provided by invoking next-generation computational methods and data analytics tools within systems medicine approaches. By deciphering the multi-faceted complexity of biological systems, the potential of emerging diagnostic tools and therapeutic functions can be ultimately revealed...
December 2017: Clinical and Translational Medicine
https://www.readbyqxmd.com/read/28744087/a-peek-into-the-future-of-radiology-using-big-data-applications
#12
Amit T Kharat, Shubham Singhal
Big data is extremely large amount of data which is available in the radiology department. Big data is identified by four Vs - Volume, Velocity, Variety, and Veracity. By applying different algorithmic tools and converting raw data to transformed data in such large datasets, there is a possibility of understanding and using radiology data for gaining new knowledge and insights. Big data analytics consists of 6Cs - Connection, Cloud, Cyber, Content, Community, and Customization. The global technological prowess and per-capita capacity to save digital information has roughly doubled every 40 months since the 1980's...
April 2017: Indian Journal of Radiology & Imaging
https://www.readbyqxmd.com/read/28721807/developing-the-transdisciplinary-aging-research-agenda-new-developments-in-big-data
#13
Christian William Callaghan
In light of dramatic advances in big data analytics and the application of these advances in certain scientific fields, new potentialities exist for breakthroughs in aging research. Translating these new potentialities to research outcomes for aging populations, however, remains a challenge, as underlying technologies which have enabled exponential increases in 'big data' have not yet enabled a commensurate era of 'big knowledge,' or similarly exponential increases in biomedical breakthroughs. Debates also reveal differences in the literature, with some arguing big data analytics heralds a new era associated with the 'end of theory' or which makes the scientific method obsolete, where correlation supercedes causation, whereby science can advance without theory and hypotheses testing...
July 19, 2017: Current Aging Science
https://www.readbyqxmd.com/read/28715407/building-the-biomedical-data-science-workforce
#14
Michelle C Dunn, Philip E Bourne
This article describes efforts at the National Institutes of Health (NIH) from 2013 to 2016 to train a national workforce in biomedical data science. We provide an analysis of the Big Data to Knowledge (BD2K) training program strengths and weaknesses with an eye toward future directions aimed at any funder and potential funding recipient worldwide. The focus is on extramurally funded programs that have a national or international impact rather than the training of NIH staff, which was addressed by the NIH's internal Data Science Workforce Development Center...
July 2017: PLoS Biology
https://www.readbyqxmd.com/read/28711216/national-nursing-science-priorities-creating-a-shared-vision
#15
Patricia Eckardt, Joan M Culley, Elizabeth Corwin, Therese Richmond, Cynthia Dougherty, Rita H Pickler, Cheryl A Krause-Parello, Carol F Roye, Jessica G Rainbow, Holli A DeVon
BACKGROUND: Nursing science is essential to advance population health through contributions at all phases of scientific inquiry. Multiple scientific initiatives important to nursing science overlap in aims and population focus. PURPOSE: This article focused on providing the American Academy of Nursing and nurse scientists in the Unites States with a blueprint of nursing science priorities to inform a shared vision for future collaborations, areas of scientific inquiry, and resource allocation...
June 12, 2017: Nursing Outlook
https://www.readbyqxmd.com/read/28701813/towards-a-new-generation-of-agricultural-system-data-models-and-knowledge-products-information-and-communication-technology
#16
Sander J C Janssen, Cheryl H Porter, Andrew D Moore, Ioannis N Athanasiadis, Ian Foster, James W Jones, John M Antle
Agricultural modeling has long suffered from fragmentation in model implementation. Many models are developed, there is much redundancy, models are often poorly coupled, model component re-use is rare, and it is frequently difficult to apply models to generate real solutions for the agricultural sector. To improve this situation, we argue that an open, self-sustained, and committed community is required to co-develop agricultural models and associated data and tools as a common resource. Such a community can benefit from recent developments in information and communications technology (ICT)...
July 2017: Agricultural Systems
https://www.readbyqxmd.com/read/28690426/graphing-trillions-of-triangles
#17
Paul Burkhardt
The increasing size of Big Data is often heralded but how data are transformed and represented is also profoundly important to knowledge discovery, and this is exemplified in Big Graph analytics. Much attention has been placed on the scale of the input graph but the product of a graph algorithm can be many times larger than the input. This is true for many graph problems, such as listing all triangles in a graph. Enabling scalable graph exploration for Big Graphs requires new approaches to algorithms, architectures, and visual analytics...
July 2017: Information Visualization
https://www.readbyqxmd.com/read/28679894/the-evotion-decision-support-system-utilizing-it-for-public-health-policy-making-in-hearing-loss
#18
Panagiotis Katrakazas, Lyubov Trenkova, Josip Milas, Dario Brdaric, Dimitris Koutsouris
As Decision Support Systems start to play a significant role in decision making, especially in the field of public-health policy making, we present an initial attempt to formulate such a system in the concept of public health policy making for hearing loss related problems. Justification for the system's conceptual architecture and its key functionalities are presented. The introduction of the EVOTION DSS sets a key innovation and a basis for paradigm shift in policymaking, by incorporating relevant models, big data analytics and generic demographic data...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28679877/crowdhealth-holistic-health-records-and-big-data-analytics-for-health-policy-making-and-personalized-health
#19
Dimosthenis Kyriazis, Serge Autexier, Iván Brondino, Michael Boniface, Lucas Donat, Vegard Engen, Rafael Fernandez, Ricardo Jimenez-Peris, Blanca Jordan, Gregor Jurak, Athanasios Kiourtis, Thanos Kosmidis, Mitja Lustrek, Ilias Maglogiannis, John Mantas, Antonio Martinez, Argyro Mavrogiorgou, Andreas Menychtas, Lydia Montandon, Cosmin-Septimiu Nechifor, Sokratis Nifakos, Alexandra Papageorgiou, Marta Patino-Martinez, Manuel Perez, Vassilis Plagianakos, Dalibor Stanimirovic, Gregor Starc, Tanja Tomson, Francesco Torelli, Vicente Traver-Salcedo, George Vassilacopoulos, Usman Wajid
Today's rich digital information environment is characterized by the multitude of data sources providing information that has not yet reached its full potential in eHealth. The aim of the presented approach, namely CrowdHEALTH, is to introduce a new paradigm of Holistic Health Records (HHRs) that include all health determinants. HHRs are transformed into HHRs clusters capturing the clinical, social and human context of population segments and as a result collective knowledge for different factors. The proposed approach also seamlessly integrates big data technologies across the complete data path, providing of Data as a Service (DaaS) to the health ecosystem stakeholders, as well as to policy makers towards a "health in all policies" approach...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28678528/21st-century-toolkit-for-optimizing-population-health-through-precision-nutrition
#20
Aifric O'Sullivan, Bethany Henrick, Bonnie Dixon, Daniela Barile, Angela Zivkovic, Jennifer Smilowitz, Danielle Lemay, William Martin, J Bruce German, Sara Elizabeth Schaefer
Scientific, technological, and economic progress over the last 100 years all but eradicated problems of widespread food shortage and nutrient deficiency in developed nations. But now society is faced with a new set of nutrition problems related to energy imbalance and metabolic disease, which require new kinds of solutions. Recent developments in the area of new analytical tools enable us to systematically study large quantities of detailed and multidimensional metabolic and health data, providing the opportunity to address current nutrition problems through an approach called Precision Nutrition...
July 5, 2017: Critical Reviews in Food Science and Nutrition
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