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https://www.readbyqxmd.com/read/29140477/when-can-the-child-speak-for-herself-the-limits-of-parental-consent-in-data-protection-law-for-health-research
#1
Mark J Taylor, Edward S Dove, Graeme Laurie, David Townend
Draft regulatory guidance suggests that if the processing of a child's personal data begins with the consent of a parent, then there is a need to find and defend an enduring consent through the child's growing capacity and on to their maturity. We consider the implications for health research of the UK Information Commissioner's Office's (ICO) suggestion that the relevant test for maturity is the Gillick test, originally developed in the context of medical treatment. Noting the significance of the welfare principle to this test, we examine the implications for the responsibilities of a parent to act as proxy for their child...
November 13, 2017: Medical Law Review
https://www.readbyqxmd.com/read/29140462/data-portal-for-the-library-of-integrated-network-based-cellular-signatures-lincs-program-integrated-access-to-diverse-large-scale-cellular-perturbation-response-data
#2
Amar Koleti, Raymond Terryn, Vasileios Stathias, Caty Chung, Daniel J Cooper, John P Turner, Dušica Vidovic, Michele Forlin, Tanya T Kelley, Alessandro D'Urso, Bryce K Allen, Denis Torre, Kathleen M Jagodnik, Lily Wang, Sherry L Jenkins, Christopher Mader, Wen Niu, Mehdi Fazel, Naim Mahi, Marcin Pilarczyk, Nicholas Clark, Behrouz Shamsaei, Jarek Meller, Juozas Vasiliauskas, John Reichard, Mario Medvedovic, Avi Ma'ayan, Ajay Pillai, Stephan C Schürer
The Library of Integrated Network-based Cellular Signatures (LINCS) program is a national consortium funded by the NIH to generate a diverse and extensive reference library of cell-based perturbation-response signatures, along with novel data analytics tools to improve our understanding of human diseases at the systems level. In contrast to other large-scale data generation efforts, LINCS Data and Signature Generation Centers (DSGCs) employ a wide range of assay technologies cataloging diverse cellular responses...
November 13, 2017: Nucleic Acids Research
https://www.readbyqxmd.com/read/29110287/a-novel-hypergraph-based-genetic-algorithm-hgga-built-on-unimodular-and-anti-homomorphism-properties-for-dna-sequencing-by-hybridization
#3
V Swaminathan, Gangothri Rajaram, V Abhishek, Boosi Shashank Reddy, K Kannan
The sequencing by hybridization (SBH) of determining the order in which nucleotides should occur on a DNA string is still under discussion for enhancements on computational intelligence although the next generation of DNA sequencing has come into existence. In the last decade, many works related to graph theory-based DNA sequencing have been carried out in the literature. This paper proposes a method for SBH by integrating hypergraph with genetic algorithm (HGGA) for designing a novel analytic technique to obtain DNA sequence from its spectrum...
November 6, 2017: Interdisciplinary Sciences, Computational Life Sciences
https://www.readbyqxmd.com/read/29098954/guidelines-for-genome-scale-analysis-of-biological-rhythms
#4
Michael E Hughes, Katherine C Abruzzi, Ravi Allada, Ron Anafi, Alaaddin Bulak Arpat, Gad Asher, Pierre Baldi, Charissa de Bekker, Deborah Bell-Pedersen, Justin Blau, Steve Brown, M Fernanda Ceriani, Zheng Chen, Joanna C Chiu, Juergen Cox, Alexander M Crowell, Jason P DeBruyne, Derk-Jan Dijk, Luciano DiTacchio, Francis J Doyle, Giles E Duffield, Jay C Dunlap, Kristin Eckel-Mahan, Karyn A Esser, Garret A FitzGerald, Daniel B Forger, Lauren J Francey, Ying-Hui Fu, Frédéric Gachon, David Gatfield, Paul de Goede, Susan S Golden, Carla Green, John Harer, Stacey Harmer, Jeff Haspel, Michael H Hastings, Hanspeter Herzel, Erik D Herzog, Christy Hoffmann, Christian Hong, Jacob J Hughey, Jennifer M Hurley, Horacio O de la Iglesia, Carl Johnson, Steve A Kay, Nobuya Koike, Karl Kornacker, Achim Kramer, Katja Lamia, Tanya Leise, Scott A Lewis, Jiajia Li, Xiaodong Li, Andrew C Liu, Jennifer J Loros, Tami A Martino, Jerome S Menet, Martha Merrow, Andrew J Millar, Todd Mockler, Felix Naef, Emi Nagoshi, Michael N Nitabach, Maria Olmedo, Dmitri A Nusinow, Louis J Ptáček, David Rand, Akhilesh B Reddy, Maria S Robles, Till Roenneberg, Michael Rosbash, Marc D Ruben, Samuel S C Rund, Aziz Sancar, Paolo Sassone-Corsi, Amita Sehgal, Scott Sherrill-Mix, Debra J Skene, Kai-Florian Storch, Joseph S Takahashi, Hiroki R Ueda, Han Wang, Charles Weitz, Pål O Westermark, Herman Wijnen, Ying Xu, Gang Wu, Seung-Hee Yoo, Michael Young, Eric Erquan Zhang, Tomasz Zielinski, John B Hogenesch
Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding "big data" that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis...
October 2017: Journal of Biological Rhythms
https://www.readbyqxmd.com/read/29098143/architecture-and-prototypical-implementation-of-a-semantic-querying-system-for-big-earth-observation-image-bases
#5
Dirk Tiede, Andrea Baraldi, Martin Sudmanns, Mariana Belgiu, Stefan Lang
Spatiotemporal analytics of multi-source Earth observation (EO) big data is a pre-condition for semantic content-based image retrieval (SCBIR). As a proof of concept, an innovative EO semantic querying (EO-SQ) subsystem was designed and prototypically implemented in series with an EO image understanding (EO-IU) subsystem. The EO-IU subsystem is automatically generating ESA Level 2 products (scene classification map, up to basic land cover units) from optical satellite data. The EO-SQ subsystem comprises a graphical user interface (GUI) and an array database embedded in a client server model...
2017: Eur J Remote Sens
https://www.readbyqxmd.com/read/29090085/assessing-and-predicting-drug-induced-anticholinergic-risks-an-integrated-computational-approach
#6
Dong Xu, Heather D Anderson, Aoxiang Tao, Katia L Hannah, Sunny A Linnebur, Robert J Valuck, Vaughn L Culbertson
BACKGROUND: Anticholinergic (AC) adverse drug events (ADEs) are caused by inhibition of muscarinic receptors as a result of designated or off-target drug-receptor interactions. In practice, AC toxicity is assessed primarily based on clinician experience. The goal of this study was to evaluate a novel concept of integrating big pharmacological and healthcare data to assess clinical AC toxicity risks. METHODS: AC toxicity scores (ATSs) were computed using drug-receptor inhibitions identified through pharmacological data screening...
November 2017: Therapeutic Advances in Drug Safety
https://www.readbyqxmd.com/read/29080814/sleep-devices-wearables-and-nearables-informational-and-interventional-consumer-and-clinical
#7
Matt T Bianchi
The field of sleep is in many ways ideally positioned to take full advantage of advancements in technology and analytics that is fueling the mobile health movement. Combining hardware and software advances with increasingly available big datasets that contain scored data obtained under gold standard sleep laboratory conditions completes the trifecta of this perfect storm. This review highlights recent developments in consumer and clinical devices for sleep, emphasizing the need for validation at multiple levels, with the ultimate goal of using personalized data and advanced algorithms to provide actionable information that will improve sleep health...
October 25, 2017: Metabolism: Clinical and Experimental
https://www.readbyqxmd.com/read/29078953/the-application-of-a-novel-high-resolution-mass-spectrometry-based-analytical-strategy-to-rapid-metabolite-profiling-of-a-dual-drug-combination-in-humans
#8
Jie Xing, Meitong Zang, Huixiang Liu
Metabolite profiling of combination drugs in complex matrix is a big challenge. Development of an effective data mining technique for simultaneously extracting metabolites of one parent drug from both background matrix and combined drug-related signals could be a solution. This study presented a novel high resolution mass spectrometry (HRMS)-based data-mining strategy to fast and comprehensive metabolite identification of combination drugs in human. The model drug combination was verapamil-irbesartan (VER-IRB), which is widely used in clinic to treat hypertension...
November 15, 2017: Analytica Chimica Acta
https://www.readbyqxmd.com/read/29068640/handling-data-skew-in-mapreduce-cluster-by-using-partition-tuning
#9
Yufei Gao, Yanjie Zhou, Bing Zhou, Lei Shi, Jiacai Zhang
The healthcare industry has generated large amounts of data, and analyzing these has emerged as an important problem in recent years. The MapReduce programming model has been successfully used for big data analytics. However, data skew invariably occurs in big data analytics and seriously affects efficiency. To overcome the data skew problem in MapReduce, we have in the past proposed a data processing algorithm called Partition Tuning-based Skew Handling (PTSH). In comparison with the one-stage partitioning strategy used in the traditional MapReduce model, PTSH uses a two-stage strategy and the partition tuning method to disperse key-value pairs in virtual partitions and recombines each partition in case of data skew...
2017: Journal of Healthcare Engineering
https://www.readbyqxmd.com/read/29065568/handling-data-skew-in-mapreduce-cluster-by-using-partition-tuning
#10
Yufei Gao, Yanjie Zhou, Bing Zhou, Lei Shi, Jiacai Zhang
The healthcare industry has generated large amounts of data, and analyzing these has emerged as an important problem in recent years. The MapReduce programming model has been successfully used for big data analytics. However, data skew invariably occurs in big data analytics and seriously affects efficiency. To overcome the data skew problem in MapReduce, we have in the past proposed a data processing algorithm called Partition Tuning-based Skew Handling (PTSH). In comparison with the one-stage partitioning strategy used in the traditional MapReduce model, PTSH uses a two-stage strategy and the partition tuning method to disperse key-value pairs in virtual partitions and recombines each partition in case of data skew...
2017: Journal of Healthcare Engineering
https://www.readbyqxmd.com/read/29059758/re-big-data-predictive-analytics-and-quality-improvement-in-kidney-transplantation-a-proof-of-concept
#11
David A Goldfarb
No abstract text is available yet for this article.
November 2017: Journal of Urology
https://www.readbyqxmd.com/read/29052219/pharmacogenomic-discovery-to-function-and-mechanism-breast-cancer-as-a-case-study
#12
Liewei Wang, James Ingle, Richard Weinshilboum
Biomedical research is undergoing rapid change, with the development of a series of analytical omics techniques that are capable of generating Biomedical Big Data. These developments provide an unprecedented opportunity to gain novel insight into disease pathophysiology and mechanisms of drug action and response-but they also present significant challenges. Pharmacogenomics is a discipline within Clinical Pharmacology that has been at the forefront in defining, taking advantage of and dealing with the opportunities and challenges of this aspect of the Post-Genome Project world...
October 20, 2017: Clinical Pharmacology and Therapeutics
https://www.readbyqxmd.com/read/29043986/potential-of-big-data-analytics-in-the-french-in-vitro-diagnostics-market
#13
Nicolas Dubois, Nicolas Garnier, Christophe Meune
The new paradigm of the big data raises many expectations, particularly in the field of health. Curiously, even though medical biology laboratories generate a great amount of data, the opportunities offered by this new field are poorly documented. For better understanding the clinical context of chronical disease follow-up, for leveraging preventive and/or personalized medicine, the contribution of big data analytics seems very promising. It is within this framework that we have explored to use data of a Breton group of laboratories of medical biology to analyze the possible contributions of their exploitation in the improvement of the clinical practices and to anticipate the evolution of pathologies for the benefit of patients...
October 18, 2017: Annales de Biologie Clinique
https://www.readbyqxmd.com/read/29042152/crowdsourcing-dermatology-dataderm-big-data-analytics-and-machine-learning-technology
#14
EDITORIAL
Andrew J Park, Justin M Ko, Robert A Swerlick
No abstract text is available yet for this article.
October 14, 2017: Journal of the American Academy of Dermatology
https://www.readbyqxmd.com/read/29040418/translational-medicine-in-the-age-of-big-data
#15
Nicholas P Tatonetti
The ability to collect, store and analyze massive amounts of molecular and clinical data is fundamentally transforming the scientific method and its application in translational medicine. Collecting observations has always been a prerequisite for discovery, and great leaps in scientific understanding are accompanied by an expansion of this ability. Particle physics, astronomy and climate science, for example, have all greatly benefited from the development of new technologies enabling the collection of larger and more diverse data...
October 12, 2017: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/29017802/big-data-and-total-hip-arthroplasty-how-do-large-databases-compare
#16
Nicholas A Bedard, Andrew J Pugely, Michael A McHugh, Nathan R Lux, Kevin J Bozic, John J Callaghan
BACKGROUND: Use of large databases for orthopedic research has become extremely popular in recent years. Each database varies in the methods used to capture data and the population it represents. The purpose of this study was to evaluate how these databases differed in reported demographics, comorbidities, and postoperative complications for primary total hip arthroplasty (THA) patients. METHODS: Primary THA patients were identified within National Surgical Quality Improvement Programs (NSQIP), Nationwide Inpatient Sample (NIS), Medicare Standard Analytic Files (MED), and Humana administrative claims database (HAC)...
September 13, 2017: Journal of Arthroplasty
https://www.readbyqxmd.com/read/28984189/the-international-conference-on-intelligent-biology-and-medicine-icibm-2016-from-big-data-to-big-analytical-tools
#17
EDITORIAL
Zhandong Liu, W Jim Zheng, Genevera I Allen, Yin Liu, Jianhua Ruan, Zhongming Zhao
The 2016 International Conference on Intelligent Biology and Medicine (ICIBM 2016) was held on December 8-10, 2016 in Houston, Texas, USA. ICIBM included eight scientific sessions, four tutorials, one poster session, four highlighted talks and four keynotes that covered topics on 3D genomics structural analysis, next generation sequencing (NGS) analysis, computational drug discovery, medical informatics, cancer genomics, and systems biology. Here, we present a summary of the nine research articles selected from ICIBM 2016 program for publishing in BMC Bioinformatics...
October 3, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28975931/patient-reported-outcomes-in-cancer-care-hearing-the-patient-voice-at-greater-volume
#18
REVIEW
Thomas W LeBlanc, Amy P Abernethy
Recording of patient-reported outcomes (PROs) enables direct measurement of the experiences of patients with cancer. In the past decade, the use of PROs has become a prominent topic in health-care innovation; this trend highlights the role of the patient experience as a key measure of health-care quality. Historically, PROs were used solely in the context of research studies, but a growing body of literature supports the feasibility of electronic collection of PROs, yielding reliable data that are sometimes of better quality than clinician-reported data...
October 4, 2017: Nature Reviews. Clinical Oncology
https://www.readbyqxmd.com/read/28961771/cloud-based-interactive-analytics-for-terabytes-of-genomic-variants-data
#19
Cuiping Pan, Gregory McInnes, Nicole Deflaux, Michael Snyder, Jonathan Bingham, Somalee Datta, Philip S Tsao
Motivation: Large scale genomic sequencing is now widely used to decipher questions in diverse realms such as biological function, human diseases, evolution, ecosystems, and agriculture. With the quantity and diversity these data harbor, a robust and scalable data handling and analysis solution is desired. Results: We present interactive analytics using a cloud-based columnar database built on Dremel to perform information compression, comprehensive quality controls, and biological information retrieval in large volumes of genomic data...
July 26, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28949092/profiling-arthritis-pain-with-decision-tree
#20
Man Hung, Jerry Bounsanga, Fangzhou Liu, Maren W Voss
BACKGROUND: Arthritis is the leading cause of work disability and contributes to lost productivity. Previous studies showed that various factors predict pain but they were limited in sample size and scope from a data analytics perspective. OBJECTIVES: The current study applied machine learning algorithms to identify predictors of pain associated with arthritis in a large national sample. METHODS: Using data from the 2011-2012 Medical Expenditure Panel Survey, data mining was performed to develop algorithms to identify factors and patterns that contribute to risk of pain...
September 26, 2017: Pain Practice: the Official Journal of World Institute of Pain
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