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https://www.readbyqxmd.com/read/29322920/investigation-and-identification-of-functional-post-translational-modification-sites-associated-with-drug-binding-and-protein-protein-interactions
#1
Min-Gang Su, Julia Tzu-Ya Weng, Justin Bo-Kai Hsu, Kai-Yao Huang, Yu-Hsiang Chi, Tzong-Yi Lee
BACKGROUND: Protein post-translational modification (PTM) plays an essential role in various cellular processes that modulates the physical and chemical properties, folding, conformation, stability and activity of proteins, thereby modifying the functions of proteins. The improved throughput of mass spectrometry (MS) or MS/MS technology has not only brought about a surge in proteome-scale studies, but also contributed to a fruitful list of identified PTMs. However, with the increase in the number of identified PTMs, perhaps the more crucial question is what kind of biological mechanisms these PTMs are involved in...
December 21, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/29287915/high-throughput-automated-analysis-of-big-flow-cytometry-data
#2
Albina Rahim, Justin Meskas, Sibyl Drissler, Alice Yue, Anna Lorenc, Adam Laing, Namita Saran, Jacqui White, Lucie Abeler-Dörner, Adrian Hayday, Ryan R Brinkman
The rapid expansion of flow cytometry applications has outpaced the functionality of traditional manual analysis tools used to interpret flow cytometry data. Scientists are faced with the daunting prospect of manually identifying interesting cell populations in 50-dimensional datasets, equalling the complexity previously only reached in mass cytometry. Data can no longer be analyzed or interpreted fully by manual approaches. While automated gating has been the focus of intense efforts, there are many significant additional steps to the analytical pipeline (e...
December 26, 2017: Methods: a Companion to Methods in Enzymology
https://www.readbyqxmd.com/read/29280752/medical-graduates-truthful-and-useful-analytics-with-big-data-and-the-art-of-persuasion
#3
Des Gorman, T Michael Kashner
The authors propose that the provision of state-of-the-art, effective, safe, and affordable health care requires medical school graduates not only to be competent practitioners and scientists, but also to be policy makers and professional leaders. To meet this challenge in the era of big data and cloud computing, these graduates must be able to understand and critically interpret analyses of large, observational datasets from electronic health records, third party claims files, surveys, and epidemiologic health datasets...
December 26, 2017: Academic Medicine: Journal of the Association of American Medical Colleges
https://www.readbyqxmd.com/read/29278490/application-of-a-deep-neural-network-to-metabolomics-studies-and-its-performance-in-determining-important-variables
#4
Yasuhiro Date, Jun Kikuchi
Deep neural networks (DNNs), which are kinds of the machine learning approaches, are powerful tools for analyzing big sets of data derived from biological and environmental systems. However, DNNs are not applicable to metabolomics studies because they have difficulty in identifying contribution factors, e.g., biomarkers, in constructed classification and regression models. In this paper, we describe an improved DNN-based analytical approach that incorporates an importance estimation for each variable using a mean decrease accuracy (MDA) calculation, which is based on a permutation algorithm; this approach is called DNN-MDA...
December 26, 2017: Analytical Chemistry
https://www.readbyqxmd.com/read/29250476/dynamic-network-model-for-smart-city-data-loss-resilience-case-study-city-to-city-network-for-crime-analytics
#5
Olivera Kotevska, A Gilad Kusne, Daniel V Samarov, Ahmed Lbath, Abdella Battou
Today's cities generate tremendous amounts of data, thanks to a boom in affordable smart devices and sensors. The resulting big data creates opportunities to develop diverse sets of context-aware services and systems, ensuring smart city services are optimized to the dynamic city environment. Critical resources in these smart cities will be more rapidly deployed to regions in need, and those regions predicted to have an imminent or prospective need. For example, crime data analytics may be used to optimize the distribution of police, medical, and emergency services...
2017: IEEE Access: Practical Innovations, Open Solutions
https://www.readbyqxmd.com/read/29237237/clinical-judgement-in-the-era-of-big-data-and-predictive-analytics
#6
Benjamin Chin-Yee, Ross Upshur
Clinical judgement is a central and longstanding issue in the philosophy of medicine which has generated significant interest over the past few decades. In this article, we explore different approaches to clinical judgement articulated in the literature, focusing in particular on data-driven, mathematical approaches which we contrast with narrative, virtue-based approaches to clinical reasoning. We discuss the tension between these different clinical epistemologies and further explore the implications of big data and machine learning for a philosophy of clinical judgement...
December 13, 2017: Journal of Evaluation in Clinical Practice
https://www.readbyqxmd.com/read/29232865/does-the-short-term-effect-of-air-pollution-influence-the-incidence-of-spontaneous-intracerebral-hemorrhage-in-different-patient-groups-big-data-analysis-in-taiwan
#7
Ting-Ying Chien, Hsien-Wei Ting, Chien-Lung Chan, Nan-Ping Yang, Ren-Hao Pan, K Robert Lai, Su-In Hung
Spontaneous intracerebral hemorrhage (sICH) has a high mortality rate. Research has demonstrated that the occurrence of sICH is related to air pollution. This study used big data analysis to explore the impact of air pollution on the risk of sICH in patients of differing age and geographic location. 39,053 cases were included in this study; 14,041 in the Taipei region (Taipei City and New Taipei City), 5537 in Taoyuan City, 7654 in Taichung City, 4739 in Tainan City, and 7082 in Kaohsiung City. The results of correlation analysis indicated that there were two pollutants groups, the CO and NO₂ group and the PM2...
December 10, 2017: International Journal of Environmental Research and Public Health
https://www.readbyqxmd.com/read/29232864/differences-in-spontaneous-intracerebral-hemorrhage-cases-between-urban-and-rural-regions-of-taiwan-big-data-analytics-of-government-open-data
#8
Hsien-Wei Ting, Ting-Ying Chien, K Robert Lai, Ren-Hao Pan, Kuan-Hsien Wu, Jun-Min Chen, Chien-Lung Chan
This study evaluated the differences in spontaneous intracerebral hemorrhage (sICH) between rural and urban areas of Taiwan with big data analysis. We used big data analytics and visualization tools to examine government open data, which included the residents' health medical administrative data, economic status, educational status, and relevant information. The study subjects included sICH patients of Taipei region (29,741 cases) and Eastern Taiwan (4565 cases). The incidence of sICH per 100,000 population per year in Eastern Taiwan (71...
December 10, 2017: International Journal of Environmental Research and Public Health
https://www.readbyqxmd.com/read/29227306/big-data-analytical-approaches-to-the-nacc-dataset-aiding-preclinical-trial-enrichment
#9
Ming Lin, Pinghua Gong, Tao Yang, Jieping Ye, Roger L Albin, Hiroko H Dodge
BACKGROUND: Clinical trials increasingly aim to retard disease progression during presymptomatic phases of Mild Cognitive Impairment (MCI) and thus recruiting study participants at high risk for developing MCI is critical for cost-effective prevention trials. However, accurately identifying those who are destined to develop MCI is difficult. Collecting biomarkers is often expensive. METHODS: We used only noninvasive clinical variables collected in the National Alzheimer's Coordinating Center (NACC) Uniform Data Sets version 2...
December 7, 2017: Alzheimer Disease and Associated Disorders
https://www.readbyqxmd.com/read/29222076/adverse-drug-event-discovery-using-biomedical-literature-a-big-data-neural-network-adventure
#10
Ahmad P Tafti, Jonathan Badger, Eric LaRose, Ehsan Shirzadi, Andrea Mahnke, John Mayer, Zhan Ye, David Page, Peggy Peissig
BACKGROUND: The study of adverse drug events (ADEs) is a tenured topic in medical literature. In recent years, increasing numbers of scientific articles and health-related social media posts have been generated and shared daily, albeit with very limited use for ADE study and with little known about the content with respect to ADEs. OBJECTIVE: The aim of this study was to develop a big data analytics strategy that mines the content of scientific articles and health-related Web-based social media to detect and identify ADEs...
December 8, 2017: JMIR Medical Informatics
https://www.readbyqxmd.com/read/29221999/supporting-imagers-voice-a-national-training-program-in-comparative-effectiveness-research-and-big-data%C3%A2-analytics
#11
Stella K Kang, James V Rawson, Michael P Recht
Provided methodologic training, more imagers can contribute to the evidence basis on improved health outcomes and value in diagnostic imaging. The Value of Imaging Through Comparative Effectiveness Research Program was developed to provide hands-on, practical training in five core areas for comparative effectiveness and big biomedical data research: decision analysis, cost-effectiveness analysis, evidence synthesis, big data principles, and applications of big data analytics. The program's mixed format consists of web-based modules for asynchronous learning as well as in-person sessions for practical skills and group discussion...
December 5, 2017: Journal of the American College of Radiology: JACR
https://www.readbyqxmd.com/read/29212678/the-myths-of-big-data-in-health-care
#12
REVIEW
D J Jacofsky
'Big data' is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Billions of dollars have been spent on attempts to build predictive tools from large sets of poorly controlled healthcare metadata. Companies often sell reports at a physician or facility level based on various flawed data sources, and comparative websites of 'publicly reported data' purport to educate the public. Physicians should be aware of concerns and pitfalls seen in such data definitions, data clarity, data relevance, data sources and data cleaning when evaluating analytic reports from metadata in health care...
December 2017: Bone & Joint Journal
https://www.readbyqxmd.com/read/29179641/microalgal-process-monitoring-based-on-high-selectivity-spectroscopy-tools-status-and-future-perspectives
#13
Michael Podevin, Ioannis A Fotidis, Irini Angelidaki
Microalgae are well known for their ability to accumulate lipids intracellularly, which can be used for biofuels and mitigate CO2 emissions. However, due to economic challenges, microalgae bioprocesses have maneuvered towards the simultaneous production of food, feed, fuel, and various high-value chemicals in a biorefinery concept. On-line and in-line monitoring of macromolecules such as lipids, proteins, carbohydrates, and high-value pigments will be more critical to maintain product quality and consistency for downstream processing in a biorefinery to maintain and valorize these markets...
November 27, 2017: Critical Reviews in Biotechnology
https://www.readbyqxmd.com/read/29178837/vispa2-a-scalable-pipeline-for-high-throughput-identification-and-annotation-of-vector-integration-sites
#14
Giulio Spinozzi, Andrea Calabria, Stefano Brasca, Stefano Beretta, Ivan Merelli, Luciano Milanesi, Eugenio Montini
BACKGROUND: Bioinformatics tools designed to identify lentiviral or retroviral vector insertion sites in the genome of host cells are used to address the safety and long-term efficacy of hematopoietic stem cell gene therapy applications and to study the clonal dynamics of hematopoietic reconstitution. The increasing number of gene therapy clinical trials combined with the increasing amount of Next Generation Sequencing data, aimed at identifying integration sites, require both highly accurate and efficient computational software able to correctly process "big data" in a reasonable computational time...
November 25, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/29172435/the-evolution-of-chemical-high-throughput-experimentation-to-address-challenging-problems-in-pharmaceutical-synthesis
#15
Shane W Krska, Daniel A DiRocco, Spencer D Dreher, Michael Shevlin
The structural complexity of pharmaceuticals presents a significant challenge to modern catalysis. Many published methods that work well on simple substrates often fail when attempts are made to apply them to complex drug intermediates. The use of high-throughput experimentation (HTE) techniques offers a means to overcome this fundamental challenge by facilitating the rational exploration of large arrays of catalysts and reaction conditions in a time- and material-efficient manner. Initial forays into the use of HTE in our laboratories for solving chemistry problems centered around screening of chiral precious-metal catalysts for homogeneous asymmetric hydrogenation...
November 27, 2017: Accounts of Chemical Research
https://www.readbyqxmd.com/read/29153405/describing-genomic-and-epigenomic-traits-underpinning-emerging-fungal-pathogens
#16
Rhys A Farrer, Matthew C Fisher
An unprecedented number of pathogenic fungi are emerging and causing disease in animals and plants, putting the resilience of wild and managed ecosystems in jeopardy. While the past decades have seen an increase in the number of pathogenic fungi, they have also seen the birth of new big data technologies and analytical approaches to tackle these emerging pathogens. We review how the linked fields of genomics and epigenomics are transforming our ability to address the challenge of emerging fungal pathogens. We explore the methodologies and bioinformatic toolkits that currently exist to rapidly analyze the genomes of unknown fungi, then discuss how these data can be used to address key questions that shed light on their epidemiology...
2017: Advances in Genetics
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
#17
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
#18
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
#19
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
#20
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
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