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Jason H Moore

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https://www.readbyqxmd.com/read/29655375/association-between-traumatic-stress-load-psychopathology-and-cognition-in-the-philadelphia-neurodevelopmental-cohort
#1
Ran Barzilay, Monica E Calkins, Tyler M Moore, Daniel H Wolf, Theodore D Satterthwaite, J Cobb Scott, Jason D Jones, Tami D Benton, Ruben C Gur, Raquel E Gur
BACKGROUND: Traumatic stressors during childhood and adolescence are associated with psychopathology, mostly studied in the context of post-traumatic stress disorder (PTSD) and depression. We investigated broader associations of traumatic stress exposure with psychopathology and cognition in a youth community sample. METHODS: The Philadelphia Neurodevelopmental Cohort (N = 9498) is an investigation of clinical and neurobehavioral phenotypes in a diverse (56% Caucasian, 33% African American, 11% other) US youth community population (aged 8-21)...
April 15, 2018: Psychological Medicine
https://www.readbyqxmd.com/read/29596416/eleven-quick-tips-for-architecting-biomedical-informatics-workflows-with-cloud-computing
#2
Brian S Cole, Jason H Moore
Cloud computing has revolutionized the development and operations of hardware and software across diverse technological arenas, yet academic biomedical research has lagged behind despite the numerous and weighty advantages that cloud computing offers. Biomedical researchers who embrace cloud computing can reap rewards in cost reduction, decreased development and maintenance workload, increased reproducibility, ease of sharing data and software, enhanced security, horizontal and vertical scalability, high availability, a thriving technology partner ecosystem, and much more...
March 2018: PLoS Computational Biology
https://www.readbyqxmd.com/read/29538381/taxonomy-based-on-science-is-necessary-for-global-conservation
#3
Scott A Thomson, Richard L Pyle, Shane T Ahyong, Miguel Alonso-Zarazaga, Joe Ammirati, Juan Francisco Araya, John S Ascher, Tracy Lynn Audisio, Valter M Azevedo-Santos, Nicolas Bailly, William J Baker, Michael Balke, Maxwell V L Barclay, Russell L Barrett, Ricardo C Benine, James R M Bickerstaff, Patrice Bouchard, Roger Bour, Thierry Bourgoin, Christopher B Boyko, Abraham S H Breure, Denis J Brothers, James W Byng, David Campbell, Luis M P Ceríaco, István Cernák, Pierfilippo Cerretti, Chih-Han Chang, Soowon Cho, Joshua M Copus, Mark J Costello, Andras Cseh, Csaba Csuzdi, Alastair Culham, Guillermo D'Elía, Cédric d'Udekem d'Acoz, Mikhail E Daneliya, René Dekker, Edward C Dickinson, Timothy A Dickinson, Peter Paul van Dijk, Klaas-Douwe B Dijkstra, Bálint Dima, Dmitry A Dmitriev, Leni Duistermaat, John P Dumbacher, Wolf L Eiserhardt, Torbjørn Ekrem, Neal L Evenhuis, Arnaud Faille, José L Fernández-Triana, Emile Fiesler, Mark Fishbein, Barry G Fordham, André V L Freitas, Natália R Friol, Uwe Fritz, Tobias Frøslev, Vicki A Funk, Stephen D Gaimari, Guilherme S T Garbino, André R S Garraffoni, József Geml, Anthony C Gill, Alan Gray, Felipe G Grazziotin, Penelope Greenslade, Eliécer E Gutiérrez, Mark S Harvey, Cornelis J Hazevoet, Kai He, Xiaolan He, Stephan Helfer, Kristofer M Helgen, Anneke H van Heteren, Francisco Hita Garcia, Norbert Holstein, Margit K Horváth, Peter H Hovenkamp, Wei Song Hwang, Jaakko Hyvönen, Melissa B Islam, John B Iverson, Michael A Ivie, Zeehan Jaafar, Morgan D Jackson, J Pablo Jayat, Norman F Johnson, Hinrich Kaiser, Bente B Klitgård, Dániel G Knapp, Jun-Ichi Kojima, Urmas Kõljalg, Jenő Kontschán, Frank-Thorsten Krell, Irmgard Krisai-Greilhuber, Sven Kullander, Leonardo Latella, John E Lattke, Valeria Lencioni, Gwilym P Lewis, Marcos G Lhano, Nathan K Lujan, Jolanda A Luksenburg, Jean Mariaux, Jader Marinho-Filho, Christopher J Marshall, Jason F Mate, Molly M McDonough, Ellinor Michel, Vitor F O Miranda, Mircea-Dan Mitroiu, Jesús Molinari, Scott Monks, Abigail J Moore, Ricardo Moratelli, Dávid Murányi, Takafumi Nakano, Svetlana Nikolaeva, John Noyes, Michael Ohl, Nora H Oleas, Thomas Orrell, Barna Páll-Gergely, Thomas Pape, Viktor Papp, Lynne R Parenti, David Patterson, Igor Ya Pavlinov, Ronald H Pine, Péter Poczai, Jefferson Prado, Divakaran Prathapan, Richard K Rabeler, John E Randall, Frank E Rheindt, Anders G J Rhodin, Sara M Rodríguez, D Christopher Rogers, Fabio de O Roque, Kevin C Rowe, Luis A Ruedas, Jorge Salazar-Bravo, Rodrigo B Salvador, George Sangster, Carlos E Sarmiento, Dmitry S Schigel, Stefan Schmidt, Frederick W Schueler, Hendrik Segers, Neil Snow, Pedro G B Souza-Dias, Riaan Stals, Soili Stenroos, R Douglas Stone, Charles F Sturm, Pavel Štys, Pablo Teta, Daniel C Thomas, Robert M Timm, Brian J Tindall, Jonathan A Todd, Dagmar Triebel, Antonio G Valdecasas, Alfredo Vizzini, Maria S Vorontsova, Jurriaan M de Vos, Philipp Wagner, Les Watling, Alan Weakley, Francisco Welter-Schultes, Daniel Whitmore, Nicholas Wilding, Kipling Will, Jason Williams, Karen Wilson, Judith E Winston, Wolfgang Wüster, Douglas Yanega, David K Yeates, Hussam Zaher, Guanyang Zhang, Zhi-Qiang Zhang, Hong-Zhang Zhou
No abstract text is available yet for this article.
March 2018: PLoS Biology
https://www.readbyqxmd.com/read/29521452/genomes-of-ubiquitous-marine-and-hypersaline-hydrogenovibrio-thiomicrorhabdus-and-thiomicrospira-spp-encode-a-diversity-of-mechanisms-to-sustain-chemolithoautotrophy-in-heterogeneous-environments
#4
Kathleen M Scott, John Williams, Cody M B Porter, Sydney Russel, Tara L Harmer, John H Paul, Kirsten M Antonen, Megan K Bridges, Gary J Camper, Christie K Campla, Leila G Casella, Eva Chase, James W Conrad, Mercedez C Cruz, Darren S Dunlap, Laura Duran, Elizabeth M Fahsbender, Dawn B Goldsmith, Ryan F Keeley, Matthew R Kondoff, Breanna I Kussy, Marannda K Lane, Stephanie Lawler, Brittany A Leigh, Courtney Lewis, Lygia M Lostal, Devon Marking, Paola A Mancera, Evan C McClenthan, Emily A McIntyre, Jessica A Mine, Swapnil Modi, Brittney D Moore, William A Morgan, Kaleigh M Nelson, Kimmy N Nguyen, Nicholas Ogburn, David G Parrino, Anangamanjari D Pedapudi, Rebecca P Pelham, Amanda M Preece, Elizabeth A Rampersad, Jason C Richardson, Christina M Rodgers, Brent L Schaffer, Nancy E Sheridan, Michael R Solone, Zachery R Staley, Maki Tabuchi, Ramond J Waide, Pauline W Wanjugi, Suzanne Young, Alicia Clum, Chris Daum, Marcel Huntemann, Natalia Ivanova, Nikos Kyrpides, Natalia Mikhailova, Krishnaveni Palaniappan, Manoj Pillay, T B K Reddy, Nicole Shapiro, Dimitrios Stamatis, Neha Varghese, Tanja Woyke, Rich Boden, Sharyn K Freyermuth, Cheryl A Kerfeld
Chemolithoautotrophic bacteria from the genera Hydrogenovibrio, Thiomicrorhabdus, and Thiomicrospira are common, sometimes dominant, isolates from sulfidic habitats including hydrothermal vents, soda and salt lakes, and marine sediments. Their genome sequences confirm their membership in a deeply branching clade of the Gammaproteobacteria. Several adaptations to heterogeneous habitats are apparent. Their genomes include large numbers of genes for sensing and responding to their environment (EAL- and GGDEF-domain proteins, and methyl-accepting chemotaxis proteins) despite their small sizes (2...
March 9, 2018: Environmental Microbiology
https://www.readbyqxmd.com/read/29480817/cancer-vaccine-formulation-dictates-synergy-with-ctla-4-and-pd-l1-checkpoint-blockade-therapy
#5
Yared Hailemichael, Amber Woods, Tihui Fu, Qiuming He, Michael C Nielsen, Farah Hasan, Jason Roszik, Zhilan Xiao, Christina Vianden, Hiep Khong, Manisha Singh, Meenu Sharma, Faisal Faak, Derek Moore, Zhimin Dai, Scott M Anthony, Kimberly S Schluns, Padmanee Sharma, Victor H Engelhard, Willem W Overwijk
Anticancer vaccination is a promising approach to increase the efficacy of cytotoxic T lymphocyte-associated protein 4 (CTLA-4) and programmed death ligand 1 (PD-L1) checkpoint blockade therapies. However, the landmark FDA registration trial for anti-CTLA-4 therapy (ipilimumab) revealed a complete lack of benefit of adding vaccination with gp100 peptide formulated in incomplete Freund's adjuvant (IFA). Here, using a mouse model of melanoma, we found that gp100 vaccination induced gp100-specific effector T cells (Teffs), which dominantly forced trafficking of anti-CTLA-4-induced, non-gp100-specific Teffs away from the tumor, reducing tumor control...
February 26, 2018: Journal of Clinical Investigation
https://www.readbyqxmd.com/read/29475824/characterizing-and-managing-missing-structured-data-in-electronic-health-records-data-analysis
#6
Brett K Beaulieu-Jones, Daniel R Lavage, John W Snyder, Jason H Moore, Sarah A Pendergrass, Christopher R Bauer
BACKGROUND: Missing data is a challenge for all studies; however, this is especially true for electronic health record (EHR)-based analyses. Failure to appropriately consider missing data can lead to biased results. While there has been extensive theoretical work on imputation, and many sophisticated methods are now available, it remains quite challenging for researchers to implement these methods appropriately. Here, we provide detailed procedures for when and how to conduct imputation of EHR laboratory results...
February 23, 2018: JMIR Medical Informatics
https://www.readbyqxmd.com/read/29467825/investigating-the-parameter-space-of-evolutionary-algorithms
#7
Moshe Sipper, Weixuan Fu, Karuna Ahuja, Jason H Moore
Evolutionary computation (EC) has been widely applied to biological and biomedical data. The practice of EC involves the tuning of many parameters, such as population size, generation count, selection size, and crossover and mutation rates. Through an extensive series of experiments over multiple evolutionary algorithm implementations and 25 problems we show that parameter space tends to be rife with viable parameters, at least for the problems studied herein. We discuss the implications of this finding in practice for the researcher employing EC...
2018: BioData Mining
https://www.readbyqxmd.com/read/29457381/a-multicentre-study-of-validity-and-reliability-of-responses-to-hand-cold-challenge-as-measured-by-laser-speckle-contrast-imaging-and-thermography-outcome-measures-for-systemic-sclerosis-related-raynaud-s-phenomenon
#8
Jack D Wilkinson, Sarah A Leggett, Elizabeth J Marjanovic, Tonia L Moore, John Allen, Marina E Anderson, Jason Britton, Maya H Buch, Francesco Del Galdo, Christopher P Denton, Graham Dinsdale, Bridgett Griffiths, Frances Hall, Kevin Howell, Audrey MacDonald, Neil J McHugh, Joanne B Manning, John D Pauling, Christopher Roberts, Jacqueline A Shipley, Ariane L Herrick, Andrea K Murray
BACKGROUND: Objective and reliable outcome measures to facilitate clinical trials of novel treatments for systemic sclerosis (SSc)-related Raynaud's phenomenon (RP) are badly needed. Laser speckle contrast imaging (LSCI) and thermography are non-invasive measures of perfusion that show excellent potential. The purpose of this multi-centre study was to determine the reliability and validity of a hand cold challenge protocol using LSCI, standard thermography and low-cost mobile phone-based thermography...
February 18, 2018: Arthritis & Rheumatology
https://www.readbyqxmd.com/read/29378062/medication-class-enrichment-analysis-a-novel-algorithm-to-analyze-multiple-pharmacologic-exposures-simultaneously-using-electronic-health-record-data
#9
Ravy K Vajravelu, Frank I Scott, Ronac Mamtani, Hongzhe Li, Jason H Moore, James D Lewis
Objective: Observational studies analyzing multiple exposures simultaneously have been limited by difficulty distinguishing relevant results from chance associations due to poor specificity. Set-based methods have been successfully used in genomics to improve signal-to-noise ratio. We present and demonstrate medication class enrichment analysis (MCEA), a signal-to-noise enhancement algorithm for observational data inspired by set-based methods. Materials and Methods: We used The Health Improvement Network database to study medications associated with Clostridium difficile infection (CDI)...
January 25, 2018: Journal of the American Medical Informatics Association: JAMIA
https://www.readbyqxmd.com/read/29377416/oncologic-outcomes-of-extended-neck-dissections-in-human-papillomavirus-related-oropharyngeal-squamous-cell-carcinoma
#10
Joseph Zenga, Patrik Pipkorn, Evan M Graboyes, Eliot J Martin, Jason T Rich, Eric J Moore, Bruce H Haughey, Ryan S Jackson
BACKGROUND: Oncologic outcomes of human papillomavirus (HPV)-related oropharyngeal squamous cell carcinoma (SCC) requiring resection of major muscular or neurovascular tissue during neck dissection for invasive nodal disease remain uncertain. METHODS: Patients with HPV-related oropharyngeal SCC requiring resection of major muscular or neurovascular tissue during their neck dissections were retrospectively identified. RESULTS: Seventy-two patients were included...
January 29, 2018: Head & Neck
https://www.readbyqxmd.com/read/29316397/discovery-of-potent-and-orally-bioavailable-dihydropyrazole-gpr40-agonists
#11
Jun Shi, Zhengxiang Gu, Elizabeth Anne Jurica, Ximao Wu, Lauren E Haque, Kristin N Williams, Andres S Hernandez, Zhenqiu Hong, Qi Gao, Marta Dabros, Akin H Davulcu, Arvind Mathur, Richard A Rampulla, Arun Kumar Gupta, Ramya Jayaram, Atsu Apedo, Douglas B Moore, Heng Liu, Lori K Kunselman, Edward J Brady, Jason J Wilkes, Bradley A Zinker, Hong Cai, Yue-Zhong Shu, Qin Sun, Elizabeth A Dierks, Kimberly A Foster, Carrie Xu, Tao Wang, Reshma Panemangalore, Mary Ellen Cvijic, Chunshan Xie, Gary G Cao, Min Zhou, John Krupinski, Jean M Whaley, Jeffrey A Robl, William R Ewing, Bruce Alan Ellsworth
G protein-coupled receptor 40 (GPR40) has become an attractive target for the treatment of diabetes since it was shown clinically to promote glucose-stimulated insulin secretion. Herein, we report our efforts to develop highly selective and potent GPR40 agonists with a dual mechanism of action, promoting both glucose-dependent insulin and incretin secretion. Employing strategies to increase polarity and the ratio of sp3 /sp2 character of the chemotype, we identified BMS-986118 (compound 4), which showed potent and selective GPR40 agonist activity in vitro...
February 8, 2018: Journal of Medicinal Chemistry
https://www.readbyqxmd.com/read/29238404/pmlb-a-large-benchmark-suite-for-machine-learning-evaluation-and-comparison
#12
Randal S Olson, William La Cava, Patryk Orzechowski, Ryan J Urbanowicz, Jason H Moore
Background: The selection, development, or comparison of machine learning methods in data mining can be a difficult task based on the target problem and goals of a particular study. Numerous publicly available real-world and simulated benchmark datasets have emerged from different sources, but their organization and adoption as standards have been inconsistent. As such, selecting and curating specific benchmarks remains an unnecessary burden on machine learning practitioners and data scientists...
2017: BioData Mining
https://www.readbyqxmd.com/read/29218913/leveraging-putative-enhancer-promoter-interactions-to-investigate-two-way-epistasis-in-type-2-diabetes-gwas
#13
Elisabetta Manduchi, Alessandra Chesi, Molly A Hall, Struan F A Grant, Jason H Moore
We utilized evidence for enhancer-promoter interactions from functional genomics data in order to build biological filters to narrow down the search space for two-way Single Nucleotide Polymorphism (SNP) interactions in Type 2 Diabetes (T2D) Genome Wide Association Studies (GWAS). This has led us to the identification of a reproducible statistically significant SNP pair associated with T2D. As more functional genomics data are being generated that can help identify potentially interacting enhancer-promoter pairs in larger collection of tissues/cells, this approach has implications for investigation of epistasis from GWAS in general...
2018: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/29218909/reading-between-the-genes-computational-models-to-discover-function-from-noncoding-dna
#14
Yves A Lussier, Joanne Berghout, Francesca Vitali, Kenneth S Ramos, Maricel Kann, Jason H Moore
Noncoding DNA - once called "junk" has revealed itself to be full of function. Technology development has allowed researchers to gather genome-scale data pointing towards complex regulatory regions, expression and function of noncoding RNA genes, and conserved elements. Variation in these regions has been tied to variation in biological function and human disease. This PSB session tackles the problem of handling, analyzing and interpreting the data relating to variation in and interactions between noncoding regions through computational biology...
2018: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/29218905/considerations-for-automated-machine-learning-in-clinical-metabolic-profiling-altered-homocysteine-plasma-concentration-associated-with-metformin-exposure
#15
Alena Orlenko, Jason H Moore, Patryk Orzechowski, Randal S Olson, Junmei Cairns, Pedro J Caraballo, Richard M Weinshilboum, Liewei Wang, Matthew K Breitenstein
With the maturation of metabolomics science and proliferation of biobanks, clinical metabolic profiling is an increasingly opportunistic frontier for advancing translational clinical research. Automated Machine Learning (AutoML) approaches provide exciting opportunity to guide feature selection in agnostic metabolic profiling endeavors, where potentially thousands of independent data points must be evaluated. In previous research, AutoML using high-dimensional data of varying types has been demonstrably robust, outperforming traditional approaches...
2018: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/29218887/a-heuristic-method-for-simulating-open-data-of-arbitrary-complexity-that-can-be-used-to-compare-and-evaluate-machine-learning-methods
#16
Jason H Moore, Maksim Shestov, Peter Schmitt, Randal S Olson
A central challenge of developing and evaluating artificial intelligence and machine learning methods for regression and classification is access to data that illuminates the strengths and weaknesses of different methods. Open data plays an important role in this process by making it easy for computational researchers to easily access real data for this purpose. Genomics has in some examples taken a leading role in the open data effort starting with DNA microarrays. While real data from experimental and observational studies is necessary for developing computational methods it is not sufficient...
2018: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/29218881/data-driven-advice-for-applying-machine-learning-to-bioinformatics-problems
#17
Randal S Olson, William La Cava, Zairah Mustahsan, Akshay Varik, Jason H Moore
As the bioinformatics field grows, it must keep pace not only with new data but with new algorithms. Here we contribute a thorough analysis of 13 state-of-the-art, commonly used machine learning algorithms on a set of 165 publicly available classification problems in order to provide data-driven algorithm recommendations to current researchers. We present a number of statistical and visual comparisons of algorithm performance and quantify the effect of model selection and algorithm tuning for each algorithm and dataset...
2018: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/29218875/mapping-patient-trajectories-using-longitudinal-extraction-and-deep-learning-in-the-mimic-iii-critical-care-database
#18
Brett K Beaulieu-Jones, Patryk Orzechowski, Jason H Moore
Electronic Health Records (EHRs) contain a wealth of patient data useful to biomedical researchers. At present, both the extraction of data and methods for analyses are frequently designed to work with a single snapshot of a patient's record. Health care providers often perform and record actions in small batches over time. By extracting these care events, a sequence can be formed providing a trajectory for a patient's interactions with the health care system. These care events also offer a basic heuristic for the level of attention a patient receives from health care providers...
2018: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/29215023/a-pilot-characterization-of-the-human-chronobiome
#19
Carsten Skarke, Nicholas F Lahens, Seth D Rhoades, Amy Campbell, Kyle Bittinger, Aubrey Bailey, Christian Hoffmann, Randal S Olson, Lihong Chen, Guangrui Yang, Thomas S Price, Jason H Moore, Frederic D Bushman, Casey S Greene, Gregory R Grant, Aalim M Weljie, Garret A FitzGerald
Physiological function, disease expression and drug effects vary by time-of-day. Clock disruption in mice results in cardio-metabolic, immunological and neurological dysfunction; circadian misalignment using forced desynchrony increases cardiovascular risk factors in humans. Here we integrated data from remote sensors, physiological and multi-omics analyses to assess the feasibility of detecting time dependent signals - the chronobiome - despite the "noise" attributable to the behavioral differences of free-living human volunteers...
December 7, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29213332/artificial-intelligence-more-human-with-human
#20
Moshe Sipper, Jason H Moore
No abstract text is available yet for this article.
2017: BioData Mining
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