Real-time, high-throughput measurements of peptide-MHC-I dissociation using a scintillation proximity assay

DEFF Research Database (Denmark)

Harndahl, Mikkel; Rasmussen, Michael; Røder, Gustav Andreas

2011-01-01

and it is well suited for high-throughput screening. To exemplify this, we screened a panel of 384 high-affinity peptides binding to the MHC class I molecule, HLA-A*02:01, and observed the rates of dissociation that ranged from 0.1h to 46h depending on the peptide used.......Efficient presentation of peptide-MHC class I complexes to immune T cells depends upon stable peptide-MHC class I interactions. Theoretically, determining the rate of dissociation of a peptide-MHC class I complexes is straightforward; in practical terms, however, generating the accurate and closely...... timed data needed to determine the rate of dissociation is not simple. Ideally, one should use a homogenous assay involving an inexhaustible and label-free assay principle. Here, we present a homogenous, high-throughput peptide-MHC class I dissociation assay, which by and large fulfill these ideal...

High-throughput scoring of seed germination

NARCIS (Netherlands)

Ligterink, Wilco; Hilhorst, Henk W.M.

2017-01-01

High-throughput analysis of seed germination for phenotyping large genetic populations or mutant collections is very labor intensive and would highly benefit from an automated setup. Although very often used, the total germination percentage after a nominated period of time is not very

TimesVector: a vectorized clustering approach to the analysis of time series transcriptome data from multiple phenotypes.

Science.gov (United States)

Jung, Inuk; Jo, Kyuri; Kang, Hyejin; Ahn, Hongryul; Yu, Youngjae; Kim, Sun

2017-12-01

Identifying biologically meaningful gene expression patterns from time series gene expression data is important to understand the underlying biological mechanisms. To identify significantly perturbed gene sets between different phenotypes, analysis of time series transcriptome data requires consideration of time and sample dimensions. Thus, the analysis of such time series data seeks to search gene sets that exhibit similar or different expression patterns between two or more sample conditions, constituting the three-dimensional data, i.e. gene-time-condition. Computational complexity for analyzing such data is very high, compared to the already difficult NP-hard two dimensional biclustering algorithms. Because of this challenge, traditional time series clustering algorithms are designed to capture co-expressed genes with similar expression pattern in two sample conditions. We present a triclustering algorithm, TimesVector, specifically designed for clustering three-dimensional time series data to capture distinctively similar or different gene expression patterns between two or more sample conditions. TimesVector identifies clusters with distinctive expression patterns in three steps: (i) dimension reduction and clustering of time-condition concatenated vectors, (ii) post-processing clusters for detecting similar and distinct expression patterns and (iii) rescuing genes from unclassified clusters. Using four sets of time series gene expression data, generated by both microarray and high throughput sequencing platforms, we demonstrated that TimesVector successfully detected biologically meaningful clusters of high quality. TimesVector improved the clustering quality compared to existing triclustering tools and only TimesVector detected clusters with differential expression patterns across conditions successfully. The TimesVector software is available at http://biohealth.snu.ac.kr/software/TimesVector/. sunkim.bioinfo@snu.ac.kr. Supplementary data are available at

High Throughput Facility

Data.gov (United States)

Federal Laboratory Consortium — Argonne?s high throughput facility provides highly automated and parallel approaches to material and materials chemistry development. The facility allows scientists...

Integrated Automation of High-Throughput Screening and Reverse Phase Protein Array Sample Preparation

DEFF Research Database (Denmark)

Pedersen, Marlene Lemvig; Block, Ines; List, Markus

into automated robotic high-throughput screens, which allows subsequent protein quantification. In this integrated solution, samples are directly forwarded to automated cell lysate preparation and preparation of dilution series, including reformatting to a protein spotter-compatible format after the high......-throughput screening. Tracking of huge sample numbers and data analysis from a high-content screen to RPPAs is accomplished via MIRACLE, a custom made software suite developed by us. To this end, we demonstrate that the RPPAs generated in this manner deliver reliable protein readouts and that GAPDH and TFR levels can...

Ultra-high throughput real-time instruments for capturing fast signals and rare events

Science.gov (United States)

Buckley, Brandon Walter

Wide-band signals play important roles in the most exciting areas of science, engineering, and medicine. To keep up with the demands of exploding internet traffic, modern data centers and communication networks are employing increasingly faster data rates. Wide-band techniques such as pulsed radar jamming and spread spectrum frequency hopping are used on the battlefield to wrestle control of the electromagnetic spectrum. Neurons communicate with each other using transient action potentials that last for only milliseconds at a time. And in the search for rare cells, biologists flow large populations of cells single file down microfluidic channels, interrogating them one-by-one, tens of thousands of times per second. Studying and enabling such high-speed phenomena pose enormous technical challenges. For one, parasitic capacitance inherent in analog electrical components limits their response time. Additionally, converting these fast analog signals to the digital domain requires enormous sampling speeds, which can lead to significant jitter and distortion. State-of-the-art imaging technologies, essential for studying biological dynamics and cells in flow, are limited in speed and sensitivity by finite charge transfer and read rates, and by the small numbers of photo-electrons accumulated in short integration times. And finally, ultra-high throughput real-time digital processing is required at the backend to analyze the streaming data. In this thesis, I discuss my work in developing real-time instruments, employing ultrafast optical techniques, which overcome some of these obstacles. In particular, I use broadband dispersive optics to slow down fast signals to speeds accessible to high-bit depth digitizers and signal processors. I also apply telecommunication multiplexing techniques to boost the speeds of confocal fluorescence microscopy. The photonic time stretcher (TiSER) uses dispersive Fourier transformation to slow down analog signals before digitization and

Applications of ambient mass spectrometry in high-throughput screening.

Science.gov (United States)

Li, Li-Ping; Feng, Bao-Sheng; Yang, Jian-Wang; Chang, Cui-Lan; Bai, Yu; Liu, Hu-Wei

2013-06-07

The development of rapid screening and identification techniques is of great importance for drug discovery, doping control, forensic identification, food safety and quality control. Ambient mass spectrometry (AMS) allows rapid and direct analysis of various samples in open air with little sample preparation. Recently, its applications in high-throughput screening have been in rapid progress. During the past decade, various ambient ionization techniques have been developed and applied in high-throughput screening. This review discusses typical applications of AMS, including DESI (desorption electrospray ionization), DART (direct analysis in real time), EESI (extractive electrospray ionization), etc., in high-throughput screening (HTS).

A high throughput DNA extraction method with high yield and quality

Directory of Open Access Journals (Sweden)

Xin Zhanguo

2012-07-01

Full Text Available Abstract Background Preparation of large quantity and high quality genomic DNA from a large number of plant samples is a major bottleneck for most genetic and genomic analyses, such as, genetic mapping, TILLING (Targeting Induced Local Lesion IN Genome, and next-generation sequencing directly from sheared genomic DNA. A variety of DNA preparation methods and commercial kits are available. However, they are either low throughput, low yield, or costly. Here, we describe a method for high throughput genomic DNA isolation from sorghum [Sorghum bicolor (L. Moench] leaves and dry seeds with high yield, high quality, and affordable cost. Results We developed a high throughput DNA isolation method by combining a high yield CTAB extraction method with an improved cleanup procedure based on MagAttract kit. The method yielded large quantity and high quality DNA from both lyophilized sorghum leaves and dry seeds. The DNA yield was improved by nearly 30 fold with 4 times less consumption of MagAttract beads. The method can also be used in other plant species, including cotton leaves and pine needles. Conclusion A high throughput system for DNA extraction from sorghum leaves and seeds was developed and validated. The main advantages of the method are low cost, high yield, high quality, and high throughput. One person can process two 96-well plates in a working day at a cost of $0.10 per sample of magnetic beads plus other consumables that other methods will also need.

Subtyping of swine influenza viruses using a high-throughput real time PCR platform

DEFF Research Database (Denmark)

Goecke, Nicole Bakkegård; Krog, Jesper Schak; Hjulsager, Charlotte Kristiane

). The results revealed that the performance of the dynamic chip was similar to conventional real time analysis. Discussion and conclusion. Application of the chip for subtyping of swine influenza has resulted in a significant reduction in time, cost and working hours. Thereby, it is possible to offer diagnostic...... test and subsequent subtyping is performed by real time RT-PCR (RT-qPCR) but several assays are needed to cover the wide range of circulating subtypes which is expensive,resource and time demanding. To mitigate these restrictions the high-throughput qPCR platform BioMark (Fluidigm) has been explored...... services with reduced price and turnover time which will facilitate choice of vaccines and by that lead to reduction of antibiotic used....

Multispot single-molecule FRET: High-throughput analysis of freely diffusing molecules.

Directory of Open Access Journals (Sweden)

Antonino Ingargiola

Full Text Available We describe an 8-spot confocal setup for high-throughput smFRET assays and illustrate its performance with two characteristic experiments. First, measurements on a series of freely diffusing doubly-labeled dsDNA samples allow us to demonstrate that data acquired in multiple spots in parallel can be properly corrected and result in measured sample characteristics consistent with those obtained with a standard single-spot setup. We then take advantage of the higher throughput provided by parallel acquisition to address an outstanding question about the kinetics of the initial steps of bacterial RNA transcription. Our real-time kinetic analysis of promoter escape by bacterial RNA polymerase confirms results obtained by a more indirect route, shedding additional light on the initial steps of transcription. Finally, we discuss the advantages of our multispot setup, while pointing potential limitations of the current single laser excitation design, as well as analysis challenges and their solutions.

High throughput imaging cytometer with acoustic focussing.

Science.gov (United States)

Zmijan, Robert; Jonnalagadda, Umesh S; Carugo, Dario; Kochi, Yu; Lemm, Elizabeth; Packham, Graham; Hill, Martyn; Glynne-Jones, Peter

2015-10-31

We demonstrate an imaging flow cytometer that uses acoustic levitation to assemble cells and other particles into a sheet structure. This technique enables a high resolution, low noise CMOS camera to capture images of thousands of cells with each frame. While ultrasonic focussing has previously been demonstrated for 1D cytometry systems, extending the technology to a planar, much higher throughput format and integrating imaging is non-trivial, and represents a significant jump forward in capability, leading to diagnostic possibilities not achievable with current systems. A galvo mirror is used to track the images of the moving cells permitting exposure times of 10 ms at frame rates of 50 fps with motion blur of only a few pixels. At 80 fps, we demonstrate a throughput of 208 000 beads per second. We investigate the factors affecting motion blur and throughput, and demonstrate the system with fluorescent beads, leukaemia cells and a chondrocyte cell line. Cells require more time to reach the acoustic focus than beads, resulting in lower throughputs; however a longer device would remove this constraint.

High-throughput sample adaptive offset hardware architecture for high-efficiency video coding

Science.gov (United States)

Zhou, Wei; Yan, Chang; Zhang, Jingzhi; Zhou, Xin

2018-03-01

A high-throughput hardware architecture for a sample adaptive offset (SAO) filter in the high-efficiency video coding video coding standard is presented. First, an implementation-friendly and simplified bitrate estimation method of rate-distortion cost calculation is proposed to reduce the computational complexity in the mode decision of SAO. Then, a high-throughput VLSI architecture for SAO is presented based on the proposed bitrate estimation method. Furthermore, multiparallel VLSI architecture for in-loop filters, which integrates both deblocking filter and SAO filter, is proposed. Six parallel strategies are applied in the proposed in-loop filters architecture to improve the system throughput and filtering speed. Experimental results show that the proposed in-loop filters architecture can achieve up to 48% higher throughput in comparison with prior work. The proposed architecture can reach a high-operating clock frequency of 297 MHz with TSMC 65-nm library and meet the real-time requirement of the in-loop filters for 8 K × 4 K video format at 132 fps.

Selection and optimization of hits from a high-throughput phenotypic screen against Trypanosoma cruzi.

Science.gov (United States)

Keenan, Martine; Alexander, Paul W; Chaplin, Jason H; Abbott, Michael J; Diao, Hugo; Wang, Zhisen; Best, Wayne M; Perez, Catherine J; Cornwall, Scott M J; Keatley, Sarah K; Thompson, R C Andrew; Charman, Susan A; White, Karen L; Ryan, Eileen; Chen, Gong; Ioset, Jean-Robert; von Geldern, Thomas W; Chatelain, Eric

2013-10-01

Inhibitors of Trypanosoma cruzi with novel mechanisms of action are urgently required to diversify the current clinical and preclinical pipelines. Increasing the number and diversity of hits available for assessment at the beginning of the discovery process will help to achieve this aim. We report the evaluation of multiple hits generated from a high-throughput screen to identify inhibitors of T. cruzi and from these studies the discovery of two novel series currently in lead optimization. Lead compounds from these series potently and selectively inhibit growth of T. cruzi in vitro and the most advanced compound is orally active in a subchronic mouse model of T. cruzi infection. High-throughput screening of novel compound collections has an important role to play in diversifying the trypanosomatid drug discovery portfolio. A new T. cruzi inhibitor series with good drug-like properties and promising in vivo efficacy has been identified through this process.

High-Throughput Scoring of Seed Germination.

Science.gov (United States)

Ligterink, Wilco; Hilhorst, Henk W M

2017-01-01

High-throughput analysis of seed germination for phenotyping large genetic populations or mutant collections is very labor intensive and would highly benefit from an automated setup. Although very often used, the total germination percentage after a nominated period of time is not very informative as it lacks information about start, rate, and uniformity of germination, which are highly indicative of such traits as dormancy, stress tolerance, and seed longevity. The calculation of cumulative germination curves requires information about germination percentage at various time points. We developed the GERMINATOR package: a simple, highly cost-efficient, and flexible procedure for high-throughput automatic scoring and evaluation of germination that can be implemented without the use of complex robotics. The GERMINATOR package contains three modules: (I) design of experimental setup with various options to replicate and randomize samples; (II) automatic scoring of germination based on the color contrast between the protruding radicle and seed coat on a single image; and (III) curve fitting of cumulative germination data and the extraction, recap, and visualization of the various germination parameters. GERMINATOR is a freely available package that allows the monitoring and analysis of several thousands of germination tests, several times a day by a single person.

High-throughput continuous cryopump

International Nuclear Information System (INIS)

Foster, C.A.

1986-01-01

A cryopump with a unique method of regeneration which allows continuous operation at high throughput has been constructed and tested. Deuterium was pumped continuously at a throughput of 30 Torr.L/s at a speed of 2000 L/s and a compression ratio of 200. Argon was pumped at a throughput of 60 Torr.L/s at a speed of 1275 L/s. To produce continuous operation of the pump, a method of regeneration that does not thermally cycle the pump is employed. A small chamber (the ''snail'') passes over the pumping surface and removes the frost from it either by mechanical action with a scraper or by local heating. The material removed is topologically in a secondary vacuum system with low conductance into the primary vacuum; thus, the exhaust can be pumped at pressures up to an effective compression ratio determined by the ratio of the pumping speed to the leakage conductance of the snail. The pump, which is all-metal-sealed and dry and which regenerates every 60 s, would be an ideal system for pumping tritium. Potential fusion applications are for mpmp limiters, for repeating pneumatic pellet injection lines, and for the centrifuge pellet injector spin tank, all of which will require pumping tritium at high throughput. Industrial applications requiring ultraclean pumping of corrosive gases at high throughput, such as the reactive ion etch semiconductor process, may also be feasible

A high-throughput pipeline for the design of real-time PCR signatures

Directory of Open Access Journals (Sweden)

Reifman Jaques

2010-06-01

Full Text Available Abstract Background Pathogen diagnostic assays based on polymerase chain reaction (PCR technology provide high sensitivity and specificity. However, the design of these diagnostic assays is computationally intensive, requiring high-throughput methods to identify unique PCR signatures in the presence of an ever increasing availability of sequenced genomes. Results We present the Tool for PCR Signature Identification (TOPSI, a high-performance computing pipeline for the design of PCR-based pathogen diagnostic assays. The TOPSI pipeline efficiently designs PCR signatures common to multiple bacterial genomes by obtaining the shared regions through pairwise alignments between the input genomes. TOPSI successfully designed PCR signatures common to 18 Staphylococcus aureus genomes in less than 14 hours using 98 cores on a high-performance computing system. Conclusions TOPSI is a computationally efficient, fully integrated tool for high-throughput design of PCR signatures common to multiple bacterial genomes. TOPSI is freely available for download at http://www.bhsai.org/downloads/topsi.tar.gz.

Estimating High-Dimensional Time Series Models

DEFF Research Database (Denmark)

Medeiros, Marcelo C.; Mendes, Eduardo F.

We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume both the number of covariates in the model and candidate variables can increase with the number of observations and the number of candidate variables is, possibly......, larger than the number of observations. We show the adaLASSO consistently chooses the relevant variables as the number of observations increases (model selection consistency), and has the oracle property, even when the errors are non-Gaussian and conditionally heteroskedastic. A simulation study shows...

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience

Science.gov (United States)

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R.; Bock, Davi D.; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C.; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R. Clay; Smith, Stephen J.; Szalay, Alexander S.; Vogelstein, Joshua T.; Vogelstein, R. Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes— neural connectivity maps of the brain—using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems—reads to parallel disk arrays and writes to solid-state storage—to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization. PMID:24401992

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience.

Science.gov (United States)

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R; Bock, Davi D; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R Clay; Smith, Stephen J; Szalay, Alexander S; Vogelstein, Joshua T; Vogelstein, R Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes - neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

Research on combination forecast of port cargo throughput based on time series and causality analysis

Directory of Open Access Journals (Sweden)

Chi Zhang

2013-03-01

Full Text Available Purpose: The purpose of this paper is to develop a combined model composed of grey-forecast model and Logistic-growth-curve model to improve the accuracy of forecast model of cargo throughput for the port. The authors also use the existing data of a current port to verify the validity of the combined model.Design/methodology/approach: A literature review is undertaken to find the appropriate forecast model of cargo throughput for the port. Through researching the related forecast model, the authors put together the individual models which are significant to study further. Finally, the authors combine two individual models (grey-forecast model and Logistic-growth-curve model into one combined model to forecast the port cargo throughput, and use the model to a physical port in China to testify the validity of the model.Findings: Test by the perceptional data of cargo throughput in the physical port, the results show that the combined model can obtain relatively higher forecast accuracy when it is not easy to find more information. Furthermore, the forecast made by the combined model are more accurate than any of the individual ones.Research limitations/implications: The study provided a new combined forecast model of cargo throughput with a relatively less information to improve the accuracy rate of the forecast. The limitation of the model is that it requires the cargo throughput of the port have an S-shaped change trend.Practical implications: This model is not limited by external conditions such as geographical, cultural. This model predicted the port cargo throughput of one real port in China in 2015, which provided some instructive guidance for the port development.Originality/value: This is the one of the study to improve the accuracy rate of the cargo throughput forecast with little information.

Towards sensitive, high-throughput, biomolecular assays based on fluorescence lifetime

Science.gov (United States)

Ioanna Skilitsi, Anastasia; Turko, Timothé; Cianfarani, Damien; Barre, Sophie; Uhring, Wilfried; Hassiepen, Ulrich; Léonard, Jérémie

2017-09-01

Time-resolved fluorescence detection for robust sensing of biomolecular interactions is developed by implementing time-correlated single photon counting in high-throughput conditions. Droplet microfluidics is used as a promising platform for the very fast handling of low-volume samples. We illustrate the potential of this very sensitive and cost-effective technology in the context of an enzymatic activity assay based on fluorescently-labeled biomolecules. Fluorescence lifetime detection by time-correlated single photon counting is shown to enable reliable discrimination between positive and negative control samples at a throughput as high as several hundred samples per second.

Modeling Steroidogenesis Disruption Using High-Throughput ...

Science.gov (United States)

Environmental chemicals can elicit endocrine disruption by altering steroid hormone biosynthesis and metabolism (steroidogenesis) causing adverse reproductive and developmental effects. Historically, a lack of assays resulted in few chemicals having been evaluated for effects on steroidogenesis. The steroidogenic pathway is a series of hydroxylation and dehydrogenation steps carried out by CYP450 and hydroxysteroid dehydrogenase enzymes, yet the only enzyme in the pathway for which a high-throughput screening (HTS) assay has been developed is aromatase (CYP19A1), responsible for the aromatization of androgens to estrogens. Recently, the ToxCast HTS program adapted the OECD validated H295R steroidogenesis assay using human adrenocortical carcinoma cells into a high-throughput model to quantitatively assess the concentration-dependent (0.003-100 µM) effects of chemicals on 10 steroid hormones including progestagens, androgens, estrogens and glucocorticoids. These results, in combination with two CYP19A1 inhibition assays, comprise a large dataset amenable to clustering approaches supporting the identification and characterization of putative mechanisms of action (pMOA) for steroidogenesis disruption. In total, 514 chemicals were tested in all CYP19A1 and steroidogenesis assays. 216 chemicals were identified as CYP19A1 inhibitors in at least one CYP19A1 assay. 208 of these chemicals also altered hormone levels in the H295R assay, suggesting 96% sensitivity in the

High-Throughput Accurate Single-Cell Screening of Euglena gracilis with Fluorescence-Assisted Optofluidic Time-Stretch Microscopy.

Directory of Open Access Journals (Sweden)

Baoshan Guo

Full Text Available The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, algal biofuel is expected to play a key role in alleviating global warming since algae absorb atmospheric CO2 via photosynthesis. Among various algae for fuel production, Euglena gracilis is an attractive microalgal species as it is known to produce wax ester (good for biodiesel and aviation fuel within lipid droplets. To date, while there exist many techniques for inducing microalgal cells to produce and accumulate lipid with high efficiency, few analytical methods are available for characterizing a population of such lipid-accumulated microalgae including E. gracilis with high throughout, high accuracy, and single-cell resolution simultaneously. Here we demonstrate high-throughput, high-accuracy, single-cell screening of E. gracilis with fluorescence-assisted optofluidic time-stretch microscopy-a method that combines the strengths of microfluidic cell focusing, optical time-stretch microscopy, and fluorescence detection used in conventional flow cytometry. Specifically, our fluorescence-assisted optofluidic time-stretch microscope consists of an optical time-stretch microscope and a fluorescence analyzer on top of a hydrodynamically focusing microfluidic device and can detect fluorescence from every E. gracilis cell in a population and simultaneously obtain its image with a high throughput of 10,000 cells/s. With the multi-dimensional information acquired by the system, we classify nitrogen-sufficient (ordinary and nitrogen-deficient (lipid-accumulated E. gracilis cells with a low false positive rate of 1.0%. This method holds promise for evaluating cultivation techniques and selective breeding for microalgae-based biofuel production.

CellProfiler Tracer: exploring and validating high-throughput, time-lapse microscopy image data.

Science.gov (United States)

Bray, Mark-Anthony; Carpenter, Anne E

2015-11-04

Time-lapse analysis of cellular images is an important and growing need in biology. Algorithms for cell tracking are widely available; what researchers have been missing is a single open-source software package to visualize standard tracking output (from software like CellProfiler) in a way that allows convenient assessment of track quality, especially for researchers tuning tracking parameters for high-content time-lapse experiments. This makes quality assessment and algorithm adjustment a substantial challenge, particularly when dealing with hundreds of time-lapse movies collected in a high-throughput manner. We present CellProfiler Tracer, a free and open-source tool that complements the object tracking functionality of the CellProfiler biological image analysis package. Tracer allows multi-parametric morphological data to be visualized on object tracks, providing visualizations that have already been validated within the scientific community for time-lapse experiments, and combining them with simple graph-based measures for highlighting possible tracking artifacts. CellProfiler Tracer is a useful, free tool for inspection and quality control of object tracking data, available from http://www.cellprofiler.org/tracer/.

A method for generating high resolution satellite image time series

Science.gov (United States)

Guo, Tao

2014-10-01

There is an increasing demand for satellite remote sensing data with both high spatial and temporal resolution in many applications. But it still is a challenge to simultaneously improve spatial resolution and temporal frequency due to the technical limits of current satellite observation systems. To this end, much R&D efforts have been ongoing for years and lead to some successes roughly in two aspects, one includes super resolution, pan-sharpen etc. methods which can effectively enhance the spatial resolution and generate good visual effects, but hardly preserve spectral signatures and result in inadequate analytical value, on the other hand, time interpolation is a straight forward method to increase temporal frequency, however it increase little informative contents in fact. In this paper we presented a novel method to simulate high resolution time series data by combing low resolution time series data and a very small number of high resolution data only. Our method starts with a pair of high and low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and then projected onto the high resolution data plane and assigned to each high resolution pixel according to the predefined temporal change patterns of each type of ground objects. Finally the simulated high resolution data is generated. A preliminary experiment shows that our method can simulate a high resolution data with a reasonable accuracy. The contribution of our method is to enable timely monitoring of temporal changes through analysis of time sequence of low resolution images only, and usage of costly high resolution data can be reduces as much as possible, and it presents a highly effective way to build up an economically operational monitoring solution for agriculture, forest, land use investigation

High-throughput screening of ionic conductivity in polymer membranes

International Nuclear Information System (INIS)

Zapata, Pedro; Basak, Pratyay; Carson Meredith, J.

2009-01-01

Combinatorial and high-throughput techniques have been successfully used for efficient and rapid property screening in multiple fields. The use of these techniques can be an advantageous new approach to assay ionic conductivity and accelerate the development of novel materials in research areas such as fuel cells. A high-throughput ionic conductivity (HTC) apparatus is described and applied to screening candidate polymer electrolyte membranes for fuel cell applications. The device uses a miniature four-point probe for rapid, automated point-to-point AC electrochemical impedance measurements in both liquid and humid air environments. The conductivity of Nafion 112 HTC validation standards was within 1.8% of the manufacturer's specification. HTC screening of 40 novel Kynar poly(vinylidene fluoride) (PVDF)/acrylic polyelectrolyte (PE) membranes focused on varying the Kynar type (5x) and PE composition (8x) using reduced sample sizes. Two factors were found to be significant in determining the proton conducting capacity: (1) Kynar PVDF series: membranes containing a particular Kynar PVDF type exhibited statistically identical mean conductivity as other membranes containing different Kynar PVDF types that belong to the same series or family. (2) Maximum effective amount of polyelectrolyte: increments in polyelectrolyte content from 55 wt% to 60 wt% showed no statistically significant effect in increasing conductivity. In fact, some membranes experienced a reduction in conductivity.

High throughput integrated thermal characterization with non-contact optical calorimetry

Science.gov (United States)

Hou, Sichao; Huo, Ruiqing; Su, Ming

2017-10-01

Commonly used thermal analysis tools such as calorimeter and thermal conductivity meter are separated instruments and limited by low throughput, where only one sample is examined each time. This work reports an infrared based optical calorimetry with its theoretical foundation, which is able to provide an integrated solution to characterize thermal properties of materials with high throughput. By taking time domain temperature information of spatially distributed samples, this method allows a single device (infrared camera) to determine the thermal properties of both phase change systems (melting temperature and latent heat of fusion) and non-phase change systems (thermal conductivity and heat capacity). This method further allows these thermal properties of multiple samples to be determined rapidly, remotely, and simultaneously. In this proof-of-concept experiment, the thermal properties of a panel of 16 samples including melting temperatures, latent heats of fusion, heat capacities, and thermal conductivities have been determined in 2 min with high accuracy. Given the high thermal, spatial, and temporal resolutions of the advanced infrared camera, this method has the potential to revolutionize the thermal characterization of materials by providing an integrated solution with high throughput, high sensitivity, and short analysis time.

DAG expression: high-throughput gene expression analysis of real-time PCR data using standard curves for relative quantification.

Directory of Open Access Journals (Sweden)

María Ballester

Full Text Available BACKGROUND: Real-time quantitative PCR (qPCR is still the gold-standard technique for gene-expression quantification. Recent technological advances of this method allow for the high-throughput gene-expression analysis, without the limitations of sample space and reagent used. However, non-commercial and user-friendly software for the management and analysis of these data is not available. RESULTS: The recently developed commercial microarrays allow for the drawing of standard curves of multiple assays using the same n-fold diluted samples. Data Analysis Gene (DAG Expression software has been developed to perform high-throughput gene-expression data analysis using standard curves for relative quantification and one or multiple reference genes for sample normalization. We discuss the application of DAG Expression in the analysis of data from an experiment performed with Fluidigm technology, in which 48 genes and 115 samples were measured. Furthermore, the quality of our analysis was tested and compared with other available methods. CONCLUSIONS: DAG Expression is a freely available software that permits the automated analysis and visualization of high-throughput qPCR. A detailed manual and a demo-experiment are provided within the DAG Expression software at http://www.dagexpression.com/dage.zip.

The high throughput biomedicine unit at the institute for molecular medicine Finland: high throughput screening meets precision medicine.

Science.gov (United States)

Pietiainen, Vilja; Saarela, Jani; von Schantz, Carina; Turunen, Laura; Ostling, Paivi; Wennerberg, Krister

2014-05-01

The High Throughput Biomedicine (HTB) unit at the Institute for Molecular Medicine Finland FIMM was established in 2010 to serve as a national and international academic screening unit providing access to state of the art instrumentation for chemical and RNAi-based high throughput screening. The initial focus of the unit was multiwell plate based chemical screening and high content microarray-based siRNA screening. However, over the first four years of operation, the unit has moved to a more flexible service platform where both chemical and siRNA screening is performed at different scales primarily in multiwell plate-based assays with a wide range of readout possibilities with a focus on ultraminiaturization to allow for affordable screening for the academic users. In addition to high throughput screening, the equipment of the unit is also used to support miniaturized, multiplexed and high throughput applications for other types of research such as genomics, sequencing and biobanking operations. Importantly, with the translational research goals at FIMM, an increasing part of the operations at the HTB unit is being focused on high throughput systems biological platforms for functional profiling of patient cells in personalized and precision medicine projects.

High throughput generation and trapping of individual agarose microgel using microfluidic approach

KAUST Repository

Shi, Yang

2013-02-28

Microgel is a kind of biocompatible polymeric material, which has been widely used as micro-carriers in materials synthesis, drug delivery and cell biology applications. However, high-throughput generation of individual microgel for on-site analysis in a microdevice still remains a challenge. Here, we presented a simple and stable droplet microfluidic system to realize high-throughput generation and trapping of individual agarose microgels based on the synergetic effect of surface tension and hydrodynamic forces in microchannels and used it for 3-D cell culture in real-time. The established system was mainly composed of droplet generators with flow focusing T-junction and a series of array individual trap structures. The whole process including the independent agarose microgel formation, immobilization in trapping array and gelation in situ via temperature cooling could be realized on the integrated microdevice completely. The performance of this system was demonstrated by successfully encapsulating and culturing adenoid cystic carcinoma (ACCM) cells in the gelated agarose microgels. This established approach is simple, easy to operate, which can not only generate the micro-carriers with different components in parallel, but also monitor the cell behavior in 3D matrix in real-time. It can also be extended for applications in the area of material synthesis and tissue engineering. © 2013 Springer-Verlag Berlin Heidelberg.

High throughput generation and trapping of individual agarose microgel using microfluidic approach

KAUST Repository

Shi, Yang; Gao, Xinghua; Chen, Longqing; Zhang, Min; Ma, Jingyun; Zhang, Xixiang; Qin, Jianhua

2013-01-01

Microgel is a kind of biocompatible polymeric material, which has been widely used as micro-carriers in materials synthesis, drug delivery and cell biology applications. However, high-throughput generation of individual microgel for on-site analysis in a microdevice still remains a challenge. Here, we presented a simple and stable droplet microfluidic system to realize high-throughput generation and trapping of individual agarose microgels based on the synergetic effect of surface tension and hydrodynamic forces in microchannels and used it for 3-D cell culture in real-time. The established system was mainly composed of droplet generators with flow focusing T-junction and a series of array individual trap structures. The whole process including the independent agarose microgel formation, immobilization in trapping array and gelation in situ via temperature cooling could be realized on the integrated microdevice completely. The performance of this system was demonstrated by successfully encapsulating and culturing adenoid cystic carcinoma (ACCM) cells in the gelated agarose microgels. This established approach is simple, easy to operate, which can not only generate the micro-carriers with different components in parallel, but also monitor the cell behavior in 3D matrix in real-time. It can also be extended for applications in the area of material synthesis and tissue engineering. © 2013 Springer-Verlag Berlin Heidelberg.

High throughput materials research and development for lithium ion batteries

Directory of Open Access Journals (Sweden)

Parker Liu

2017-09-01

Full Text Available Development of next generation batteries requires a breakthrough in materials. Traditional one-by-one method, which is suitable for synthesizing large number of sing-composition material, is time-consuming and costly. High throughput and combinatorial experimentation, is an effective method to synthesize and characterize huge amount of materials over a broader compositional region in a short time, which enables to greatly speed up the discovery and optimization of materials with lower cost. In this work, high throughput and combinatorial materials synthesis technologies for lithium ion battery research are discussed, and our efforts on developing such instrumentations are introduced.

High-throughput microfluidics automated cytogenetic processing for effectively lowering biological process time and aid triage during radiation accidents

International Nuclear Information System (INIS)

Ramakumar, Adarsh

2016-01-01

Nuclear or radiation mass casualties require individual, rapid, and accurate dose-based triage of exposed subjects for cytokine therapy and supportive care, to save life. Radiation mass casualties will demand high-throughput individual diagnostic dose assessment for medical management of exposed subjects. Cytogenetic techniques are widely used for triage and definitive radiation biodosimetry. Prototype platform to demonstrate high-throughput microfluidic micro incubation to support the logistics of sample in miniaturized incubators from the site of accident to analytical labs has been developed. Efforts have been made, both at the level of developing concepts and advanced system for higher throughput in processing the samples and also implementing better and efficient methods of logistics leading to performance of lab-on-chip analyses. Automated high-throughput platform with automated feature extraction, storage, cross platform data linkage, cross platform validation and inclusion of multi-parametric biomarker approaches will provide the first generation high-throughput platform systems for effective medical management, particularly during radiation mass casualty events

High-throughput sequence alignment using Graphics Processing Units

Directory of Open Access Journals (Sweden)

Trapnell Cole

2007-12-01

Full Text Available Abstract Background The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and de novo genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies. Results This paper describes MUMmerGPU, an open-source high-throughput parallel pairwise local sequence alignment program that runs on commodity Graphics Processing Units (GPUs in common workstations. MUMmerGPU uses the new Compute Unified Device Architecture (CUDA from nVidia to align multiple query sequences against a single reference sequence stored as a suffix tree. By processing the queries in parallel on the highly parallel graphics card, MUMmerGPU achieves more than a 10-fold speedup over a serial CPU version of the sequence alignment kernel, and outperforms the exact alignment component of MUMmer on a high end CPU by 3.5-fold in total application time when aligning reads from recent sequencing projects using Solexa/Illumina, 454, and Sanger sequencing technologies. Conclusion MUMmerGPU is a low cost, ultra-fast sequence alignment program designed to handle the increasing volume of data produced by new, high-throughput sequencing technologies. MUMmerGPU demonstrates that even memory-intensive applications can run significantly faster on the relatively low-cost GPU than on the CPU.

A high-throughput multiplex method adapted for GMO detection.

Science.gov (United States)

Chaouachi, Maher; Chupeau, Gaëlle; Berard, Aurélie; McKhann, Heather; Romaniuk, Marcel; Giancola, Sandra; Laval, Valérie; Bertheau, Yves; Brunel, Dominique

2008-12-24

A high-throughput multiplex assay for the detection of genetically modified organisms (GMO) was developed on the basis of the existing SNPlex method designed for SNP genotyping. This SNPlex assay allows the simultaneous detection of up to 48 short DNA sequences (approximately 70 bp; "signature sequences") from taxa endogenous reference genes, from GMO constructions, screening targets, construct-specific, and event-specific targets, and finally from donor organisms. This assay avoids certain shortcomings of multiplex PCR-based methods already in widespread use for GMO detection. The assay demonstrated high specificity and sensitivity. The results suggest that this assay is reliable, flexible, and cost- and time-effective for high-throughput GMO detection.

Machine learning in computational biology to accelerate high-throughput protein expression.

Science.gov (United States)

Sastry, Anand; Monk, Jonathan; Tegel, Hanna; Uhlen, Mathias; Palsson, Bernhard O; Rockberg, Johan; Brunk, Elizabeth

2017-08-15

The Human Protein Atlas (HPA) enables the simultaneous characterization of thousands of proteins across various tissues to pinpoint their spatial location in the human body. This has been achieved through transcriptomics and high-throughput immunohistochemistry-based approaches, where over 40 000 unique human protein fragments have been expressed in E. coli. These datasets enable quantitative tracking of entire cellular proteomes and present new avenues for understanding molecular-level properties influencing expression and solubility. Combining computational biology and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template for analysis of further expression and solubility datasets. ebrunk@ucsd.edu or johanr@biotech.kth.se. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

High throughput electrospinning of high-quality nanofibers via an aluminum disk spinneret

Science.gov (United States)

Zheng, Guokuo

In this work, a simple and efficient needleless high throughput electrospinning process using an aluminum disk spinneret with 24 holes is described. Electrospun mats produced by this setup consisted of fine fibers (nano-sized) of the highest quality while the productivity (yield) was many times that obtained from conventional single-needle electrospinning. The goal was to produce scaled-up amounts of the same or better quality nanofibers under variable concentration, voltage, and the working distance than those produced with the single needle lab setting. The fiber mats produced were either polymer or ceramic (such as molybdenum trioxide nanofibers). Through experimentation the optimum process conditions were defined to be: 24 kilovolt, a distance to collector of 15cm. More diluted solutions resulted in smaller diameter fibers. Comparing the morphologies of the nanofibers of MoO3 produced by both the traditional and the high throughput set up it was found that they were very similar. Moreover, the nanofibers production rate is nearly 10 times than that of traditional needle electrospinning. Thus, the high throughput process has the potential to become an industrial nanomanufacturing process and the materials processed by it may be used as filtration devices, in tissue engineering, and as sensors.

High Throughput Neuro-Imaging Informatics

Directory of Open Access Journals (Sweden)

Michael I Miller

2013-12-01

Full Text Available This paper describes neuroinformatics technologies at 1 mm anatomical scale based on high throughput 3D functional and structural imaging technologies of the human brain. The core is an abstract pipeline for converting functional and structural imagery into their high dimensional neuroinformatic representations index containing O(E3-E4 discriminating dimensions. The pipeline is based on advanced image analysis coupled to digital knowledge representations in the form of dense atlases of the human brain at gross anatomical scale. We demonstrate the integration of these high-dimensional representations with machine learning methods, which have become the mainstay of other fields of science including genomics as well as social networks. Such high throughput facilities have the potential to alter the way medical images are stored and utilized in radiological workflows. The neuroinformatics pipeline is used to examine cross-sectional and personalized analyses of neuropsychiatric illnesses in clinical applications as well as longitudinal studies. We demonstrate the use of high throughput machine learning methods for supporting (i cross-sectional image analysis to evaluate the health status of individual subjects with respect to the population data, (ii integration of image and non-image information for diagnosis and prognosis.

High-throughput screening to identify inhibitors of lysine demethylases.

Science.gov (United States)

Gale, Molly; Yan, Qin

2015-01-01

Lysine demethylases (KDMs) are epigenetic regulators whose dysfunction is implicated in the pathology of many human diseases including various types of cancer, inflammation and X-linked intellectual disability. Particular demethylases have been identified as promising therapeutic targets, and tremendous efforts are being devoted toward developing suitable small-molecule inhibitors for clinical and research use. Several High-throughput screening strategies have been developed to screen for small-molecule inhibitors of KDMs, each with advantages and disadvantages in terms of time, cost, effort, reliability and sensitivity. In this Special Report, we review and evaluate the High-throughput screening methods utilized for discovery of novel small-molecule KDM inhibitors.

Solion ion source for high-efficiency, high-throughput solar cell manufacturing

Energy Technology Data Exchange (ETDEWEB)

Koo, John, E-mail: john-koo@amat.com; Binns, Brant; Miller, Timothy; Krause, Stephen; Skinner, Wesley; Mullin, James [Applied Materials, Inc., Varian Semiconductor Equipment Business Unit, 35 Dory Road, Gloucester, Massachusetts 01930 (United States)

2014-02-15

In this paper, we introduce the Solion ion source for high-throughput solar cell doping. As the source power is increased to enable higher throughput, negative effects degrade the lifetime of the plasma chamber and the extraction electrodes. In order to improve efficiency, we have explored a wide range of electron energies and determined the conditions which best suit production. To extend the lifetime of the source we have developed an in situ cleaning method using only existing hardware. With these combinations, source life-times of >200 h for phosphorous and >100 h for boron ion beams have been achieved while maintaining 1100 cell-per-hour production.

High throughput route selection in multi-rate wireless mesh networks

Institute of Scientific and Technical Information of China (English)

WEI Yi-fei; GUO Xiang-li; SONG Mei; SONG Jun-de

2008-01-01

Most existing Ad-hoc routing protocols use the shortest path algorithm with a hop count metric to select paths. It is appropriate in single-rate wireless networks, but has a tendency to select paths containing long-distance links that have low data rates and reduced reliability in multi-rate networks. This article introduces a high throughput routing algorithm utilizing the multi-rate capability and some mesh characteristics in wireless fidelity (WiFi) mesh networks. It uses the medium access control (MAC) transmission time as the routing metric, which is estimated by the information passed up from the physical layer. When the proposed algorithm is adopted, the Ad-hoc on-demand distance vector (AODV) routing can be improved as high throughput AODV (HT-AODV). Simulation results show that HT-AODV is capable of establishing a route that has high data-rate, short end-to-end delay and great network throughput.

Space Link Extension Protocol Emulation for High-Throughput, High-Latency Network Connections

Science.gov (United States)

Tchorowski, Nicole; Murawski, Robert

2014-01-01

New space missions require higher data rates and new protocols to meet these requirements. These high data rate space communication links push the limitations of not only the space communication links, but of the ground communication networks and protocols which forward user data to remote ground stations (GS) for transmission. The Consultative Committee for Space Data Systems, (CCSDS) Space Link Extension (SLE) standard protocol is one protocol that has been proposed for use by the NASA Space Network (SN) Ground Segment Sustainment (SGSS) program. New protocol implementations must be carefully tested to ensure that they provide the required functionality, especially because of the remote nature of spacecraft. The SLE protocol standard has been tested in the NASA Glenn Research Center's SCENIC Emulation Lab in order to observe its operation under realistic network delay conditions. More specifically, the delay between then NASA Integrated Services Network (NISN) and spacecraft has been emulated. The round trip time (RTT) delay for the continental NISN network has been shown to be up to 120ms; as such the SLE protocol was tested with network delays ranging from 0ms to 200ms. Both a base network condition and an SLE connection were tested with these RTT delays, and the reaction of both network tests to the delay conditions were recorded. Throughput for both of these links was set at 1.2Gbps. The results will show that, in the presence of realistic network delay, the SLE link throughput is significantly reduced while the base network throughput however remained at the 1.2Gbps specification. The decrease in SLE throughput has been attributed to the implementation's use of blocking calls. The decrease in throughput is not acceptable for high data rate links, as the link requires constant data a flow in order for spacecraft and ground radios to stay synchronized, unless significant data is queued a the ground station. In cases where queuing the data is not an option

High-resolution (noble) gas time series for aquatic research

Science.gov (United States)

Popp, A. L.; Brennwald, M. S.; Weber, U.; Kipfer, R.

2017-12-01

We developed a portable mass spectrometer (miniRUEDI) for on-site quantification of gas concentrations (He, Ar, Kr, N2, O2, CO2, CH4, etc.) in terrestrial gases [1,2]. Using the gas-equilibrium membrane-inlet technique (GE-MIMS), the miniRUEDI for the first time also allows accurate on-site and long-term dissolved-gas analysis in water bodies. The miniRUEDI is designed for operation in the field and at remote locations, using battery power and ambient air as a calibration gas. In contrast to conventional sampling and subsequent lab analysis, the miniRUEDI provides real-time and continuous time series of gas concentrations with a time resolution of a few seconds.Such high-resolution time series and immediate data availability open up new opportunities for research in highly dynamic and heterogeneous environmental systems. In addition the combined analysis of inert and reactive gas species provides direct information on the linkages of physical and biogoechemical processes, such as the air/water gas exchange, excess air formation, O2 turnover, or N2 production by denitrification [1,3,4].We present the miniRUEDI instrument and discuss its use for environmental research based on recent applications of tracking gas dynamics related to rapid and short-term processes in aquatic systems. [1] Brennwald, M.S., Schmidt, M., Oser, J., and Kipfer, R. (2016). Environmental Science and Technology, 50(24):13455-13463, doi: 10.1021/acs.est.6b03669[2] Gasometrix GmbH, gasometrix.com[3] Mächler, L., Peter, S., Brennwald, M.S., and Kipfer, R. (2013). Excess air formation as a mechanism for delivering oxygen to groundwater. Water Resources Research, doi:10.1002/wrcr.20547[4] Mächler, L., Brennwald, M.S., and Kipfer, R. (2013). Argon Concentration Time-Series As a Tool to Study Gas Dynamics in the Hyporheic Zone. Environmental Science and Technology, doi: 10.1021/es305309b

From Networks to Time Series

Science.gov (United States)

Shimada, Yutaka; Ikeguchi, Tohru; Shigehara, Takaomi

2012-10-01

In this Letter, we propose a framework to transform a complex network to a time series. The transformation from complex networks to time series is realized by the classical multidimensional scaling. Applying the transformation method to a model proposed by Watts and Strogatz [Nature (London) 393, 440 (1998)], we show that ring lattices are transformed to periodic time series, small-world networks to noisy periodic time series, and random networks to random time series. We also show that these relationships are analytically held by using the circulant-matrix theory and the perturbation theory of linear operators. The results are generalized to several high-dimensional lattices.

A novel high throughput assay for anthelmintic drug screening and resistance diagnosis by real-time monitoring of parasite motility.

Directory of Open Access Journals (Sweden)

Michael J Smout

Full Text Available BACKGROUND: Helminth parasites cause untold morbidity and mortality to billions of people and livestock. Anthelmintic drugs are available but resistance is a problem in livestock parasites, and is a looming threat for human helminths. Testing the efficacy of available anthelmintic drugs and development of new drugs is hindered by the lack of objective high-throughput screening methods. Currently, drug effect is assessed by observing motility or development of parasites using laborious, subjective, low-throughput methods. METHODOLOGY/PRINCIPAL FINDINGS: Here we describe a novel application for a real-time cell monitoring device (xCELLigence that can simply and objectively assess anthelmintic effects by measuring parasite motility in real time in a fully automated high-throughput fashion. We quantitatively assessed motility and determined real time IC(50 values of different anthelmintic drugs against several developmental stages of major helminth pathogens of humans and livestock, including larval Haemonchus contortus and Strongyloides ratti, and adult hookworms and blood flukes. The assay enabled quantification of the onset of egg hatching in real time, and the impact of drugs on hatch rate, as well as discriminating between the effects of drugs on motility of drug-susceptible and -resistant isolates of H. contortus. CONCLUSIONS/SIGNIFICANCE: Our findings indicate that this technique will be suitable for discovery and development of new anthelmintic drugs as well as for detection of phenotypic resistance to existing drugs for the majority of helminths and other pathogens where motility is a measure of pathogen viability. The method is also amenable to use for other purposes where motility is assessed, such as gene silencing or antibody-mediated killing.

High-throughput label-free detection of aggregate platelets with optofluidic time-stretch microscopy (Conference Presentation)

Science.gov (United States)

Jiang, Yiyue; Lei, Cheng; Yasumoto, Atsushi; Ito, Takuro; Guo, Baoshan; Kobayashi, Hirofumi; Ozeki, Yasuyuki; Yatomi, Yutaka; Goda, Keisuke

2017-02-01

According to WHO, approximately 10 million new cases of thrombotic disorders are diagnosed worldwide every year. In the U.S. and Europe, their related diseases kill more people than those from AIDS, prostate cancer, breast cancer and motor vehicle accidents combined. Although thrombotic disorders, especially arterial ones, mainly result from enhanced platelet aggregability in the vascular system, visual detection of platelet aggregates in vivo is not employed in clinical settings. Here we present a high-throughput label-free platelet aggregate detection method, aiming at the diagnosis and monitoring of thrombotic disorders in clinical settings. With optofluidic time-stretch microscopy with a spatial resolution of 780 nm and an ultrahigh linear scanning rate of 75 MHz, it is capable of detecting aggregated platelets in lysed blood which flows through a hydrodynamic-focusing microfluidic device at a high throughput of 10,000 particles/s. With digital image processing and statistical analysis, we are able to distinguish them from single platelets and other blood cells via morphological features. The detection results are compared with results of fluorescence-based detection (which is slow and inaccurate, but established). Our results indicate that the method holds promise for real-time, low-cost, label-free, and minimally invasive detection of platelet aggregates, which is potentially applicable to detection of platelet aggregates in vivo and to the diagnosis and monitoring of thrombotic disorders in clinical settings. This technique, if introduced clinically, may provide important clinical information in addition to that obtained by conventional techniques for thrombotic disorder diagnosis, including ex vivo platelet aggregation tests.

Integrating external biological knowledge in the construction of regulatory networks from time-series expression data

Directory of Open Access Journals (Sweden)

Lo Kenneth

2012-08-01

Full Text Available Abstract Background Inference about regulatory networks from high-throughput genomics data is of great interest in systems biology. We present a Bayesian approach to infer gene regulatory networks from time series expression data by integrating various types of biological knowledge. Results We formulate network construction as a series of variable selection problems and use linear regression to model the data. Our method summarizes additional data sources with an informative prior probability distribution over candidate regression models. We extend the Bayesian model averaging (BMA variable selection method to select regulators in the regression framework. We summarize the external biological knowledge by an informative prior probability distribution over the candidate regression models. Conclusions We demonstrate our method on simulated data and a set of time-series microarray experiments measuring the effect of a drug perturbation on gene expression levels, and show that it outperforms leading regression-based methods in the literature.

International Work-Conference on Time Series

CERN Document Server

Pomares, Héctor; Valenzuela, Olga

2017-01-01

This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series. The contributions were originally presented at the International Work-Conference on Time Series, ITISE 2016, held in Granada, Spain, June 27-29, 2016. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting.  It focuses on interdisciplinary and multidisciplinary rese arch encompassing the disciplines of comput...

High-throughput transformation of Saccharomyces cerevisiae using liquid handling robots.

Directory of Open Access Journals (Sweden)

Guangbo Liu

Full Text Available Saccharomyces cerevisiae (budding yeast is a powerful eukaryotic model organism ideally suited to high-throughput genetic analyses, which time and again has yielded insights that further our understanding of cell biology processes conserved in humans. Lithium Acetate (LiAc transformation of yeast with DNA for the purposes of exogenous protein expression (e.g., plasmids or genome mutation (e.g., gene mutation, deletion, epitope tagging is a useful and long established method. However, a reliable and optimized high throughput transformation protocol that runs almost no risk of human error has not been described in the literature. Here, we describe such a method that is broadly transferable to most liquid handling high-throughput robotic platforms, which are now commonplace in academic and industry settings. Using our optimized method, we are able to comfortably transform approximately 1200 individual strains per day, allowing complete transformation of typical genomic yeast libraries within 6 days. In addition, use of our protocol for gene knockout purposes also provides a potentially quicker, easier and more cost-effective approach to generating collections of double mutants than the popular and elegant synthetic genetic array methodology. In summary, our methodology will be of significant use to anyone interested in high throughput molecular and/or genetic analysis of yeast.

a novel two – factor high order fuzzy time series with applications to ...

African Journals Online (AJOL)

HOD

objectively with multiple – factor fuzzy time series, recurrent number of fuzzy relationships, and assigning weights to elements of fuzzy forecasting rules. In this paper, a novel two – factor high – order fuzzy time series forecasting method based on fuzzy C-means clustering and particle swarm optimization is proposed to ...

factor high order fuzzy time series with applications to temperature

African Journals Online (AJOL)

HOD

In this paper, a novel two – factor high – order fuzzy time series forecasting method based on .... to balance between local and global exploitations of the swarms. While, .... Although, there were a number of outliers but, the spread at the spot in ...

High Throughput Transcriptomics @ USEPA (Toxicology ...

Science.gov (United States)

The ideal chemical testing approach will provide complete coverage of all relevant toxicological responses. It should be sensitive and specific It should identify the mechanism/mode-of-action (with dose-dependence). It should identify responses relevant to the species of interest. Responses should ideally be translated into tissue-, organ-, and organism-level effects. It must be economical and scalable. Using a High Throughput Transcriptomics platform within US EPA provides broader coverage of biological activity space and toxicological MOAs and helps fill the toxicological data gap. Slide presentation at the 2016 ToxForum on using High Throughput Transcriptomics at US EPA for broader coverage biological activity space and toxicological MOAs.

Application of ToxCast High-Throughput Screening and ...

Science.gov (United States)

Slide presentation at the SETAC annual meeting on High-Throughput Screening and Modeling Approaches to Identify Steroidogenesis Distruptors Slide presentation at the SETAC annual meeting on High-Throughput Screening and Modeling Approaches to Identify Steroidogenssis Distruptors

High-throughput full-automatic synchrotron-based tomographic microscopy

International Nuclear Information System (INIS)

Mader, Kevin; Marone, Federica; Hintermueller, Christoph; Mikuljan, Gordan; Isenegger, Andreas; Stampanoni, Marco

2011-01-01

At the TOMCAT (TOmographic Microscopy and Coherent rAdiology experimenTs) beamline of the Swiss Light Source with an energy range of 8-45 keV and voxel size from 0.37 (micro)m to 7.4 (micro)m, full tomographic datasets are typically acquired in 5 to 10 min. To exploit the speed of the system and enable high-throughput studies to be performed in a fully automatic manner, a package of automation tools has been developed. The samples are automatically exchanged, aligned, moved to the correct region of interest, and scanned. This task is accomplished through the coordination of Python scripts, a robot-based sample-exchange system, sample positioning motors and a CCD camera. The tools are suited for any samples that can be mounted on a standard SEM stub, and require no specific environmental conditions. Up to 60 samples can be analyzed at a time without user intervention. The throughput of the system is dependent on resolution, energy and sample size, but rates of four samples per hour have been achieved with 0.74 (micro)m voxel size at 17.5 keV. The maximum intervention-free scanning time is theoretically unlimited, and in practice experiments have been running unattended as long as 53 h (the average beam time allocation at TOMCAT is 48 h per user). The system is the first fully automated high-throughput tomography station: mounting samples, finding regions of interest, scanning and reconstructing can be performed without user intervention. The system also includes many features which accelerate and simplify the process of tomographic microscopy.

High throughput nanoimprint lithography for semiconductor memory applications

Science.gov (United States)

Ye, Zhengmao; Zhang, Wei; Khusnatdinov, Niyaz; Stachowiak, Tim; Irving, J. W.; Longsine, Whitney; Traub, Matthew; Fletcher, Brian; Liu, Weijun

2017-03-01

Imprint lithography is a promising technology for replication of nano-scale features. For semiconductor device applications, Canon deposits a low viscosity resist on a field by field basis using jetting technology. A patterned mask is lowered into the resist fluid which then quickly flows into the relief patterns in the mask by capillary action. Following this filling step, the resist is crosslinked under UV radiation, and then the mask is removed, leaving a patterned resist on the substrate. There are two critical components to meeting throughput requirements for imprint lithography. Using a similar approach to what is already done for many deposition and etch processes, imprint stations can be clustered to enhance throughput. The FPA-1200NZ2C is a four station cluster system designed for high volume manufacturing. For a single station, throughput includes overhead, resist dispense, resist fill time (or spread time), exposure and separation. Resist exposure time and mask/wafer separation are well understood processing steps with typical durations on the order of 0.10 to 0.20 seconds. To achieve a total process throughput of 17 wafers per hour (wph) for a single station, it is necessary to complete the fluid fill step in 1.2 seconds. For a throughput of 20 wph, fill time must be reduced to only one 1.1 seconds. There are several parameters that can impact resist filling. Key parameters include resist drop volume (smaller is better), system controls (which address drop spreading after jetting), Design for Imprint or DFI (to accelerate drop spreading) and material engineering (to promote wetting between the resist and underlying adhesion layer). In addition, it is mandatory to maintain fast filling, even for edge field imprinting. In this paper, we address the improvements made in all of these parameters to first enable a 1.20 second filling process for a device like pattern and have demonstrated this capability for both full fields and edge fields. Non

Online Self-Organizing Network Control with Time Averaged Weighted Throughput Objective

Directory of Open Access Journals (Sweden)

Zhicong Zhang

2018-01-01

Full Text Available We study an online multisource multisink queueing network control problem characterized with self-organizing network structure and self-organizing job routing. We decompose the self-organizing queueing network control problem into a series of interrelated Markov Decision Processes and construct a control decision model for them based on the coupled reinforcement learning (RL architecture. To maximize the mean time averaged weighted throughput of the jobs through the network, we propose a reinforcement learning algorithm with time averaged reward to deal with the control decision model and obtain a control policy integrating the jobs routing selection strategy and the jobs sequencing strategy. Computational experiments verify the learning ability and the effectiveness of the proposed reinforcement learning algorithm applied in the investigated self-organizing network control problem.

Towards low-delay and high-throughput cognitive radio vehicular networks

Directory of Open Access Journals (Sweden)

Nada Elgaml

2017-12-01

Full Text Available Cognitive Radio Vehicular Ad-hoc Networks (CR-VANETs exploit cognitive radios to allow vehicles to access the unused channels in their radio environment. Thus, CR-VANETs do not only suffer the traditional CR problems, especially spectrum sensing, but also suffer new challenges due to the highly dynamic nature of VANETs. In this paper, we present a low-delay and high-throughput radio environment assessment scheme for CR-VANETs that can be easily incorporated with the IEEE 802.11p standard developed for VANETs. Simulation results show that the proposed scheme significantly reduces the time to get the radio environment map and increases the CR-VANET throughput.

IoT for Real-Time Measurement of High-Throughput Liquid Dispensing in Laboratory Environments.

Science.gov (United States)

Shumate, Justin; Baillargeon, Pierre; Spicer, Timothy P; Scampavia, Louis

2018-04-01

Critical to maintaining quality control in high-throughput screening is the need for constant monitoring of liquid-dispensing fidelity. Traditional methods involve operator intervention with gravimetric analysis to monitor the gross accuracy of full plate dispenses, visual verification of contents, or dedicated weigh stations on screening platforms that introduce potential bottlenecks and increase the plate-processing cycle time. We present a unique solution using open-source hardware, software, and 3D printing to automate dispenser accuracy determination by providing real-time dispense weight measurements via a network-connected precision balance. This system uses an Arduino microcontroller to connect a precision balance to a local network. By integrating the precision balance as an Internet of Things (IoT) device, it gains the ability to provide real-time gravimetric summaries of dispensing, generate timely alerts when problems are detected, and capture historical dispensing data for future analysis. All collected data can then be accessed via a web interface for reviewing alerts and dispensing information in real time or remotely for timely intervention of dispense errors. The development of this system also leveraged 3D printing to rapidly prototype sensor brackets, mounting solutions, and component enclosures.

International Work-Conference on Time Series

CERN Document Server

Pomares, Héctor

2016-01-01

This volume presents selected peer-reviewed contributions from The International Work-Conference on Time Series, ITISE 2015, held in Granada, Spain, July 1-3, 2015. It discusses topics in time series analysis and forecasting, advanced methods and online learning in time series, high-dimensional and complex/big data time series as well as forecasting in real problems. The International Work-Conferences on Time Series (ITISE) provide a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing the disciplines of computer science, mathematics, statistics and econometrics.

High-throughput single nucleotide polymorphism genotyping using nanofluidic Dynamic Arrays

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Crenshaw Andrew

2009-01-01

Full Text Available Abstract Background Single nucleotide polymorphisms (SNPs have emerged as the genetic marker of choice for mapping disease loci and candidate gene association studies, because of their high density and relatively even distribution in the human genomes. There is a need for systems allowing medium multiplexing (ten to hundreds of SNPs with high throughput, which can efficiently and cost-effectively generate genotypes for a very large sample set (thousands of individuals. Methods that are flexible, fast, accurate and cost-effective are urgently needed. This is also important for those who work on high throughput genotyping in non-model systems where off-the-shelf assays are not available and a flexible platform is needed. Results We demonstrate the use of a nanofluidic Integrated Fluidic Circuit (IFC - based genotyping system for medium-throughput multiplexing known as the Dynamic Array, by genotyping 994 individual human DNA samples on 47 different SNP assays, using nanoliter volumes of reagents. Call rates of greater than 99.5% and call accuracies of greater than 99.8% were achieved from our study, which demonstrates that this is a formidable genotyping platform. The experimental set up is very simple, with a time-to-result for each sample of about 3 hours. Conclusion Our results demonstrate that the Dynamic Array is an excellent genotyping system for medium-throughput multiplexing (30-300 SNPs, which is simple to use and combines rapid throughput with excellent call rates, high concordance and low cost. The exceptional call rates and call accuracy obtained may be of particular interest to those working on validation and replication of genome- wide- association (GWA studies.

High Throughput PBTK: Open-Source Data and Tools for ...

Science.gov (United States)

Presentation on High Throughput PBTK at the PBK Modelling in Risk Assessment meeting in Ispra, Italy Presentation on High Throughput PBTK at the PBK Modelling in Risk Assessment meeting in Ispra, Italy

High-Throughput Screening and Hit Validation of Extracellular-Related Kinase 5 (ERK5) Inhibitors.

Science.gov (United States)

Myers, Stephanie M; Bawn, Ruth H; Bisset, Louise C; Blackburn, Timothy J; Cottyn, Betty; Molyneux, Lauren; Wong, Ai-Ching; Cano, Celine; Clegg, William; Harrington, Ross W; Leung, Hing; Rigoreau, Laurent; Vidot, Sandrine; Golding, Bernard T; Griffin, Roger J; Hammonds, Tim; Newell, David R; Hardcastle, Ian R

2016-08-08

The extracellular-related kinase 5 (ERK5) is a promising target for cancer therapy. A high-throughput screen was developed for ERK5, based on the IMAP FP progressive binding system, and used to identify hits from a library of 57 617 compounds. Four distinct chemical series were evident within the screening hits. Resynthesis and reassay of the hits demonstrated that one series did not return active compounds, whereas three series returned active hits. Structure-activity studies demonstrated that the 4-benzoylpyrrole-2-carboxamide pharmacophore had excellent potential for further development. The minimum kinase binding pharmacophore was identified, and key examples demonstrated good selectivity for ERK5 over p38α kinase.

High throughput 16S rRNA gene amplicon sequencing

DEFF Research Database (Denmark)

Nierychlo, Marta; Larsen, Poul; Jørgensen, Mads Koustrup

S rRNA gene amplicon sequencing has been developed over the past few years and is now ready to use for more comprehensive studies related to plant operation and optimization thanks to short analysis time, low cost, high throughput, and high taxonomic resolution. In this study we show how 16S r......RNA gene amplicon sequencing can be used to reveal factors of importance for the operation of full-scale nutrient removal plants related to settling problems and floc properties. Using optimized DNA extraction protocols, indexed primers and our in-house Illumina platform, we prepared multiple samples...... be correlated to the presence of the species that are regarded as “strong” and “weak” floc formers. In conclusion, 16S rRNA gene amplicon sequencing provides a high throughput approach for a rapid and cheap community profiling of activated sludge that in combination with multivariate statistics can be used...

High throughput screening method for assessing heterogeneity of microorganisms

NARCIS (Netherlands)

Ingham, C.J.; Sprenkels, A.J.; van Hylckama Vlieg, J.E.T.; Bomer, Johan G.; de Vos, W.M.; van den Berg, Albert

2006-01-01

The invention relates to the field of microbiology. Provided is a method which is particularly powerful for High Throughput Screening (HTS) purposes. More specific a high throughput method for determining heterogeneity or interactions of microorganisms is provided.

High throughput diffractive multi-beam femtosecond laser processing using a spatial light modulator

Energy Technology Data Exchange (ETDEWEB)

Kuang Zheng [Laser Group, Department of Engineering, University of Liverpool Brownlow Street, Liverpool L69 3GQ (United Kingdom)], E-mail: z.kuang@liv.ac.uk; Perrie, Walter [Laser Group, Department of Engineering, University of Liverpool Brownlow Street, Liverpool L69 3GQ (United Kingdom); Leach, Jonathan [Department of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Sharp, Martin; Edwardson, Stuart P. [Laser Group, Department of Engineering, University of Liverpool Brownlow Street, Liverpool L69 3GQ (United Kingdom); Padgett, Miles [Department of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Dearden, Geoff; Watkins, Ken G. [Laser Group, Department of Engineering, University of Liverpool Brownlow Street, Liverpool L69 3GQ (United Kingdom)

2008-12-30

High throughput femtosecond laser processing is demonstrated by creating multiple beams using a spatial light modulator (SLM). The diffractive multi-beam patterns are modulated in real time by computer generated holograms (CGHs), which can be calculated by appropriate algorithms. An interactive LabVIEW program is adopted to generate the relevant CGHs. Optical efficiency at this stage is shown to be {approx}50% into first order beams and real time processing has been carried out at 50 Hz refresh rate. Results obtained demonstrate high precision surface micro-structuring on silicon and Ti6Al4V with throughput gain >1 order of magnitude.

High throughput on-chip analysis of high-energy charged particle tracks using lensfree imaging

Energy Technology Data Exchange (ETDEWEB)

Luo, Wei; Shabbir, Faizan; Gong, Chao; Gulec, Cagatay; Pigeon, Jeremy; Shaw, Jessica; Greenbaum, Alon; Tochitsky, Sergei; Joshi, Chandrashekhar [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States); Ozcan, Aydogan, E-mail: ozcan@ucla.edu [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States); Bioengineering Department, University of California, Los Angeles, California 90095 (United States); California NanoSystems Institute (CNSI), University of California, Los Angeles, California 90095 (United States)

2015-04-13

We demonstrate a high-throughput charged particle analysis platform, which is based on lensfree on-chip microscopy for rapid ion track analysis using allyl diglycol carbonate, i.e., CR-39 plastic polymer as the sensing medium. By adopting a wide-area opto-electronic image sensor together with a source-shifting based pixel super-resolution technique, a large CR-39 sample volume (i.e., 4 cm × 4 cm × 0.1 cm) can be imaged in less than 1 min using a compact lensfree on-chip microscope, which detects partially coherent in-line holograms of the ion tracks recorded within the CR-39 detector. After the image capture, using highly parallelized reconstruction and ion track analysis algorithms running on graphics processing units, we reconstruct and analyze the entire volume of a CR-39 detector within ∼1.5 min. This significant reduction in the entire imaging and ion track analysis time not only increases our throughput but also allows us to perform time-resolved analysis of the etching process to monitor and optimize the growth of ion tracks during etching. This computational lensfree imaging platform can provide a much higher throughput and more cost-effective alternative to traditional lens-based scanning optical microscopes for ion track analysis using CR-39 and other passive high energy particle detectors.

High throughput electrophysiology: new perspectives for ion channel drug discovery

DEFF Research Database (Denmark)

Willumsen, Niels J; Bech, Morten; Olesen, Søren-Peter

2003-01-01

Proper function of ion channels is crucial for all living cells. Ion channel dysfunction may lead to a number of diseases, so-called channelopathies, and a number of common diseases, including epilepsy, arrhythmia, and type II diabetes, are primarily treated by drugs that modulate ion channels....... A cornerstone in current drug discovery is high throughput screening assays which allow examination of the activity of specific ion channels though only to a limited extent. Conventional patch clamp remains the sole technique with sufficiently high time resolution and sensitivity required for precise and direct...... characterization of ion channel properties. However, patch clamp is a slow, labor-intensive, and thus expensive, technique. New techniques combining the reliability and high information content of patch clamping with the virtues of high throughput philosophy are emerging and predicted to make a number of ion...

Time Series in Education: The Analysis of Daily Attendance in Two High Schools

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Koopmans, Matthijs

2011-01-01

This presentation discusses the use of a time series approach to the analysis of daily attendance in two urban high schools over the course of one school year (2009-10). After establishing that the series for both schools were stationary, they were examined for moving average processes, autoregression, seasonal dependencies (weekly cycles),…

Forecasting and analyzing high O3 time series in educational area through an improved chaotic approach

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Hamid, Nor Zila Abd; Adenan, Nur Hamiza; Noorani, Mohd Salmi Md

2017-08-01

Forecasting and analyzing the ozone (O3) concentration time series is important because the pollutant is harmful to health. This study is a pilot study for forecasting and analyzing the O3 time series in one of Malaysian educational area namely Shah Alam using chaotic approach. Through this approach, the observed hourly scalar time series is reconstructed into a multi-dimensional phase space, which is then used to forecast the future time series through the local linear approximation method. The main purpose is to forecast the high O3 concentrations. The original method performed poorly but the improved method addressed the weakness thereby enabling the high concentrations to be successfully forecast. The correlation coefficient between the observed and forecasted time series through the improved method is 0.9159 and both the mean absolute error and root mean squared error are low. Thus, the improved method is advantageous. The time series analysis by means of the phase space plot and Cao method identified the presence of low-dimensional chaotic dynamics in the observed O3 time series. Results showed that at least seven factors affect the studied O3 time series, which is consistent with the listed factors from the diurnal variations investigation and the sensitivity analysis from past studies. In conclusion, chaotic approach has been successfully forecast and analyzes the O3 time series in educational area of Shah Alam. These findings are expected to help stakeholders such as Ministry of Education and Department of Environment in having a better air pollution management.

High throughput detection of Coxiella burnetii by real-time PCR with internal control system and automated DNA preparation

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Kramme Stefanie

2008-05-01

Full Text Available Abstract Background Coxiella burnetii is the causative agent of Q-fever, a widespread zoonosis. Due to its high environmental stability and infectivity it is regarded as a category B biological weapon agent. In domestic animals infection remains either asymptomatic or presents as infertility or abortion. Clinical presentation in humans can range from mild flu-like illness to acute pneumonia and hepatitis. Endocarditis represents the most common form of chronic Q-fever. In humans serology is the gold standard for diagnosis but is inadequate for early case detection. In order to serve as a diagnostic tool in an eventual biological weapon attack or in local epidemics we developed a real-time 5'nuclease based PCR assay with an internal control system. To facilitate high-throughput an automated extraction procedure was evaluated. Results To determine the minimum number of copies that are detectable at 95% chance probit analysis was used. Limit of detection in blood was 2,881 copies/ml [95%CI, 2,188–4,745 copies/ml] with a manual extraction procedure and 4,235 copies/ml [95%CI, 3,143–7,428 copies/ml] with a fully automated extraction procedure, respectively. To demonstrate clinical application a total of 72 specimens of animal origin were compared with respect to manual and automated extraction. A strong correlation between both methods was observed rendering both methods suitable. Testing of 247 follow up specimens of animal origin from a local Q-fever epidemic rendered real-time PCR more sensitive than conventional PCR. Conclusion A sensitive and thoroughly evaluated real-time PCR was established. Its high-throughput mode may show a useful approach to rapidly screen samples in local outbreaks for other organisms relevant for humans or animals. Compared to a conventional PCR assay sensitivity of real-time PCR was higher after testing samples from a local Q-fever outbreak.

Extracting Fluorescent Reporter Time Courses of Cell Lineages from High-Throughput Microscopy at Low Temporal Resolution

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Downey, Mike J.; Jeziorska, Danuta M.; Ott, Sascha; Tamai, T. Katherine; Koentges, Georgy; Vance, Keith W.; Bretschneider, Till

2011-01-01

The extraction of fluorescence time course data is a major bottleneck in high-throughput live-cell microscopy. Here we present an extendible framework based on the open-source image analysis software ImageJ, which aims in particular at analyzing the expression of fluorescent reporters through cell divisions. The ability to track individual cell lineages is essential for the analysis of gene regulatory factors involved in the control of cell fate and identity decisions. In our approach, cell nuclei are identified using Hoechst, and a characteristic drop in Hoechst fluorescence helps to detect dividing cells. We first compare the efficiency and accuracy of different segmentation methods and then present a statistical scoring algorithm for cell tracking, which draws on the combination of various features, such as nuclear intensity, area or shape, and importantly, dynamic changes thereof. Principal component analysis is used to determine the most significant features, and a global parameter search is performed to determine the weighting of individual features. Our algorithm has been optimized to cope with large cell movements, and we were able to semi-automatically extract cell trajectories across three cell generations. Based on the MTrackJ plugin for ImageJ, we have developed tools to efficiently validate tracks and manually correct them by connecting broken trajectories and reassigning falsely connected cell positions. A gold standard consisting of two time-series with 15,000 validated positions will be released as a valuable resource for benchmarking. We demonstrate how our method can be applied to analyze fluorescence distributions generated from mouse stem cells transfected with reporter constructs containing transcriptional control elements of the Msx1 gene, a regulator of pluripotency, in mother and daughter cells. Furthermore, we show by tracking zebrafish PAC2 cells expressing FUCCI cell cycle markers, our framework can be easily adapted to different cell

Extracting fluorescent reporter time courses of cell lineages from high-throughput microscopy at low temporal resolution.

Directory of Open Access Journals (Sweden)

Mike J Downey

Full Text Available The extraction of fluorescence time course data is a major bottleneck in high-throughput live-cell microscopy. Here we present an extendible framework based on the open-source image analysis software ImageJ, which aims in particular at analyzing the expression of fluorescent reporters through cell divisions. The ability to track individual cell lineages is essential for the analysis of gene regulatory factors involved in the control of cell fate and identity decisions. In our approach, cell nuclei are identified using Hoechst, and a characteristic drop in Hoechst fluorescence helps to detect dividing cells. We first compare the efficiency and accuracy of different segmentation methods and then present a statistical scoring algorithm for cell tracking, which draws on the combination of various features, such as nuclear intensity, area or shape, and importantly, dynamic changes thereof. Principal component analysis is used to determine the most significant features, and a global parameter search is performed to determine the weighting of individual features. Our algorithm has been optimized to cope with large cell movements, and we were able to semi-automatically extract cell trajectories across three cell generations. Based on the MTrackJ plugin for ImageJ, we have developed tools to efficiently validate tracks and manually correct them by connecting broken trajectories and reassigning falsely connected cell positions. A gold standard consisting of two time-series with 15,000 validated positions will be released as a valuable resource for benchmarking. We demonstrate how our method can be applied to analyze fluorescence distributions generated from mouse stem cells transfected with reporter constructs containing transcriptional control elements of the Msx1 gene, a regulator of pluripotency, in mother and daughter cells. Furthermore, we show by tracking zebrafish PAC2 cells expressing FUCCI cell cycle markers, our framework can be easily adapted

High Throughput Determinations of Critical Dosing Parameters (IVIVE workshop)

Science.gov (United States)

High throughput toxicokinetics (HTTK) is an approach that allows for rapid estimations of TK for hundreds of environmental chemicals. HTTK-based reverse dosimetry (i.e, reverse toxicokinetics or RTK) is used in order to convert high throughput in vitro toxicity screening (HTS) da...

High-Throughput Quantification of Bacterial-Cell Interactions Using Virtual Colony Counts

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Stefanie Hoffmann

2018-02-01

Full Text Available The quantification of bacteria in cell culture infection models is of paramount importance for the characterization of host-pathogen interactions and pathogenicity factors involved. The standard to enumerate bacteria in these assays is plating of a dilution series on solid agar and counting of the resulting colony forming units (CFU. In contrast, the virtual colony count (VCC method is a high-throughput compatible alternative with minimized manual input. Based on the recording of quantitative growth kinetics, VCC relates the time to reach a given absorbance threshold to the initial cell count using a series of calibration curves. Here, we adapted the VCC method using the model organism Salmonella enterica sv. Typhimurium (S. Typhimurium in combination with established cell culture-based infection models. For HeLa infections, a direct side-by-side comparison showed a good correlation of VCC with CFU counting after plating. For MDCK cells and RAW macrophages we found that VCC reproduced the expected phenotypes of different S. Typhimurium mutants. Furthermore, we demonstrated the use of VCC to test the inhibition of Salmonella invasion by the probiotic E. coli strain Nissle 1917. Taken together, VCC provides a flexible, label-free, automation-compatible methodology to quantify bacteria in in vitro infection assays.

GlycoExtractor: a web-based interface for high throughput processing of HPLC-glycan data.

Science.gov (United States)

Artemenko, Natalia V; Campbell, Matthew P; Rudd, Pauline M

2010-04-05

Recently, an automated high-throughput HPLC platform has been developed that can be used to fully sequence and quantify low concentrations of N-linked sugars released from glycoproteins, supported by an experimental database (GlycoBase) and analytical tools (autoGU). However, commercial packages that support the operation of HPLC instruments and data storage lack platforms for the extraction of large volumes of data. The lack of resources and agreed formats in glycomics is now a major limiting factor that restricts the development of bioinformatic tools and automated workflows for high-throughput HPLC data analysis. GlycoExtractor is a web-based tool that interfaces with a commercial HPLC database/software solution to facilitate the extraction of large volumes of processed glycan profile data (peak number, peak areas, and glucose unit values). The tool allows the user to export a series of sample sets to a set of file formats (XML, JSON, and CSV) rather than a collection of disconnected files. This approach not only reduces the amount of manual refinement required to export data into a suitable format for data analysis but also opens the field to new approaches for high-throughput data interpretation and storage, including biomarker discovery and validation and monitoring of online bioprocessing conditions for next generation biotherapeutics.

High-throughput Sequencing Based Immune Repertoire Study during Infectious Disease

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Dongni Hou

2016-08-01

Full Text Available The selectivity of the adaptive immune response is based on the enormous diversity of T and B cell antigen-specific receptors. The immune repertoire, the collection of T and B cells with functional diversity in the circulatory system at any given time, is dynamic and reflects the essence of immune selectivity. In this article, we review the recent advances in immune repertoire study of infectious diseases that achieved by traditional techniques and high-throughput sequencing techniques. High-throughput sequencing techniques enable the determination of complementary regions of lymphocyte receptors with unprecedented efficiency and scale. This progress in methodology enhances the understanding of immunologic changes during pathogen challenge, and also provides a basis for further development of novel diagnostic markers, immunotherapies and vaccines.

Quality control methodology for high-throughput protein-protein interaction screening.

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Vazquez, Alexei; Rual, Jean-François; Venkatesan, Kavitha

2011-01-01

Protein-protein interactions are key to many aspects of the cell, including its cytoskeletal structure, the signaling processes in which it is involved, or its metabolism. Failure to form protein complexes or signaling cascades may sometimes translate into pathologic conditions such as cancer or neurodegenerative diseases. The set of all protein interactions between the proteins encoded by an organism constitutes its protein interaction network, representing a scaffold for biological function. Knowing the protein interaction network of an organism, combined with other sources of biological information, can unravel fundamental biological circuits and may help better understand the molecular basics of human diseases. The protein interaction network of an organism can be mapped by combining data obtained from both low-throughput screens, i.e., "one gene at a time" experiments and high-throughput screens, i.e., screens designed to interrogate large sets of proteins at once. In either case, quality controls are required to deal with the inherent imperfect nature of experimental assays. In this chapter, we discuss experimental and statistical methodologies to quantify error rates in high-throughput protein-protein interactions screens.

Time of flight secondary ion mass spectrometry: A powerful high throughput screening tool

International Nuclear Information System (INIS)

Smentkowski, Vincent S.; Ostrowski, Sara G.

2007-01-01

Combinatorial materials libraries are becoming more complicated; successful screening of these libraries requires the development of new high throughput screening methodologies. Time of flight secondary ion mass spectrometry (ToF-SIMS) is a surface analytical technique that is able to detect and image all elements (including hydrogen which is problematic for many other analysis instruments) and molecular fragments, with high mass resolution, during a single measurement. Commercial ToF-SIMS instruments can image 500 μm areas by rastering the primary ion beam over the region of interest. In this work, we will show that large area analysis can be performed, in one single measurement, by rastering the sample under the ion beam. We show that an entire 70 mm diameter wafer can be imaged in less than 90 min using ToF-SIMS stage (macro)rastering techniques. ToF-SIMS data sets contain a wealth of information since an entire high mass resolution mass spectrum is saved at each pixel in an ion image. Multivariate statistical analysis (MVSA) tools are being used in the ToF-SIMS community to assist with data interpretation; we will demonstrate that MVSA tools provide details that were not obtained using manual (univariate) analysis

High-Throughput Analysis of Enzyme Activities

Energy Technology Data Exchange (ETDEWEB)

Lu, Guoxin [Iowa State Univ., Ames, IA (United States)

2007-01-01

High-throughput screening (HTS) techniques have been applied to many research fields nowadays. Robot microarray printing technique and automation microtiter handling technique allows HTS performing in both heterogeneous and homogeneous formats, with minimal sample required for each assay element. In this dissertation, new HTS techniques for enzyme activity analysis were developed. First, patterns of immobilized enzyme on nylon screen were detected by multiplexed capillary system. The imaging resolution is limited by the outer diameter of the capillaries. In order to get finer images, capillaries with smaller outer diameters can be used to form the imaging probe. Application of capillary electrophoresis allows separation of the product from the substrate in the reaction mixture, so that the product doesn't have to have different optical properties with the substrate. UV absorption detection allows almost universal detection for organic molecules. Thus, no modifications of either the substrate or the product molecules are necessary. This technique has the potential to be used in screening of local distribution variations of specific bio-molecules in a tissue or in screening of multiple immobilized catalysts. Another high-throughput screening technique is developed by directly monitoring the light intensity of the immobilized-catalyst surface using a scientific charge-coupled device (CCD). Briefly, the surface of enzyme microarray is focused onto a scientific CCD using an objective lens. By carefully choosing the detection wavelength, generation of product on an enzyme spot can be seen by the CCD. Analyzing the light intensity change over time on an enzyme spot can give information of reaction rate. The same microarray can be used for many times. Thus, high-throughput kinetic studies of hundreds of catalytic reactions are made possible. At last, we studied the fluorescence emission spectra of ADP and obtained the detection limits for ADP under three different

A time-series method for automated measurement of changes in mitotic and interphase duration from time-lapse movies.

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Frederic D Sigoillot

Full Text Available Automated time-lapse microscopy can visualize proliferation of large numbers of individual cells, enabling accurate measurement of the frequency of cell division and the duration of interphase and mitosis. However, extraction of quantitative information by manual inspection of time-lapse movies is too time-consuming to be useful for analysis of large experiments.Here we present an automated time-series approach that can measure changes in the duration of mitosis and interphase in individual cells expressing fluorescent histone 2B. The approach requires analysis of only 2 features, nuclear area and average intensity. Compared to supervised learning approaches, this method reduces processing time and does not require generation of training data sets. We demonstrate that this method is as sensitive as manual analysis in identifying small changes in interphase or mitotic duration induced by drug or siRNA treatment.This approach should facilitate automated analysis of high-throughput time-lapse data sets to identify small molecules or gene products that influence timing of cell division.

High-throughput screening with micro-x-ray fluorescence

International Nuclear Information System (INIS)

Havrilla, George J.; Miller, Thomasin C.

2005-01-01

Micro-x-ray fluorescence (MXRF) is a useful characterization tool for high-throughput screening of combinatorial libraries. Due to the increasing threat of use of chemical warfare (CW) agents both in military actions and against civilians by terrorist extremists, there is a strong push to improve existing methods and develop means for the detection of a broad spectrum of CW agents in a minimal amount of time to increase national security. This paper describes a combinatorial high-throughput screening technique for CW receptor discovery to aid in sensor development. MXRF can screen materials for elemental composition at the mesoscale level (tens to hundreds of micrometers). The key aspect of this work is the use of commercial MXRF instrumentation coupled with the inherent heteroatom elements within the target molecules of the combinatorial reaction to provide rapid and specific identification of lead species. The method is demonstrated by screening an 11-mer oligopeptide library for selective binding of the degradation products of the nerve agent VX. The identified oligopeptides can be used as selective molecular receptors for sensor development. The MXRF screening method is nondestructive, requires minimal sample preparation or special tags for analysis, and the screening time depends on the desired sensitivity

High-throughput screening (HTS) and modeling of the retinoid ...

Science.gov (United States)

Presentation at the Retinoids Review 2nd workshop in Brussels, Belgium on the application of high throughput screening and model to the retinoid system Presentation at the Retinoids Review 2nd workshop in Brussels, Belgium on the application of high throughput screening and model to the retinoid system

Applied time series analysis

CERN Document Server

Woodward, Wayne A; Elliott, Alan C

2011-01-01

""There is scarcely a standard technique that the reader will find left out … this book is highly recommended for those requiring a ready introduction to applicable methods in time series and serves as a useful resource for pedagogical purposes.""-International Statistical Review (2014), 82""Current time series theory for practice is well summarized in this book.""-Emmanuel Parzen, Texas A&M University""What an extraordinary range of topics covered, all very insightfully. I like [the authors'] innovations very much, such as the AR factor table.""-David Findley, U.S. Census Bureau (retired)""…

Analysis of Heavy-Tailed Time Series

DEFF Research Database (Denmark)

Xie, Xiaolei

This thesis is about analysis of heavy-tailed time series. We discuss tail properties of real-world equity return series and investigate the possibility that a single tail index is shared by all return series of actively traded equities in a market. Conditions for this hypothesis to be true...... are identified. We study the eigenvalues and eigenvectors of sample covariance and sample auto-covariance matrices of multivariate heavy-tailed time series, and particularly for time series with very high dimensions. Asymptotic approximations of the eigenvalues and eigenvectors of such matrices are found...... and expressed in terms of the parameters of the dependence structure, among others. Furthermore, we study an importance sampling method for estimating rare-event probabilities of multivariate heavy-tailed time series generated by matrix recursion. We show that the proposed algorithm is efficient in the sense...

Estimation of dynamic flux profiles from metabolic time series data

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Chou I-Chun

2012-07-01

Full Text Available Abstract Background Advances in modern high-throughput techniques of molecular biology have enabled top-down approaches for the estimation of parameter values in metabolic systems, based on time series data. Special among them is the recent method of dynamic flux estimation (DFE, which uses such data not only for parameter estimation but also for the identification of functional forms of the processes governing a metabolic system. DFE furthermore provides diagnostic tools for the evaluation of model validity and of the quality of a model fit beyond residual errors. Unfortunately, DFE works only when the data are more or less complete and the system contains as many independent fluxes as metabolites. These drawbacks may be ameliorated with other types of estimation and information. However, such supplementations incur their own limitations. In particular, assumptions must be made regarding the functional forms of some processes and detailed kinetic information must be available, in addition to the time series data. Results The authors propose here a systematic approach that supplements DFE and overcomes some of its shortcomings. Like DFE, the approach is model-free and requires only minimal assumptions. If sufficient time series data are available, the approach allows the determination of a subset of fluxes that enables the subsequent applicability of DFE to the rest of the flux system. The authors demonstrate the procedure with three artificial pathway systems exhibiting distinct characteristics and with actual data of the trehalose pathway in Saccharomyces cerevisiae. Conclusions The results demonstrate that the proposed method successfully complements DFE under various situations and without a priori assumptions regarding the model representation. The proposed method also permits an examination of whether at all, to what degree, or within what range the available time series data can be validly represented in a particular functional format of

High throughput experimentation for the discovery of new catalysts

International Nuclear Information System (INIS)

Thomson, S.; Hoffmann, C.; Johann, T.; Wolf, A.; Schmidt, H.-W.; Farrusseng, D.; Schueth, F.

2002-01-01

Full text: The use of combinatorial chemistry to obtain new materials has been developed extensively by the pharmaceutical and biochemical industries, but such approaches have been slow to impact on the field of heterogeneous catalysis. The reasons for this lie in with difficulties associated in the synthesis, characterisation and determination of catalytic properties of such materials. In many synthetic and catalytic reactions, the conditions used are difficult to emulate using High Throughput Experimentation (HTE). Furthermore, the ability to screen these catalysts simultaneously in real time, requires the development and/or modification of characterisation methods. Clearly, there is a need for both high throughput synthesis and screening of new and novel reactions, and we describe several new concepts that help to achieve these goals. Although such problems have impeded the development of combinatorial catalysis, the fact remains that many highly attractive processes still exist for which no suitable catalysts have been developed. The ability to decrease the tiFme needed to evaluate catalyst is therefore essential and this makes the use of high throughput techniques highly desirable. In this presentation we will describe the synthesis, catalytic testing, and novel screening methods developed at the Max Planck Institute. Automated synthesis procedures, performed by the use of a modified Gilson pipette robot, will be described, as will the development of two 16 and 49 sample fixed bed reactors and two 25 and 29 sample three phase reactors for catalytic testing. We will also present new techniques for the characterisation of catalysts and catalytic products using standard IR microscopy and infrared focal plane array detection, respectively

An Automated High Throughput Proteolysis and Desalting Platform for Quantitative Proteomic Analysis

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Albert-Baskar Arul

2013-06-01

Full Text Available Proteomics for biomarker validation needs high throughput instrumentation to analyze huge set of clinical samples for quantitative and reproducible analysis at a minimum time without manual experimental errors. Sample preparation, a vital step in proteomics plays a major role in identification and quantification of proteins from biological samples. Tryptic digestion a major check point in sample preparation for mass spectrometry based proteomics needs to be more accurate with rapid processing time. The present study focuses on establishing a high throughput automated online system for proteolytic digestion and desalting of proteins from biological samples quantitatively and qualitatively in a reproducible manner. The present study compares online protein digestion and desalting of BSA with conventional off-line (in-solution method and validated for real time sample for reproducibility. Proteins were identified using SEQUEST data base search engine and the data were quantified using IDEALQ software. The present study shows that the online system capable of handling high throughput samples in 96 well formats carries out protein digestion and peptide desalting efficiently in a reproducible and quantitative manner. Label free quantification showed clear increase of peptide quantities with increase in concentration with much linearity compared to off line method. Hence we would like to suggest that inclusion of this online system in proteomic pipeline will be effective in quantification of proteins in comparative proteomics were the quantification is really very crucial.

Network structure of multivariate time series.

Science.gov (United States)

Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

High throughput electrophysiology: new perspectives for ion channel drug discovery

DEFF Research Database (Denmark)

Willumsen, Niels J; Bech, Morten; Olesen, Søren-Peter

2003-01-01

. A cornerstone in current drug discovery is high throughput screening assays which allow examination of the activity of specific ion channels though only to a limited extent. Conventional patch clamp remains the sole technique with sufficiently high time resolution and sensitivity required for precise and direct....... The introduction of new powerful HTS electrophysiological techniques is predicted to cause a revolution in ion channel drug discovery....

A pocket device for high-throughput optofluidic holographic microscopy

Science.gov (United States)

Mandracchia, B.; Bianco, V.; Wang, Z.; Paturzo, M.; Bramanti, A.; Pioggia, G.; Ferraro, P.

2017-06-01

Here we introduce a compact holographic microscope embedded onboard a Lab-on-a-Chip (LoC) platform. A wavefront division interferometer is realized by writing a polymer grating onto the channel to extract a reference wave from the object wave impinging the LoC. A portion of the beam reaches the samples flowing along the channel path, carrying their information content to the recording device, while one of the diffraction orders from the grating acts as an off-axis reference wave. Polymeric micro-lenses are delivered forward the chip by Pyro-ElectroHydroDynamic (Pyro-EHD) inkjet printing techniques. Thus, all the required optical components are embedded onboard a pocket device, and fast, non-iterative, reconstruction algorithms can be used. We use our device in combination with a novel high-throughput technique, named Space-Time Digital Holography (STDH). STDH exploits the samples motion inside microfluidic channels to obtain a synthetic hologram, mapped in a hybrid space-time domain, and with intrinsic useful features. Indeed, a single Linear Sensor Array (LSA) is sufficient to build up a synthetic representation of the entire experiment (i.e. the STDH) with unlimited Field of View (FoV) along the scanning direction, independently from the magnification factor. The throughput of the imaging system is dramatically increased as STDH provides unlimited FoV, refocusable imaging of samples inside the liquid volume with no need for hologram stitching. To test our embedded STDH microscopy module, we counted, imaged and tracked in 3D with high-throughput red blood cells moving inside the channel volume under non ideal flow conditions.

Applications of high-throughput clonogenic survival assays in high-LET particle microbeams

Directory of Open Access Journals (Sweden)

Antonios eGeorgantzoglou

2016-01-01

Full Text Available Charged particle therapy is increasingly becoming a valuable tool in cancer treatment, mainly due to the favorable interaction of particle radiation with matter. Its application is still limited due, in part, to lack of data regarding the radiosensitivity of certain cell lines to this radiation type, especially to high-LET particles. From the earliest days of radiation biology, the clonogenic survival assay has been used to provide radiation response data. This method produces reliable data but it is not optimized for high-throughput microbeam studies with high-LET radiation where high levels of cell killing lead to a very low probability of maintaining cells’ clonogenic potential. A new method, therefore, is proposed in this paper, which could potentially allow these experiments to be conducted in a high-throughput fashion. Cells are seeded in special polypropylene dishes and bright-field illumination provides cell visualization. Digital images are obtained and cell detection is applied based on corner detection, generating individual cell targets as x-y points. These points in the dish are then irradiated individually by a micron field size high-LET microbeam. Post-irradiation, time-lapse imaging follows cells’ response. All irradiated cells are tracked by linking trajectories in all time-frames, based on finding their nearest position. Cell divisions are detected based on cell appearance and individual cell temporary corner density. The number of divisions anticipated is low due to the high probability of cell killing from high-LET irradiation. Survival curves are produced based on cell’s capacity to divide at least 4-5 times. The process is repeated for a range of doses of radiation. Validation shows the efficiency of the proposed cell detection and tracking method in finding cell divisions.

Applications of High-Throughput Clonogenic Survival Assays in High-LET Particle Microbeams.

Science.gov (United States)

Georgantzoglou, Antonios; Merchant, Michael J; Jeynes, Jonathan C G; Mayhead, Natalie; Punia, Natasha; Butler, Rachel E; Jena, Rajesh

2015-01-01

Charged particle therapy is increasingly becoming a valuable tool in cancer treatment, mainly due to the favorable interaction of particle radiation with matter. Its application is still limited due, in part, to lack of data regarding the radiosensitivity of certain cell lines to this radiation type, especially to high-linear energy transfer (LET) particles. From the earliest days of radiation biology, the clonogenic survival assay has been used to provide radiation response data. This method produces reliable data but it is not optimized for high-throughput microbeam studies with high-LET radiation where high levels of cell killing lead to a very low probability of maintaining cells' clonogenic potential. A new method, therefore, is proposed in this paper, which could potentially allow these experiments to be conducted in a high-throughput fashion. Cells are seeded in special polypropylene dishes and bright-field illumination provides cell visualization. Digital images are obtained and cell detection is applied based on corner detection, generating individual cell targets as x-y points. These points in the dish are then irradiated individually by a micron field size high-LET microbeam. Post-irradiation, time-lapse imaging follows cells' response. All irradiated cells are tracked by linking trajectories in all time-frames, based on finding their nearest position. Cell divisions are detected based on cell appearance and individual cell temporary corner density. The number of divisions anticipated is low due to the high probability of cell killing from high-LET irradiation. Survival curves are produced based on cell's capacity to divide at least four to five times. The process is repeated for a range of doses of radiation. Validation shows the efficiency of the proposed cell detection and tracking method in finding cell divisions.

Dashboard visualizations: Supporting real-time throughput decision-making.

Science.gov (United States)

Franklin, Amy; Gantela, Swaroop; Shifarraw, Salsawit; Johnson, Todd R; Robinson, David J; King, Brent R; Mehta, Amit M; Maddow, Charles L; Hoot, Nathan R; Nguyen, Vickie; Rubio, Adriana; Zhang, Jiajie; Okafor, Nnaemeka G

2017-07-01

Providing timely and effective care in the emergency department (ED) requires the management of individual patients as well as the flow and demands of the entire department. Strategic changes to work processes, such as adding a flow coordination nurse or a physician in triage, have demonstrated improvements in throughput times. However, such global strategic changes do not address the real-time, often opportunistic workflow decisions of individual clinicians in the ED. We believe that real-time representation of the status of the entire emergency department and each patient within it through information visualizations will better support clinical decision-making in-the-moment and provide for rapid intervention to improve ED flow. This notion is based on previous work where we found that clinicians' workflow decisions were often based on an in-the-moment local perspective, rather than a global perspective. Here, we discuss the challenges of designing and implementing visualizations for ED through a discussion of the development of our prototype Throughput Dashboard and the potential it holds for supporting real-time decision-making. Copyright © 2017. Published by Elsevier Inc.

Optimization and high-throughput screening of antimicrobial peptides.

Science.gov (United States)

Blondelle, Sylvie E; Lohner, Karl

2010-01-01

While a well-established process for lead compound discovery in for-profit companies, high-throughput screening is becoming more popular in basic and applied research settings in academia. The development of combinatorial libraries combined with easy and less expensive access to new technologies have greatly contributed to the implementation of high-throughput screening in academic laboratories. While such techniques were earlier applied to simple assays involving single targets or based on binding affinity, they have now been extended to more complex systems such as whole cell-based assays. In particular, the urgent need for new antimicrobial compounds that would overcome the rapid rise of drug-resistant microorganisms, where multiple target assays or cell-based assays are often required, has forced scientists to focus onto high-throughput technologies. Based on their existence in natural host defense systems and their different mode of action relative to commercial antibiotics, antimicrobial peptides represent a new hope in discovering novel antibiotics against multi-resistant bacteria. The ease of generating peptide libraries in different formats has allowed a rapid adaptation of high-throughput assays to the search for novel antimicrobial peptides. Similarly, the availability nowadays of high-quantity and high-quality antimicrobial peptide data has permitted the development of predictive algorithms to facilitate the optimization process. This review summarizes the various library formats that lead to de novo antimicrobial peptide sequences as well as the latest structural knowledge and optimization processes aimed at improving the peptides selectivity.

A Primer on High-Throughput Computing for Genomic Selection

Directory of Open Access Journals (Sweden)

Xiao-Lin eWu

2011-02-01

Full Text Available High-throughput computing (HTC uses computer clusters to solve advanced computational problems, with the goal of accomplishing high throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general purpose computation on a graphics processing unit (GPU provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin – Madison, which can be leveraged for genomic selection, in terms of central processing unit (CPU capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of

Ratiometric fluorescent pH-sensitive polymers for high-throughput monitoring of extracellular pH†

OpenAIRE

Zhang, Liqiang; Su, Fengyu; Kong, Xiangxing; Lee, Fred; Day, Kevin; Gao, Weimin; Vecera, Mary E.; Sohr, Jeremy M.; Buizer, Sean; Tian, Yanqing; Meldrum, Deirdre R

2016-01-01

Extracellular pH has a strong effect on cell metabolism and growth. Precisely detecting extracellular pH with high throughput is critical for cell metabolism research and fermentation applications. In this research, a series of ratiometric fluorescent pH sensitive polymers are developed and the ps-pH-neutral is characterized as the best one for exculsive detection of extracellular pH. Poly(N-(2-hydroxypropyl)methacrylamide) (PHPMA) is used as the host polymer to increase the water solubility ...

Development of rapid high throughput biodosimetry tools for radiological triage

International Nuclear Information System (INIS)

Balajee, Adayabalam S.; Escalona, Maria; Smith, Tammy; Ryan, Terri; Dainiak, Nicholas

2018-01-01

Accidental or intentional radiological or nuclear (R/N) disasters constitute a major threat around the globe that can affect several tens, hundreds and thousands of humans. Currently available cytogenetic biodosimeters are time consuming and laborious to perform making them impractical for triage scenarios. Therefore, it is imperative to develop high throughput techniques which will enable timely assessment of personalized dose for making an appropriate 'life-saving' clinical decision

20180311 - High Throughput Transcriptomics: From screening to pathways (SOT 2018)

Science.gov (United States)

The EPA ToxCast effort has screened thousands of chemicals across hundreds of high-throughput in vitro screening assays. The project is now leveraging high-throughput transcriptomic (HTTr) technologies to substantially expand its coverage of biological pathways. The first HTTr sc...

High throughput label-free platform for statistical bio-molecular sensing

DEFF Research Database (Denmark)

Bosco, Filippo; Hwu, En-Te; Chen, Ching-Hsiu

2011-01-01

Sensors are crucial in many daily operations including security, environmental control, human diagnostics and patient monitoring. Screening and online monitoring require reliable and high-throughput sensing. We report on the demonstration of a high-throughput label-free sensor platform utilizing...

Novel method for the high-throughput processing of slides for the comet assay.

Science.gov (United States)

Karbaschi, Mahsa; Cooke, Marcus S

2014-11-26

Single cell gel electrophoresis (the comet assay), continues to gain popularity as a means of assessing DNA damage. However, the assay's low sample throughput and laborious sample workup procedure are limiting factors to its application. "Scoring", or individually determining DNA damage levels in 50 cells per treatment, is time-consuming, but with the advent of high-throughput scoring, the limitation is now the ability to process significant numbers of comet slides. We have developed a novel method by which multiple slides may be manipulated, and undergo electrophoresis, in batches of 25 rather than individually and, importantly, retains the use of standard microscope comet slides, which are the assay convention. This decreases assay time by 60%, and benefits from an electrophoresis tank with a substantially smaller footprint, and more uniform orientation of gels during electrophoresis. Our high-throughput variant of the comet assay greatly increases the number of samples analysed, decreases assay time, number of individual slide manipulations, reagent requirements and risk of damage to slides. The compact nature of the electrophoresis tank is of particular benefit to laboratories where bench space is at a premium. This novel approach is a significant advance on the current comet assay procedure.

A High-Throughput Biological Calorimetry Core: Steps to Startup, Run, and Maintain a Multiuser Facility.

Science.gov (United States)

Yennawar, Neela H; Fecko, Julia A; Showalter, Scott A; Bevilacqua, Philip C

2016-01-01

Many labs have conventional calorimeters where denaturation and binding experiments are setup and run one at a time. While these systems are highly informative to biopolymer folding and ligand interaction, they require considerable manual intervention for cleaning and setup. As such, the throughput for such setups is limited typically to a few runs a day. With a large number of experimental parameters to explore including different buffers, macromolecule concentrations, temperatures, ligands, mutants, controls, replicates, and instrument tests, the need for high-throughput automated calorimeters is on the rise. Lower sample volume requirements and reduced user intervention time compared to the manual instruments have improved turnover of calorimetry experiments in a high-throughput format where 25 or more runs can be conducted per day. The cost and efforts to maintain high-throughput equipment typically demands that these instruments be housed in a multiuser core facility. We describe here the steps taken to successfully start and run an automated biological calorimetry facility at Pennsylvania State University. Scientists from various departments at Penn State including Chemistry, Biochemistry and Molecular Biology, Bioengineering, Biology, Food Science, and Chemical Engineering are benefiting from this core facility. Samples studied include proteins, nucleic acids, sugars, lipids, synthetic polymers, small molecules, natural products, and virus capsids. This facility has led to higher throughput of data, which has been leveraged into grant support, attracting new faculty hire and has led to some exciting publications. © 2016 Elsevier Inc. All rights reserved.

High Throughput Computing Impact on Meta Genomics (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

Energy Technology Data Exchange (ETDEWEB)

Gore, Brooklin

2011-10-12

This presentation includes a brief background on High Throughput Computing, correlating gene transcription factors, optical mapping, genotype to phenotype mapping via QTL analysis, and current work on next gen sequencing.

Caveats and limitations of plate reader-based high-throughput kinetic measurements of intracellular calcium levels

International Nuclear Information System (INIS)

Heusinkveld, Harm J.; Westerink, Remco H.S.

2011-01-01

Calcium plays a crucial role in virtually all cellular processes, including neurotransmission. The intracellular Ca 2+ concentration ([Ca 2+ ] i ) is therefore an important readout in neurotoxicological and neuropharmacological studies. Consequently, there is an increasing demand for high-throughput measurements of [Ca 2+ ] i , e.g. using multi-well microplate readers, in hazard characterization, human risk assessment and drug development. However, changes in [Ca 2+ ] i are highly dynamic, thereby creating challenges for high-throughput measurements. Nonetheless, several protocols are now available for real-time kinetic measurement of [Ca 2+ ] i in plate reader systems, though the results of such plate reader-based measurements have been questioned. In view of the increasing use of plate reader systems for measurements of [Ca 2+ ] i a careful evaluation of current technologies is warranted. We therefore performed an extensive set of experiments, using two cell lines (PC12 and B35) and two fluorescent calcium-sensitive dyes (Fluo-4 and Fura-2), for comparison of a linear plate reader system with single cell fluorescence microscopy. Our data demonstrate that the use of plate reader systems for high-throughput real-time kinetic measurements of [Ca 2+ ] i is associated with many pitfalls and limitations, including erroneous sustained increases in fluorescence, limited sensitivity and lack of single cell resolution. Additionally, our data demonstrate that probenecid, which is often used to prevent dye leakage, effectively inhibits the depolarization-evoked increase in [Ca 2+ ] i . Overall, the data indicate that the use of current plate reader-based strategies for high-throughput real-time kinetic measurements of [Ca 2+ ] i is associated with caveats and limitations that require further investigation. - Research highlights: → The use of plate readers for high-throughput screening of intracellular Ca 2+ is associated with many pitfalls and limitations. → Single cell

High-throughput screening of filamentous fungi using nanoliter-range droplet-based microfluidics

Science.gov (United States)

Beneyton, Thomas; Wijaya, I. Putu Mahendra; Postros, Prexilia; Najah, Majdi; Leblond, Pascal; Couvent, Angélique; Mayot, Estelle; Griffiths, Andrew D.; Drevelle, Antoine

2016-06-01

Filamentous fungi are an extremely important source of industrial enzymes because of their capacity to secrete large quantities of proteins. Currently, functional screening of fungi is associated with low throughput and high costs, which severely limits the discovery of novel enzymatic activities and better production strains. Here, we describe a nanoliter-range droplet-based microfluidic system specially adapted for the high-throughput sceening (HTS) of large filamentous fungi libraries for secreted enzyme activities. The platform allowed (i) compartmentalization of single spores in ~10 nl droplets, (ii) germination and mycelium growth and (iii) high-throughput sorting of fungi based on enzymatic activity. A 104 clone UV-mutated library of Aspergillus niger was screened based on α-amylase activity in just 90 minutes. Active clones were enriched 196-fold after a single round of microfluidic HTS. The platform is a powerful tool for the development of new production strains with low cost, space and time footprint and should bring enormous benefit for improving the viability of biotechnological processes.

High-throughput GPU-based LDPC decoding

Science.gov (United States)

Chang, Yang-Lang; Chang, Cheng-Chun; Huang, Min-Yu; Huang, Bormin

2010-08-01

Low-density parity-check (LDPC) code is a linear block code known to approach the Shannon limit via the iterative sum-product algorithm. LDPC codes have been adopted in most current communication systems such as DVB-S2, WiMAX, WI-FI and 10GBASE-T. LDPC for the needs of reliable and flexible communication links for a wide variety of communication standards and configurations have inspired the demand for high-performance and flexibility computing. Accordingly, finding a fast and reconfigurable developing platform for designing the high-throughput LDPC decoder has become important especially for rapidly changing communication standards and configurations. In this paper, a new graphic-processing-unit (GPU) LDPC decoding platform with the asynchronous data transfer is proposed to realize this practical implementation. Experimental results showed that the proposed GPU-based decoder achieved 271x speedup compared to its CPU-based counterpart. It can serve as a high-throughput LDPC decoder.

Time-motion analysis of factors affecting patient throughput in an MR imaging center

International Nuclear Information System (INIS)

O'Donohue, J.; Enzmann, D.R.

1986-01-01

The high cost of MR imaging makes efficient use essential. In an effort to increase patient throughput, attention has been focused on shortening the imaging time through reductions in matrix size and number of excitations, and through the use of newer ''fast imaging'' techniques. Less attention has been given to other time-consuming aspects not directly related to imaging time. The authors undertook a time-motion study using a daily log of minute-by-minute activities associated with an MR imaging examination. The times required for the following components of the examination were measured: total study time, examination set-up time, intrastudy physician ''image review'' time, and interstudy patient turnover time. The time lost to claustrophobic reactions, patients' failure to appear for scheduled examinations, unanticipated patient care (sedation, reassurance), and equipment malfunction was also analyzed. Actual imaging time accounted for a relatively small proportion (42%) of total study time. Other factors such as intrastudy image review time (15%), interstudy patient turnover time (11%), and time lost due to claustrophobic reactions, patients' failure to appear for scheduled examinations, and equipment malfunction contributed significantly to the total study time. Simple solutions to these problems can contribute greatly to increasing patient throughput

Evaluating High Throughput Toxicokinetics and Toxicodynamics for IVIVE (WC10)

Science.gov (United States)

High-throughput screening (HTS) generates in vitro data for characterizing potential chemical hazard. TK models are needed to allow in vitro to in vivo extrapolation (IVIVE) to real world situations. The U.S. EPA has created a public tool (R package “httk” for high throughput tox...

Robust Forecasting of Non-Stationary Time Series

NARCIS (Netherlands)

Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.

2010-01-01

This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable

Quantifying memory in complex physiological time-series.

Science.gov (United States)

Shirazi, Amir H; Raoufy, Mohammad R; Ebadi, Haleh; De Rui, Michele; Schiff, Sami; Mazloom, Roham; Hajizadeh, Sohrab; Gharibzadeh, Shahriar; Dehpour, Ahmad R; Amodio, Piero; Jafari, G Reza; Montagnese, Sara; Mani, Ali R

2013-01-01

In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of "memory length" was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are 'forgotten' quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations.

High-throughput optical system for HDES hyperspectral imager

Science.gov (United States)

Václavík, Jan; Melich, Radek; Pintr, Pavel; Pleštil, Jan

2015-01-01

Affordable, long-wave infrared hyperspectral imaging calls for use of an uncooled FPA with high-throughput optics. This paper describes the design of the optical part of a stationary hyperspectral imager in a spectral range of 7-14 um with a field of view of 20°×10°. The imager employs a push-broom method made by a scanning mirror. High throughput and a demand for simplicity and rigidity led to a fully refractive design with highly aspheric surfaces and off-axis positioning of the detector array. The design was optimized to exploit the machinability of infrared materials by the SPDT method and a simple assemblage.

Infra-red thermography for high throughput field phenotyping in Solanum tuberosum.

Directory of Open Access Journals (Sweden)

Ankush Prashar

Full Text Available The rapid development of genomic technology has made high throughput genotyping widely accessible but the associated high throughput phenotyping is now the major limiting factor in genetic analysis of traits. This paper evaluates the use of thermal imaging for the high throughput field phenotyping of Solanum tuberosum for differences in stomatal behaviour. A large multi-replicated trial of a potato mapping population was used to investigate the consistency in genotypic rankings across different trials and across measurements made at different times of day and on different days. The results confirmed a high degree of consistency between the genotypic rankings based on relative canopy temperature on different occasions. Genotype discrimination was enhanced both through normalising data by expressing genotype temperatures as differences from image means and through the enhanced replication obtained by using overlapping images. A Monte Carlo simulation approach was used to confirm the magnitude of genotypic differences that it is possible to discriminate. The results showed a clear negative association between canopy temperature and final tuber yield for this population, when grown under ample moisture supply. We have therefore established infrared thermography as an easy, rapid and non-destructive screening method for evaluating large population trials for genetic analysis. We also envisage this approach as having great potential for evaluating plant response to stress under field conditions.

High-throughput, label-free, single-cell, microalgal lipid screening by machine-learning-equipped optofluidic time-stretch quantitative phase microscopy.

Science.gov (United States)

Guo, Baoshan; Lei, Cheng; Kobayashi, Hirofumi; Ito, Takuro; Yalikun, Yaxiaer; Jiang, Yiyue; Tanaka, Yo; Ozeki, Yasuyuki; Goda, Keisuke

2017-05-01

The development of reliable, sustainable, and economical sources of alternative fuels to petroleum is required to tackle the global energy crisis. One such alternative is microalgal biofuel, which is expected to play a key role in reducing the detrimental effects of global warming as microalgae absorb atmospheric CO 2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid amounts and fail to characterize a diverse population of microalgal cells with single-cell resolution in a non-invasive and interference-free manner. Here high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy was demonstrated. In particular, Euglena gracilis, an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement), within lipid droplets was investigated. The optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch quantitative phase microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase maps of every single cell at a high throughput of 10,000 cells/s, enabling accurate cell classification without the need for fluorescent staining. Specifically, the dataset was used to characterize heterogeneous populations of E. gracilis cells under two different culture conditions (nitrogen-sufficient and nitrogen-deficient) and achieve the cell classification with an error rate of only 2.15%. The method holds promise as an effective analytical tool for microalgae-based biofuel production. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Low-cost guaranteed-throughput communication ring for real-time streaming MPSoCs

NARCIS (Netherlands)

Dekens, B.H.J.; Kurtin, Philip Sebastian; Bekooij, Marco Jan Gerrit; Smit, Gerardus Johannes Maria

2013-01-01

Connection-oriented guaranteed-throughput mesh-based networks on chip have been proposed as a replacement for buses in real-time embedded multiprocessor systems such as software defined radios. Even with attractive features like throughput and latency guarantees they are not always used because

High Throughput Plasma Water Treatment

Science.gov (United States)

Mujovic, Selman; Foster, John

2016-10-01

The troublesome emergence of new classes of micro-pollutants, such as pharmaceuticals and endocrine disruptors, poses challenges for conventional water treatment systems. In an effort to address these contaminants and to support water reuse in drought stricken regions, new technologies must be introduced. The interaction of water with plasma rapidly mineralizes organics by inducing advanced oxidation in addition to other chemical, physical and radiative processes. The primary barrier to the implementation of plasma-based water treatment is process volume scale up. In this work, we investigate a potentially scalable, high throughput plasma water reactor that utilizes a packed bed dielectric barrier-like geometry to maximize the plasma-water interface. Here, the water serves as the dielectric medium. High-speed imaging and emission spectroscopy are used to characterize the reactor discharges. Changes in methylene blue concentration and basic water parameters are mapped as a function of plasma treatment time. Experimental results are compared to electrostatic and plasma chemistry computations, which will provide insight into the reactor's operation so that efficiency can be assessed. Supported by NSF (CBET 1336375).

High Performance Computing Modernization Program Kerberos Throughput Test Report

Science.gov (United States)

2017-10-26

Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/5524--17-9751 High Performance Computing Modernization Program Kerberos Throughput Test ...NUMBER 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 2. REPORT TYPE1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 6. AUTHOR(S) 8. PERFORMING...PAGE 18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT High Performance Computing Modernization Program Kerberos Throughput Test Report Daniel G. Gdula* and

High-Density Liquid-State Machine Circuitry for Time-Series Forecasting.

Science.gov (United States)

Rosselló, Josep L; Alomar, Miquel L; Morro, Antoni; Oliver, Antoni; Canals, Vincent

2016-08-01

Spiking neural networks (SNN) are the last neural network generation that try to mimic the real behavior of biological neurons. Although most research in this area is done through software applications, it is in hardware implementations in which the intrinsic parallelism of these computing systems are more efficiently exploited. Liquid state machines (LSM) have arisen as a strategic technique to implement recurrent designs of SNN with a simple learning methodology. In this work, we show a new low-cost methodology to implement high-density LSM by using Boolean gates. The proposed method is based on the use of probabilistic computing concepts to reduce hardware requirements, thus considerably increasing the neuron count per chip. The result is a highly functional system that is applied to high-speed time series forecasting.

GPS Position Time Series @ JPL

Science.gov (United States)

Owen, Susan; Moore, Angelyn; Kedar, Sharon; Liu, Zhen; Webb, Frank; Heflin, Mike; Desai, Shailen

2013-01-01

Different flavors of GPS time series analysis at JPL - Use same GPS Precise Point Positioning Analysis raw time series - Variations in time series analysis/post-processing driven by different users. center dot JPL Global Time Series/Velocities - researchers studying reference frame, combining with VLBI/SLR/DORIS center dot JPL/SOPAC Combined Time Series/Velocities - crustal deformation for tectonic, volcanic, ground water studies center dot ARIA Time Series/Coseismic Data Products - Hazard monitoring and response focused center dot ARIA data system designed to integrate GPS and InSAR - GPS tropospheric delay used for correcting InSAR - Caltech's GIANT time series analysis uses GPS to correct orbital errors in InSAR - Zhen Liu's talking tomorrow on InSAR Time Series analysis

A primer on high-throughput computing for genomic selection.

Science.gov (United States)

Wu, Xiao-Lin; Beissinger, Timothy M; Bauck, Stewart; Woodward, Brent; Rosa, Guilherme J M; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

2011-01-01

High-throughput computing (HTC) uses computer clusters to solve advanced computational problems, with the goal of accomplishing high-throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long, and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl, and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general-purpose computation on a graphics processing unit provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin-Madison, which can be leveraged for genomic selection, in terms of central processing unit capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general-purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of marker panels to realized

Protocol: high throughput silica-based purification of RNA from Arabidopsis seedlings in a 96-well format

Directory of Open Access Journals (Sweden)

Salvo-Chirnside Eliane

2011-12-01

Full Text Available Abstract The increasing popularity of systems-based approaches to plant research has resulted in a demand for high throughput (HTP methods to be developed. RNA extraction from multiple samples in an experiment is a significant bottleneck in performing systems-level genomic studies. Therefore we have established a high throughput method of RNA extraction from Arabidopsis thaliana to facilitate gene expression studies in this widely used plant model. We present optimised manual and automated protocols for the extraction of total RNA from 9-day-old Arabidopsis seedlings in a 96 well plate format using silica membrane-based methodology. Consistent and reproducible yields of high quality RNA are isolated averaging 8.9 μg total RNA per sample (~20 mg plant tissue. The purified RNA is suitable for subsequent qPCR analysis of the expression of over 500 genes in triplicate from each sample. Using the automated procedure, 192 samples (2 × 96 well plates can easily be fully processed (samples homogenised, RNA purified and quantified in less than half a day. Additionally we demonstrate that plant samples can be stored in RNAlater at -20°C (but not 4°C for 10 months prior to extraction with no significant effect on RNA yield or quality. Additionally, disrupted samples can be stored in the lysis buffer at -20°C for at least 6 months prior to completion of the extraction procedure providing a flexible sampling and storage scheme to facilitate complex time series experiments.

Protocol: high throughput silica-based purification of RNA from Arabidopsis seedlings in a 96-well format.

Science.gov (United States)

Salvo-Chirnside, Eliane; Kane, Steven; Kerr, Lorraine E

2011-12-02

The increasing popularity of systems-based approaches to plant research has resulted in a demand for high throughput (HTP) methods to be developed. RNA extraction from multiple samples in an experiment is a significant bottleneck in performing systems-level genomic studies. Therefore we have established a high throughput method of RNA extraction from Arabidopsis thaliana to facilitate gene expression studies in this widely used plant model. We present optimised manual and automated protocols for the extraction of total RNA from 9-day-old Arabidopsis seedlings in a 96 well plate format using silica membrane-based methodology. Consistent and reproducible yields of high quality RNA are isolated averaging 8.9 μg total RNA per sample (~20 mg plant tissue). The purified RNA is suitable for subsequent qPCR analysis of the expression of over 500 genes in triplicate from each sample. Using the automated procedure, 192 samples (2 × 96 well plates) can easily be fully processed (samples homogenised, RNA purified and quantified) in less than half a day. Additionally we demonstrate that plant samples can be stored in RNAlater at -20°C (but not 4°C) for 10 months prior to extraction with no significant effect on RNA yield or quality. Additionally, disrupted samples can be stored in the lysis buffer at -20°C for at least 6 months prior to completion of the extraction procedure providing a flexible sampling and storage scheme to facilitate complex time series experiments.

Correction of Microplate Data from High-Throughput Screening.

Science.gov (United States)

Wang, Yuhong; Huang, Ruili

2016-01-01

High-throughput screening (HTS) makes it possible to collect cellular response data from a large number of cell lines and small molecules in a timely and cost-effective manner. The errors and noises in the microplate-formatted data from HTS have unique characteristics, and they can be generally grouped into three categories: run-wise (temporal, multiple plates), plate-wise (background pattern, single plate), and well-wise (single well). In this chapter, we describe a systematic solution for identifying and correcting such errors and noises, mainly basing on pattern recognition and digital signal processing technologies.

Chromatographic Monoliths for High-Throughput Immunoaffinity Isolation of Transferrin from Human Plasma

Directory of Open Access Journals (Sweden)

Irena Trbojević-Akmačić

2016-06-01

Full Text Available Changes in protein glycosylation are related to different diseases and have a potential as diagnostic and prognostic disease biomarkers. Transferrin (Tf glycosylation changes are common marker for congenital disorders of glycosylation. However, biological interindividual variability of Tf N-glycosylation and genes involved in glycosylation regulation are not known. Therefore, high-throughput Tf isolation method and large scale glycosylation studies are needed in order to address these questions. Due to their unique chromatographic properties, the use of chromatographic monoliths enables very fast analysis cycle, thus significantly increasing sample preparation throughput. Here, we are describing characterization of novel immunoaffinity-based monolithic columns in a 96-well plate format for specific high-throughput purification of human Tf from blood plasma. We optimized the isolation and glycan preparation procedure for subsequent ultra performance liquid chromatography (UPLC analysis of Tf N-glycosylation and managed to increase the sensitivity for approximately three times compared to initial experimental conditions, with very good reproducibility. This work is licensed under a Creative Commons Attribution 4.0 International License.

Time series analysis time series analysis methods and applications

CERN Document Server

Rao, Tata Subba; Rao, C R

2012-01-01

The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments. The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowened experts in their respect...

High-throughput theoretical design of lithium battery materials

International Nuclear Information System (INIS)

Ling Shi-Gang; Gao Jian; Xiao Rui-Juan; Chen Li-Quan

2016-01-01

The rapid evolution of high-throughput theoretical design schemes to discover new lithium battery materials is reviewed, including high-capacity cathodes, low-strain cathodes, anodes, solid state electrolytes, and electrolyte additives. With the development of efficient theoretical methods and inexpensive computers, high-throughput theoretical calculations have played an increasingly important role in the discovery of new materials. With the help of automatic simulation flow, many types of materials can be screened, optimized and designed from a structural database according to specific search criteria. In advanced cell technology, new materials for next generation lithium batteries are of great significance to achieve performance, and some representative criteria are: higher energy density, better safety, and faster charge/discharge speed. (topical review)

A high-throughput surface plasmon resonance biosensor based on differential interferometric imaging

International Nuclear Information System (INIS)

Wang, Daqian; Ding, Lili; Zhang, Wei; Zhang, Enyao; Yu, Xinglong; Luo, Zhaofeng; Ou, Huichao

2012-01-01

A new high-throughput surface plasmon resonance (SPR) biosensor based on differential interferometric imaging is reported. The two SPR interferograms of the sensing surface are imaged on two CCD cameras. The phase difference between the two interferograms is 180°. The refractive index related factor (RIRF) of the sensing surface is calculated from the two simultaneously acquired interferograms. The simulation results indicate that the RIRF exhibits a linear relationship with the refractive index of the sensing surface and is unaffected by the noise, drift and intensity distribution of the light source. The affinity and kinetic information can be extracted in real time from continuously acquired RIRF distributions. The results of refractometry experiments show that the dynamic detection range of SPR differential interferometric imaging system can be over 0.015 refractive index unit (RIU). High refractive index resolution is down to 0.45 RU (1 RU = 1 × 10 −6 RIU). Imaging and protein microarray experiments demonstrate the ability of high-throughput detection. The aptamer experiments demonstrate that the SPR sensor based on differential interferometric imaging has a great capability to be implemented for high-throughput aptamer kinetic evaluation. These results suggest that this biosensor has the potential to be utilized in proteomics and drug discovery after further improvement. (paper)

High-Throughput Block Optical DNA Sequence Identification.

Science.gov (United States)

Sagar, Dodderi Manjunatha; Korshoj, Lee Erik; Hanson, Katrina Bethany; Chowdhury, Partha Pratim; Otoupal, Peter Britton; Chatterjee, Anushree; Nagpal, Prashant

2018-01-01

Optical techniques for molecular diagnostics or DNA sequencing generally rely on small molecule fluorescent labels, which utilize light with a wavelength of several hundred nanometers for detection. Developing a label-free optical DNA sequencing technique will require nanoscale focusing of light, a high-throughput and multiplexed identification method, and a data compression technique to rapidly identify sequences and analyze genomic heterogeneity for big datasets. Such a method should identify characteristic molecular vibrations using optical spectroscopy, especially in the "fingerprinting region" from ≈400-1400 cm -1 . Here, surface-enhanced Raman spectroscopy is used to demonstrate label-free identification of DNA nucleobases with multiplexed 3D plasmonic nanofocusing. While nanometer-scale mode volumes prevent identification of single nucleobases within a DNA sequence, the block optical technique can identify A, T, G, and C content in DNA k-mers. The content of each nucleotide in a DNA block can be a unique and high-throughput method for identifying sequences, genes, and other biomarkers as an alternative to single-letter sequencing. Additionally, coupling two complementary vibrational spectroscopy techniques (infrared and Raman) can improve block characterization. These results pave the way for developing a novel, high-throughput block optical sequencing method with lossy genomic data compression using k-mer identification from multiplexed optical data acquisition. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automated high-throughput flow-through real-time diagnostic system

Science.gov (United States)

Regan, John Frederick

2012-10-30

An automated real-time flow-through system capable of processing multiple samples in an asynchronous, simultaneous, and parallel fashion for nucleic acid extraction and purification, followed by assay assembly, genetic amplification, multiplex detection, analysis, and decontamination. The system is able to hold and access an unlimited number of fluorescent reagents that may be used to screen samples for the presence of specific sequences. The apparatus works by associating extracted and purified sample with a series of reagent plugs that have been formed in a flow channel and delivered to a flow-through real-time amplification detector that has a multiplicity of optical windows, to which the sample-reagent plugs are placed in an operative position. The diagnostic apparatus includes sample multi-position valves, a master sample multi-position valve, a master reagent multi-position valve, reagent multi-position valves, and an optical amplification/detection system.

Introduction to Time Series Modeling

CERN Document Server

Kitagawa, Genshiro

2010-01-01

In time series modeling, the behavior of a certain phenomenon is expressed in relation to the past values of itself and other covariates. Since many important phenomena in statistical analysis are actually time series and the identification of conditional distribution of the phenomenon is an essential part of the statistical modeling, it is very important and useful to learn fundamental methods of time series modeling. Illustrating how to build models for time series using basic methods, "Introduction to Time Series Modeling" covers numerous time series models and the various tools f

High throughput salt separation from uranium deposits

Energy Technology Data Exchange (ETDEWEB)

Kwon, S.W.; Park, K.M.; Kim, J.G.; Kim, I.T.; Park, S.B., E-mail: swkwon@kaeri.re.kr [Korea Atomic Energy Research Inst. (Korea, Republic of)

2014-07-01

It is very important to increase the throughput of the salt separation system owing to the high uranium content of spent nuclear fuel and high salt fraction of uranium dendrites in pyroprocessing. Multilayer porous crucible system was proposed to increase a throughput of the salt distiller in this study. An integrated sieve-crucible assembly was also investigated for the practical use of the porous crucible system. The salt evaporation behaviors were compared between the conventional nonporous crucible and the porous crucible. Two step weight reductions took place in the porous crucible, whereas the salt weight reduced only at high temperature by distillation in a nonporous crucible. The first weight reduction in the porous crucible was caused by the liquid salt penetrated out through the perforated crucible during the temperature elevation until the distillation temperature. Multilayer porous crucibles have a benefit to expand the evaporation surface area. (author)

Ethoscopes: An open platform for high-throughput ethomics.

Directory of Open Access Journals (Sweden)

Quentin Geissmann

2017-10-01

Full Text Available Here, we present the use of ethoscopes, which are machines for high-throughput analysis of behavior in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable. They perform, in real-time, tracking and profiling of behavior by using a supervised machine learning algorithm, are able to deliver behaviorally triggered stimuli to flies in a feedback-loop mode, and are highly customizable and open source. Ethoscopes can be built easily by using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at http://lab.gilest.ro/ethoscope.

COMPUTER APPROACHES TO WHEAT HIGH-THROUGHPUT PHENOTYPING

Directory of Open Access Journals (Sweden)

Afonnikov D.

2012-08-01

Full Text Available The growing need for rapid and accurate approaches for large-scale assessment of phenotypic characters in plants becomes more and more obvious in the studies looking into relationships between genotype and phenotype. This need is due to the advent of high throughput methods for analysis of genomes. Nowadays, any genetic experiment involves data on thousands and dozens of thousands of plants. Traditional ways of assessing most phenotypic characteristics (those with reliance on the eye, the touch, the ruler are little effective on samples of such sizes. Modern approaches seek to take advantage of automated phenotyping, which warrants a much more rapid data acquisition, higher accuracy of the assessment of phenotypic features, measurement of new parameters of these features and exclusion of human subjectivity from the process. Additionally, automation allows measurement data to be rapidly loaded into computer databases, which reduces data processing time.In this work, we present the WheatPGE information system designed to solve the problem of integration of genotypic and phenotypic data and parameters of the environment, as well as to analyze the relationships between the genotype and phenotype in wheat. The system is used to consolidate miscellaneous data on a plant for storing and processing various morphological traits and genotypes of wheat plants as well as data on various environmental factors. The system is available at www.wheatdb.org. Its potential in genetic experiments has been demonstrated in high-throughput phenotyping of wheat leaf pubescence.

High-throughput epitope identification for snakebite antivenom

DEFF Research Database (Denmark)

Engmark, Mikael; De Masi, Federico; Laustsen, Andreas Hougaard

Insight into the epitopic recognition pattern for polyclonal antivenoms is a strong tool for accurate prediction of antivenom cross-reactivity and provides a basis for design of novel antivenoms. In this work, a high-throughput approach was applied to characterize linear epitopes in 966 individua...... toxins from pit vipers (Crotalidae) using the ICP Crotalidae antivenom. Due to an abundance of snake venom metalloproteinases and phospholipase A2s in the venoms used for production of the investigated antivenom, this study focuses on these toxin families.......Insight into the epitopic recognition pattern for polyclonal antivenoms is a strong tool for accurate prediction of antivenom cross-reactivity and provides a basis for design of novel antivenoms. In this work, a high-throughput approach was applied to characterize linear epitopes in 966 individual...

Towards a high throughput droplet-based agglutination assay

KAUST Repository

Kodzius, Rimantas; Castro, David; Foulds, Ian G.

2013-01-01

This work demonstrates the detection method for a high throughput droplet based agglutination assay system. Using simple hydrodynamic forces to mix and aggregate functionalized microbeads we avoid the need to use magnetic assistance or mixing structures. The concentration of our target molecules was estimated by agglutination strength, obtained through optical image analysis. Agglutination in droplets was performed with flow rates of 150 µl/min and occurred in under a minute, with potential to perform high-throughput measurements. The lowest target concentration detected in droplet microfluidics was 0.17 nM, which is three orders of magnitude more sensitive than a conventional card based agglutination assay.

Towards a high throughput droplet-based agglutination assay

KAUST Repository

Kodzius, Rimantas

2013-10-22

This work demonstrates the detection method for a high throughput droplet based agglutination assay system. Using simple hydrodynamic forces to mix and aggregate functionalized microbeads we avoid the need to use magnetic assistance or mixing structures. The concentration of our target molecules was estimated by agglutination strength, obtained through optical image analysis. Agglutination in droplets was performed with flow rates of 150 µl/min and occurred in under a minute, with potential to perform high-throughput measurements. The lowest target concentration detected in droplet microfluidics was 0.17 nM, which is three orders of magnitude more sensitive than a conventional card based agglutination assay.

Arioc: high-throughput read alignment with GPU-accelerated exploration of the seed-and-extend search space

Directory of Open Access Journals (Sweden)

Richard Wilton

2015-03-01

Full Text Available When computing alignments of DNA sequences to a large genome, a key element in achieving high processing throughput is to prioritize locations in the genome where high-scoring mappings might be expected. We formulated this task as a series of list-processing operations that can be efficiently performed on graphics processing unit (GPU hardware.We followed this approach in implementing a read aligner called Arioc that uses GPU-based parallel sort and reduction techniques to identify high-priority locations where potential alignments may be found. We then carried out a read-by-read comparison of Arioc’s reported alignments with the alignments found by several leading read aligners. With simulated reads, Arioc has comparable or better accuracy than the other read aligners we tested. With human sequencing reads, Arioc demonstrates significantly greater throughput than the other aligners we evaluated across a wide range of sensitivity settings. The Arioc software is available at https://github.com/RWilton/Arioc. It is released under a BSD open-source license.

A high-throughput method for GMO multi-detection using a microfluidic dynamic array

NARCIS (Netherlands)

Brod, F.C.A.; Dijk, van J.P.; Voorhuijzen, M.M.; Dinon, A.Z.; Guimarães, L.H.S.; Scholtens, I.M.J.; Arisi, A.C.M.; Kok, E.J.

2014-01-01

The ever-increasing production of genetically modified crops generates a demand for high-throughput DNAbased methods for the enforcement of genetically modified organisms (GMO) labelling requirements. The application of standard real-time PCR will become increasingly costly with the growth of the

Super-Hydrophobic High Throughput Electrospun Cellulose Acetate (CA) Nanofibrous Mats as Oil Selective Sorbents

Science.gov (United States)

Han, Chao

The threat of oil pollution increases with the expansion of oil exploration and production activities, as well as the industrial growth around the world. Use of sorbents is a common method to deal with the oil spills. In this work, an advanced sorbent technology is described. A series of non-woven Cellulose Acetate (CA) nanofibrous mats with a 3D fibrous structure were synthesized by a novel high-throughput electrospinning technique. The precursor was solutions of CA/ acetic acid-acetone in various concentrations. Among them, 15.0% CA exhibits a superhydrophobic surface property, with a water contact angle of 128.95°. Its oil sorption capacity is many times higher the oil sorption capacity of the best commercial sorbent available in the market. Also, it showed good buoyancy properties on the water both as dry-mat and oil-saturated mat. In addition, it is biodegradable, easily available, easily manufactured, so the CA nanofibrous mat is an excellent candidate as oil sorbent for oil spill in water treatment.

High-throughput screening of small molecule libraries using SAMDI mass spectrometry.

Science.gov (United States)

Gurard-Levin, Zachary A; Scholle, Michael D; Eisenberg, Adam H; Mrksich, Milan

2011-07-11

High-throughput screening is a common strategy used to identify compounds that modulate biochemical activities, but many approaches depend on cumbersome fluorescent reporters or antibodies and often produce false-positive hits. The development of "label-free" assays addresses many of these limitations, but current approaches still lack the throughput needed for applications in drug discovery. This paper describes a high-throughput, label-free assay that combines self-assembled monolayers with mass spectrometry, in a technique called SAMDI, as a tool for screening libraries of 100,000 compounds in one day. This method is fast, has high discrimination, and is amenable to a broad range of chemical and biological applications.

High-Throughput Tabular Data Processor - Platform independent graphical tool for processing large data sets.

Science.gov (United States)

Madanecki, Piotr; Bałut, Magdalena; Buckley, Patrick G; Ochocka, J Renata; Bartoszewski, Rafał; Crossman, David K; Messiaen, Ludwine M; Piotrowski, Arkadiusz

2018-01-01

High-throughput technologies generate considerable amount of data which often requires bioinformatic expertise to analyze. Here we present High-Throughput Tabular Data Processor (HTDP), a platform independent Java program. HTDP works on any character-delimited column data (e.g. BED, GFF, GTF, PSL, WIG, VCF) from multiple text files and supports merging, filtering and converting of data that is produced in the course of high-throughput experiments. HTDP can also utilize itemized sets of conditions from external files for complex or repetitive filtering/merging tasks. The program is intended to aid global, real-time processing of large data sets using a graphical user interface (GUI). Therefore, no prior expertise in programming, regular expression, or command line usage is required of the user. Additionally, no a priori assumptions are imposed on the internal file composition. We demonstrate the flexibility and potential of HTDP in real-life research tasks including microarray and massively parallel sequencing, i.e. identification of disease predisposing variants in the next generation sequencing data as well as comprehensive concurrent analysis of microarray and sequencing results. We also show the utility of HTDP in technical tasks including data merge, reduction and filtering with external criteria files. HTDP was developed to address functionality that is missing or rudimentary in other GUI software for processing character-delimited column data from high-throughput technologies. Flexibility, in terms of input file handling, provides long term potential functionality in high-throughput analysis pipelines, as the program is not limited by the currently existing applications and data formats. HTDP is available as the Open Source software (https://github.com/pmadanecki/htdp).

Creation of a small high-throughput screening facility.

Science.gov (United States)

Flak, Tod

2009-01-01

The creation of a high-throughput screening facility within an organization is a difficult task, requiring a substantial investment of time, money, and organizational effort. Major issues to consider include the selection of equipment, the establishment of data analysis methodologies, and the formation of a group having the necessary competencies. If done properly, it is possible to build a screening system in incremental steps, adding new pieces of equipment and data analysis modules as the need grows. Based upon our experience with the creation of a small screening service, we present some guidelines to consider in planning a screening facility.

Preliminary High-Throughput Metagenome Assembly

Energy Technology Data Exchange (ETDEWEB)

Dusheyko, Serge; Furman, Craig; Pangilinan, Jasmyn; Shapiro, Harris; Tu, Hank

2007-03-26

Metagenome data sets present a qualitatively different assembly problem than traditional single-organism whole-genome shotgun (WGS) assembly. The unique aspects of such projects include the presence of a potentially large number of distinct organisms and their representation in the data set at widely different fractions. In addition, multiple closely related strains could be present, which would be difficult to assemble separately. Failure to take these issues into account can result in poor assemblies that either jumble together different strains or which fail to yield useful results. The DOE Joint Genome Institute has sequenced a number of metagenomic projects and plans to considerably increase this number in the coming year. As a result, the JGI has a need for high-throughput tools and techniques for handling metagenome projects. We present the techniques developed to handle metagenome assemblies in a high-throughput environment. This includes a streamlined assembly wrapper, based on the JGI?s in-house WGS assembler, Jazz. It also includes the selection of sensible defaults targeted for metagenome data sets, as well as quality control automation for cleaning up the raw results. While analysis is ongoing, we will discuss preliminary assessments of the quality of the assembly results (http://fames.jgi-psf.org).

High-throughput diagnosis of potato cyst nematodes in soil samples.

Science.gov (United States)

Reid, Alex; Evans, Fiona; Mulholland, Vincent; Cole, Yvonne; Pickup, Jon

2015-01-01

Potato cyst nematode (PCN) is a damaging soilborne pest of potatoes which can cause major crop losses. In 2010, a new European Union directive (2007/33/EC) on the control of PCN came into force. Under the new directive, seed potatoes can only be planted on land which has been found to be free from PCN infestation following an official soil test. A major consequence of the new directive was the introduction of a new harmonized soil sampling rate resulting in a threefold increase in the number of samples requiring testing. To manage this increase with the same staffing resources, we have replaced the traditional diagnostic methods. A system has been developed for the processing of soil samples, extraction of DNA from float material, and detection of PCN by high-throughput real-time PCR. Approximately 17,000 samples are analyzed each year using this method. This chapter describes the high-throughput processes for the production of float material from soil samples, DNA extraction from the entire float, and subsequent detection and identification of PCN within these samples.

A multilayer microdevice for cell-based high-throughput drug screening

International Nuclear Information System (INIS)

Liu, Chong; Wang, Lei; Li, Jingmin; Ding, Xiping; Chunyu, Li; Xu, Zheng; Wang, Qi

2012-01-01

A multilayer polydimethylsiloxane microdevice for cell-based high-throughput drug screening is described in this paper. This established microdevice was based on a modularization method and it integrated a drug/medium concentration gradient generator (CGG), pneumatic microvalves and a cell culture microchamber array. The CGG was able to generate five steps of linear concentrations with the same outlet flow rate. The medium/drug flowed through CGG and then into the pear-shaped cell culture microchambers vertically. This vertical perfusion mode was used to reduce the impact of the shear stress on the physiology of cells induced by the fluid flow in the microchambers. Pear-shaped microchambers with two arrays of miropillars at each outlet were adopted in this microdevice, which were beneficial to cell distribution. The chemotherapeutics Cisplatin (DDP)-induced Cisplatin-resistant cell line A549/DDP apoptotic experiments were performed well on this platform. The results showed that this novel microdevice could not only provide well-defined and stable conditions for cell culture, but was also useful for cell-based high-throughput drug screening with less reagents and time consumption. (paper)

Quantitative analysis of treatment process time and throughput capacity for spot scanning proton therapy

International Nuclear Information System (INIS)

Suzuki, Kazumichi; Sahoo, Narayan; Zhang, Xiaodong; Poenisch, Falk; Mackin, Dennis S.; Liu, Amy Y.; Wu, Richard; Zhu, X. Ronald; Gillin, Michael T.; Palmer, Matthew B.; Frank, Steven J.; Lee, Andrew K.

2016-01-01

approximately 30%–40% of total treatment time for the total target volumes exceeding 200 cm 3 , which was the case for more than 80% of the patients in this study. When total treatment time was modeled as a function of the number of fields and total target volume, the model overestimated total treatment time by 12% on average, with a standard deviation of 32%. A sensitivity analysis of throughput capacity for a hypothetical four-room spot scanning proton therapy center identified several priority items for improvements in throughput capacity, including operation time, beam delivery time, and patient immobilization and setup time. Conclusions: The spot scanning port at our proton therapy center has operated at a high performance level and has been used to treat a large number of complex cases. Further improvements in efficiency may be feasible in the areas of facility operation, beam delivery, patient immobilization and setup, and optimization of treatment scheduling.

Development of a High-Throughput Ion-Exchange Resin Characterization Workflow.

Science.gov (United States)

Liu, Chun; Dermody, Daniel; Harris, Keith; Boomgaard, Thomas; Sweeney, Jeff; Gisch, Daryl; Goltz, Bob

2017-06-12

A novel high-throughout (HTR) ion-exchange (IEX) resin workflow has been developed for characterizing ion exchange equilibrium of commercial and experimental IEX resins against a range of different applications where water environment differs from site to site. Because of its much higher throughput, design of experiment (DOE) methodology can be easily applied for studying the effects of multiple factors on resin performance. Two case studies will be presented to illustrate the efficacy of the combined HTR workflow and DOE method. In case study one, a series of anion exchange resins have been screened for selective removal of NO 3 - and NO 2 - in water environments consisting of multiple other anions, varied pH, and ionic strength. The response surface model (RSM) is developed to statistically correlate the resin performance with the water composition and predict the best resin candidate. In case study two, the same HTR workflow and DOE method have been applied for screening different cation exchange resins in terms of the selective removal of Mg 2+ , Ca 2+ , and Ba 2+ from high total dissolved salt (TDS) water. A master DOE model including all of the cation exchange resins is created to predict divalent cation removal by different IEX resins under specific conditions, from which the best resin candidates can be identified. The successful adoption of HTR workflow and DOE method for studying the ion exchange of IEX resins can significantly reduce the resources and time to address industry and application needs.

High throughput octal alpha/gamma spectrometer for low level bioassay estimations

International Nuclear Information System (INIS)

Bhasin, B.D.; Shirke, S.H.; Suri, M.M.; Vaidya, P.P.; Ghodgaonkar, M.D.

1995-01-01

The present paper describes the development of a high throughput octal alpha spectrometry system specially developed for the estimation of low levels of actinides in bioassay and environmental samples. The system processes simultaneously the outputs coming from eight independent detectors. It can be configured to simultaneously record low level alpha and gamma spectra. The high throughput is achieved by using a prioritised multiplexer router. The prioritised multiplexing and routing coupled with fast 8K ADC (conversion time 20 μsec) allow simultaneous acquisition of multiple spectra without any significant loss in counts. The dual (8K, 24bit) port memory facilitates easy online viewing of spectrum buildup. A menu driven user friendly software makes the operating system convenient to use. A specially developed software provides built-in routines for processing the spectra and estimating the isotopic activity. The interactive mode of software provides easy identification of isotopes compatible with the separation chemistry of different actinides. (author). 6 refs., 2 figs

Novel high-throughput cell-based hybridoma screening methodology using the Celigo Image Cytometer.

Science.gov (United States)

Zhang, Haohai; Chan, Leo Li-Ying; Rice, William; Kassam, Nasim; Longhi, Maria Serena; Zhao, Haitao; Robson, Simon C; Gao, Wenda; Wu, Yan

2017-08-01

Hybridoma screening is a critical step for antibody discovery, which necessitates prompt identification of potential clones from hundreds to thousands of hybridoma cultures against the desired immunogen. Technical issues associated with ELISA- and flow cytometry-based screening limit accuracy and diminish high-throughput capability, increasing time and cost. Conventional ELISA screening with coated antigen is also impractical for difficult-to-express hydrophobic membrane antigens or multi-chain protein complexes. Here, we demonstrate novel high-throughput screening methodology employing the Celigo Image Cytometer, which avoids nonspecific signals by contrasting antibody binding signals directly on living cells, with and without recombinant antigen expression. The image cytometry-based high-throughput screening method was optimized by detecting the binding of hybridoma supernatants to the recombinant antigen CD39 expressed on Chinese hamster ovary (CHO) cells. Next, the sensitivity of the image cytometer was demonstrated by serial dilution of purified CD39 antibody. Celigo was used to measure antibody affinities of commercial and in-house antibodies to membrane-bound CD39. This cell-based screening procedure can be completely accomplished within one day, significantly improving throughput and efficiency of hybridoma screening. Furthermore, measuring direct antibody binding to living cells eliminated both false positive and false negative hits. The image cytometry method was highly sensitive and versatile, and could detect positive antibody in supernatants at concentrations as low as ~5ng/mL, with concurrent K d binding affinity coefficient determination. We propose that this screening method will greatly facilitate antibody discovery and screening technologies. Copyright © 2017 Elsevier B.V. All rights reserved.

Hidden discriminative features extraction for supervised high-order time series modeling.

Science.gov (United States)

Nguyen, Ngoc Anh Thi; Yang, Hyung-Jeong; Kim, Sunhee

2016-11-01

In this paper, an orthogonal Tucker-decomposition-based extraction of high-order discriminative subspaces from a tensor-based time series data structure is presented, named as Tensor Discriminative Feature Extraction (TDFE). TDFE relies on the employment of category information for the maximization of the between-class scatter and the minimization of the within-class scatter to extract optimal hidden discriminative feature subspaces that are simultaneously spanned by every modality for supervised tensor modeling. In this context, the proposed tensor-decomposition method provides the following benefits: i) reduces dimensionality while robustly mining the underlying discriminative features, ii) results in effective interpretable features that lead to an improved classification and visualization, and iii) reduces the processing time during the training stage and the filtering of the projection by solving the generalized eigenvalue issue at each alternation step. Two real third-order tensor-structures of time series datasets (an epilepsy electroencephalogram (EEG) that is modeled as channel×frequency bin×time frame and a microarray data that is modeled as gene×sample×time) were used for the evaluation of the TDFE. The experiment results corroborate the advantages of the proposed method with averages of 98.26% and 89.63% for the classification accuracies of the epilepsy dataset and the microarray dataset, respectively. These performance averages represent an improvement on those of the matrix-based algorithms and recent tensor-based, discriminant-decomposition approaches; this is especially the case considering the small number of samples that are used in practice. Copyright © 2016 Elsevier Ltd. All rights reserved.

TCP Throughput Profiles Using Measurements over Dedicated Connections

Energy Technology Data Exchange (ETDEWEB)

Rao, Nageswara S. [ORNL; Liu, Qiang [ORNL; Sen, Satyabrata [ORNL; Towsley, Don [University of Massachusetts, Amherst; Vardoyan, Gayane [University of Massachusetts, Amherst; Kettimuthu, R. [Argonne National Laboratory (ANL); Foster, Ian [University of Chicago

2017-06-01

Wide-area data transfers in high-performance computing infrastructures are increasingly being carried over dynamically provisioned dedicated network connections that provide high capacities with no competing traffic. We present extensive TCP throughput measurements and time traces over a suite of physical and emulated 10 Gbps connections with 0-366 ms round-trip times (RTTs). Contrary to the general expectation, they show significant statistical and temporal variations, in addition to the overall dependencies on the congestion control mechanism, buffer size, and the number of parallel streams. We analyze several throughput profiles that have highly desirable concave regions wherein the throughput decreases slowly with RTTs, in stark contrast to the convex profiles predicted by various TCP analytical models. We present a generic throughput model that abstracts the ramp-up and sustainment phases of TCP flows, which provides insights into qualitative trends observed in measurements across TCP variants: (i) slow-start followed by well-sustained throughput leads to concave regions; (ii) large buffers and multiple parallel streams expand the concave regions in addition to improving the throughput; and (iii) stable throughput dynamics, indicated by a smoother Poincare map and smaller Lyapunov exponents, lead to wider concave regions. These measurements and analytical results together enable us to select a TCP variant and its parameters for a given connection to achieve high throughput with statistical guarantees.

High Throughput Analysis of Photocatalytic Water Purification

NARCIS (Netherlands)

Sobral Romao, J.I.; Baiao Barata, David; Habibovic, Pamela; Mul, Guido; Baltrusaitis, Jonas

2014-01-01

We present a novel high throughput photocatalyst efficiency assessment method based on 96-well microplates and UV-Vis spectroscopy. We demonstrate the reproducibility of the method using methyl orange (MO) decomposition, and compare kinetic data obtained with those provided in the literature for

High Throughput Synthesis and Screening for Agents Inhibiting Androgen Receptor Mediated Gene Transcription

National Research Council Canada - National Science Library

Boger, Dale L

2005-01-01

.... This entails the high throughput synthesis of DNA binding agents related to distamycin, their screening for binding to androgen response elements using a new high throughput DNA binding screen...

High Throughput Synthesis and Screening for Agents Inhibiting Androgen Receptor Mediated Gene Transcription

National Research Council Canada - National Science Library

Boger, Dale

2004-01-01

.... This entails the high throughput synthesis of DNA binding agents related to distamycin, their screening for binding to androgen response elements using a new high throughput DNA binding screen...

Cycle Time and Throughput Rate Modelling Study through the Simulation Platform

Directory of Open Access Journals (Sweden)

Fei Xiong

2014-02-01

Full Text Available The shorter cycle time (CT and higher throughput rate (TH are primary goals of the industry, including sensors and transducer factory. The common way of cycle time reduction is to reduce WIP, but such action may also reduce throughput. This paper will show one practical healthy heuristic algorithm based on tool time modelling to balance both the CT and the TH. This algorithm considers the factors that exist in the work in process (WIP and its constrains in modules of the factory. One computer simulation platform based on a semiconductor factory is built to verify this algorithm. The result of computing simulation experiments suggests that the WIP level calculated by this algorithm can achieve the good balance of CT and TH.

A CRISPR CASe for High-Throughput Silencing

Directory of Open Access Journals (Sweden)

Jacob eHeintze

2013-10-01

Full Text Available Manipulation of gene expression on a genome-wide level is one of the most important systematic tools in the post-genome era. Such manipulations have largely been enabled by expression cloning approaches using sequence-verified cDNA libraries, large-scale RNA interference libraries (shRNA or siRNA and zinc finger nuclease technologies. More recently, the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated (Cas9-mediated gene editing technology has been described that holds great promise for future use of this technology in genomic manipulation. It was suggested that the CRISPR system has the potential to be used in high-throughput, large-scale loss of function screening. Here we discuss some of the challenges in engineering of CRISPR/Cas genomic libraries and some of the aspects that need to be addressed in order to use this technology on a high-throughput scale.

Time series analysis in the social sciences the fundamentals

CERN Document Server

Shin, Youseop

2017-01-01

Times Series Analysis in the Social Sciences is a practical and highly readable introduction written exclusively for students and researchers whose mathematical background is limited to basic algebra. The book focuses on fundamental elements of time series analysis that social scientists need to understand so they can employ time series analysis for their research and practice. Through step-by-step explanations and using monthly violent crime rates as case studies, this book explains univariate time series from the preliminary visual analysis through the modeling of seasonality, trends, and re

Alginate Immobilization of Metabolic Enzymes (AIME) for High-Throughput Screening Assays (SOT)

Science.gov (United States)

Alginate Immobilization of Metabolic Enzymes (AIME) for High-Throughput Screening Assays DE DeGroot, RS Thomas, and SO SimmonsNational Center for Computational Toxicology, US EPA, Research Triangle Park, NC USAThe EPA’s ToxCast program utilizes a wide variety of high-throughput s...

High-throughput phenotyping and genomic selection: the frontiers of crop breeding converge.

Science.gov (United States)

Cabrera-Bosquet, Llorenç; Crossa, José; von Zitzewitz, Jarislav; Serret, María Dolors; Araus, José Luis

2012-05-01

Genomic selection (GS) and high-throughput phenotyping have recently been captivating the interest of the crop breeding community from both the public and private sectors world-wide. Both approaches promise to revolutionize the prediction of complex traits, including growth, yield and adaptation to stress. Whereas high-throughput phenotyping may help to improve understanding of crop physiology, most powerful techniques for high-throughput field phenotyping are empirical rather than analytical and comparable to genomic selection. Despite the fact that the two methodological approaches represent the extremes of what is understood as the breeding process (phenotype versus genome), they both consider the targeted traits (e.g. grain yield, growth, phenology, plant adaptation to stress) as a black box instead of dissecting them as a set of secondary traits (i.e. physiological) putatively related to the target trait. Both GS and high-throughput phenotyping have in common their empirical approach enabling breeders to use genome profile or phenotype without understanding the underlying biology. This short review discusses the main aspects of both approaches and focuses on the case of genomic selection of maize flowering traits and near-infrared spectroscopy (NIRS) and plant spectral reflectance as high-throughput field phenotyping methods for complex traits such as crop growth and yield. © 2012 Institute of Botany, Chinese Academy of Sciences.

HTTK: R Package for High-Throughput Toxicokinetics

Science.gov (United States)

Thousands of chemicals have been profiled by high-throughput screening programs such as ToxCast and Tox21; these chemicals are tested in part because most of them have limited or no data on hazard, exposure, or toxicokinetics. Toxicokinetic models aid in predicting tissue concent...

DTW-APPROACH FOR UNCORRELATED MULTIVARIATE TIME SERIES IMPUTATION

OpenAIRE

Phan , Thi-Thu-Hong; Poisson Caillault , Emilie; Bigand , André; Lefebvre , Alain

2017-01-01

International audience; Missing data are inevitable in almost domains of applied sciences. Data analysis with missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Some well-known methods for multivariate time series imputation require high correlations between series or their features. In this paper , we propose an approach based on the shape-behaviour relation in low/un-correlated multivariate time series under an assumption of...

Time series modeling in traffic safety research.

Science.gov (United States)

Lavrenz, Steven M; Vlahogianni, Eleni I; Gkritza, Konstantina; Ke, Yue

2018-08-01

The use of statistical models for analyzing traffic safety (crash) data has been well-established. However, time series techniques have traditionally been underrepresented in the corresponding literature, due to challenges in data collection, along with a limited knowledge of proper methodology. In recent years, new types of high-resolution traffic safety data, especially in measuring driver behavior, have made time series modeling techniques an increasingly salient topic of study. Yet there remains a dearth of information to guide analysts in their use. This paper provides an overview of the state of the art in using time series models in traffic safety research, and discusses some of the fundamental techniques and considerations in classic time series modeling. It also presents ongoing and future opportunities for expanding the use of time series models, and explores newer modeling techniques, including computational intelligence models, which hold promise in effectively handling ever-larger data sets. The information contained herein is meant to guide safety researchers in understanding this broad area of transportation data analysis, and provide a framework for understanding safety trends that can influence policy-making. Copyright © 2017 Elsevier Ltd. All rights reserved.

High-Throughput Process Development for Biopharmaceuticals.

Science.gov (United States)

Shukla, Abhinav A; Rameez, Shahid; Wolfe, Leslie S; Oien, Nathan

2017-11-14

The ability to conduct multiple experiments in parallel significantly reduces the time that it takes to develop a manufacturing process for a biopharmaceutical. This is particularly significant before clinical entry, because process development and manufacturing are on the "critical path" for a drug candidate to enter clinical development. High-throughput process development (HTPD) methodologies can be similarly impactful during late-stage development, both for developing the final commercial process as well as for process characterization and scale-down validation activities that form a key component of the licensure filing package. This review examines the current state of the art for HTPD methodologies as they apply to cell culture, downstream purification, and analytical techniques. In addition, we provide a vision of how HTPD activities across all of these spaces can integrate to create a rapid process development engine that can accelerate biopharmaceutical drug development. Graphical Abstract.

A high throughput mechanical screening device for cartilage tissue engineering.

Science.gov (United States)

Mohanraj, Bhavana; Hou, Chieh; Meloni, Gregory R; Cosgrove, Brian D; Dodge, George R; Mauck, Robert L

2014-06-27

Articular cartilage enables efficient and near-frictionless load transmission, but suffers from poor inherent healing capacity. As such, cartilage tissue engineering strategies have focused on mimicking both compositional and mechanical properties of native tissue in order to provide effective repair materials for the treatment of damaged or degenerated joint surfaces. However, given the large number design parameters available (e.g. cell sources, scaffold designs, and growth factors), it is difficult to conduct combinatorial experiments of engineered cartilage. This is particularly exacerbated when mechanical properties are a primary outcome, given the long time required for testing of individual samples. High throughput screening is utilized widely in the pharmaceutical industry to rapidly and cost-effectively assess the effects of thousands of compounds for therapeutic discovery. Here we adapted this approach to develop a high throughput mechanical screening (HTMS) system capable of measuring the mechanical properties of up to 48 materials simultaneously. The HTMS device was validated by testing various biomaterials and engineered cartilage constructs and by comparing the HTMS results to those derived from conventional single sample compression tests. Further evaluation showed that the HTMS system was capable of distinguishing and identifying 'hits', or factors that influence the degree of tissue maturation. Future iterations of this device will focus on reducing data variability, increasing force sensitivity and range, as well as scaling-up to even larger (96-well) formats. This HTMS device provides a novel tool for cartilage tissue engineering, freeing experimental design from the limitations of mechanical testing throughput. © 2013 Published by Elsevier Ltd.

Duality between Time Series and Networks

Science.gov (United States)

Campanharo, Andriana S. L. O.; Sirer, M. Irmak; Malmgren, R. Dean; Ramos, Fernando M.; Amaral, Luís A. Nunes.

2011-01-01

Studying the interaction between a system's components and the temporal evolution of the system are two common ways to uncover and characterize its internal workings. Recently, several maps from a time series to a network have been proposed with the intent of using network metrics to characterize time series. Although these maps demonstrate that different time series result in networks with distinct topological properties, it remains unclear how these topological properties relate to the original time series. Here, we propose a map from a time series to a network with an approximate inverse operation, making it possible to use network statistics to characterize time series and time series statistics to characterize networks. As a proof of concept, we generate an ensemble of time series ranging from periodic to random and confirm that application of the proposed map retains much of the information encoded in the original time series (or networks) after application of the map (or its inverse). Our results suggest that network analysis can be used to distinguish different dynamic regimes in time series and, perhaps more importantly, time series analysis can provide a powerful set of tools that augment the traditional network analysis toolkit to quantify networks in new and useful ways. PMID:21858093

Robust Forecasting of Non-Stationary Time Series

OpenAIRE

Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.

2010-01-01

This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable forecasts in the presence of outliers, non-linearity, and heteroscedasticity. In the absence of outliers, the forecasts are only slightly less precise than those based on a localized Least Squares estima...

A high-throughput screening system for barley/powdery mildew interactions based on automated analysis of light micrographs.

Science.gov (United States)

Ihlow, Alexander; Schweizer, Patrick; Seiffert, Udo

2008-01-23

To find candidate genes that potentially influence the susceptibility or resistance of crop plants to powdery mildew fungi, an assay system based on transient-induced gene silencing (TIGS) as well as transient over-expression in single epidermal cells of barley has been developed. However, this system relies on quantitative microscopic analysis of the barley/powdery mildew interaction and will only become a high-throughput tool of phenomics upon automation of the most time-consuming steps. We have developed a high-throughput screening system based on a motorized microscope which evaluates the specimens fully automatically. A large-scale double-blind verification of the system showed an excellent agreement of manual and automated analysis and proved the system to work dependably. Furthermore, in a series of bombardment experiments an RNAi construct targeting the Mlo gene was included, which is expected to phenocopy resistance mediated by recessive loss-of-function alleles such as mlo5. In most cases, the automated analysis system recorded a shift towards resistance upon RNAi of Mlo, thus providing proof of concept for its usefulness in detecting gene-target effects. Besides saving labor and enabling a screening of thousands of candidate genes, this system offers continuous operation of expensive laboratory equipment and provides a less subjective analysis as well as a complete and enduring documentation of the experimental raw data in terms of digital images. In general, it proves the concept of enabling available microscope hardware to handle challenging screening tasks fully automatically.

Large-scale DNA Barcode Library Generation for Biomolecule Identification in High-throughput Screens.

Science.gov (United States)

Lyons, Eli; Sheridan, Paul; Tremmel, Georg; Miyano, Satoru; Sugano, Sumio

2017-10-24

High-throughput screens allow for the identification of specific biomolecules with characteristics of interest. In barcoded screens, DNA barcodes are linked to target biomolecules in a manner allowing for the target molecules making up a library to be identified by sequencing the DNA barcodes using Next Generation Sequencing. To be useful in experimental settings, the DNA barcodes in a library must satisfy certain constraints related to GC content, homopolymer length, Hamming distance, and blacklisted subsequences. Here we report a novel framework to quickly generate large-scale libraries of DNA barcodes for use in high-throughput screens. We show that our framework dramatically reduces the computation time required to generate large-scale DNA barcode libraries, compared with a naїve approach to DNA barcode library generation. As a proof of concept, we demonstrate that our framework is able to generate a library consisting of one million DNA barcodes for use in a fragment antibody phage display screening experiment. We also report generating a general purpose one billion DNA barcode library, the largest such library yet reported in literature. Our results demonstrate the value of our novel large-scale DNA barcode library generation framework for use in high-throughput screening applications.

Long time series

DEFF Research Database (Denmark)

Hisdal, H.; Holmqvist, E.; Hyvärinen, V.

Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the......Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the...

Life in the fast lane: high-throughput chemistry for lead generation and optimisation.

Science.gov (United States)

Hunter, D

2001-01-01

The pharmaceutical industry has come under increasing pressure due to regulatory restrictions on the marketing and pricing of drugs, competition, and the escalating costs of developing new drugs. These forces can be addressed by the identification of novel targets, reductions in the development time of new drugs, and increased productivity. Emphasis has been placed on identifying and validating new targets and on lead generation: the response from industry has been very evident in genomics and high throughput screening, where new technologies have been applied, usually coupled with a high degree of automation. The combination of numerous new potential biological targets and the ability to screen large numbers of compounds against many of these targets has generated the need for large diverse compound collections. To address this requirement, high-throughput chemistry has become an integral part of the drug discovery process. Copyright 2002 Wiley-Liss, Inc.

Modeling Time Series Data for Supervised Learning

Science.gov (United States)

Baydogan, Mustafa Gokce

2012-01-01

Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…

A robust robotic high-throughput antibody purification platform.

Science.gov (United States)

Schmidt, Peter M; Abdo, Michael; Butcher, Rebecca E; Yap, Min-Yin; Scotney, Pierre D; Ramunno, Melanie L; Martin-Roussety, Genevieve; Owczarek, Catherine; Hardy, Matthew P; Chen, Chao-Guang; Fabri, Louis J

2016-07-15

Monoclonal antibodies (mAbs) have become the fastest growing segment in the drug market with annual sales of more than 40 billion US$ in 2013. The selection of lead candidate molecules involves the generation of large repertoires of antibodies from which to choose a final therapeutic candidate. Improvements in the ability to rapidly produce and purify many antibodies in sufficient quantities reduces the lead time for selection which ultimately impacts on the speed with which an antibody may transition through the research stage and into product development. Miniaturization and automation of chromatography using micro columns (RoboColumns(®) from Atoll GmbH) coupled to an automated liquid handling instrument (ALH; Freedom EVO(®) from Tecan) has been a successful approach to establish high throughput process development platforms. Recent advances in transient gene expression (TGE) using the high-titre Expi293F™ system have enabled recombinant mAb titres of greater than 500mg/L. These relatively high protein titres reduce the volume required to generate several milligrams of individual antibodies for initial biochemical and biological downstream assays, making TGE in the Expi293F™ system ideally suited to high throughput chromatography on an ALH. The present publication describes a novel platform for purifying Expi293F™-expressed recombinant mAbs directly from cell-free culture supernatant on a Perkin Elmer JANUS-VariSpan ALH equipped with a plate shuttle device. The purification platform allows automated 2-step purification (Protein A-desalting/size exclusion chromatography) of several hundred mAbs per week. The new robotic method can purify mAbs with high recovery (>90%) at sub-milligram level with yields of up to 2mg from 4mL of cell-free culture supernatant. Copyright © 2016 Elsevier B.V. All rights reserved.

High throughput protein production screening

Science.gov (United States)

Beernink, Peter T [Walnut Creek, CA; Coleman, Matthew A [Oakland, CA; Segelke, Brent W [San Ramon, CA

2009-09-08

Methods, compositions, and kits for the cell-free production and analysis of proteins are provided. The invention allows for the production of proteins from prokaryotic sequences or eukaryotic sequences, including human cDNAs using PCR and IVT methods and detecting the proteins through fluorescence or immunoblot techniques. This invention can be used to identify optimized PCR and WT conditions, codon usages and mutations. The methods are readily automated and can be used for high throughput analysis of protein expression levels, interactions, and functional states.

High throughput production of mouse monoclonal antibodies using antigen microarrays

DEFF Research Database (Denmark)

De Masi, Federico; Chiarella, P.; Wilhelm, H.

2005-01-01

Recent advances in proteomics research underscore the increasing need for high-affinity monoclonal antibodies, which are still generated with lengthy, low-throughput antibody production techniques. Here we present a semi-automated, high-throughput method of hybridoma generation and identification....... Monoclonal antibodies were raised to different targets in single batch runs of 6-10 wk using multiplexed immunisations, automated fusion and cell-culture, and a novel antigen-coated microarray-screening assay. In a large-scale experiment, where eight mice were immunized with ten antigens each, we generated...

A Course in Time Series Analysis

CERN Document Server

Peña, Daniel; Tsay, Ruey S

2011-01-01

New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, a

Label-free detection of cellular drug responses by high-throughput bright-field imaging and machine learning.

Science.gov (United States)

Kobayashi, Hirofumi; Lei, Cheng; Wu, Yi; Mao, Ailin; Jiang, Yiyue; Guo, Baoshan; Ozeki, Yasuyuki; Goda, Keisuke

2017-09-29

In the last decade, high-content screening based on multivariate single-cell imaging has been proven effective in drug discovery to evaluate drug-induced phenotypic variations. Unfortunately, this method inherently requires fluorescent labeling which has several drawbacks. Here we present a label-free method for evaluating cellular drug responses only by high-throughput bright-field imaging with the aid of machine learning algorithms. Specifically, we performed high-throughput bright-field imaging of numerous drug-treated and -untreated cells (N = ~240,000) by optofluidic time-stretch microscopy with high throughput up to 10,000 cells/s and applied machine learning to the cell images to identify their morphological variations which are too subtle for human eyes to detect. Consequently, we achieved a high accuracy of 92% in distinguishing drug-treated and -untreated cells without the need for labeling. Furthermore, we also demonstrated that dose-dependent, drug-induced morphological change from different experiments can be inferred from the classification accuracy of a single classification model. Our work lays the groundwork for label-free drug screening in pharmaceutical science and industry.

Efficient production of a gene mutant cell line through integrating TALENs and high-throughput cell cloning.

Science.gov (United States)

Sun, Changhong; Fan, Yu; Li, Juan; Wang, Gancheng; Zhang, Hanshuo; Xi, Jianzhong Jeff

2015-02-01

Transcription activator-like effectors (TALEs) are becoming powerful DNA-targeting tools in a variety of mammalian cells and model organisms. However, generating a stable cell line with specific gene mutations in a simple and rapid manner remains a challenging task. Here, we report a new method to efficiently produce monoclonal cells using integrated TALE nuclease technology and a series of high-throughput cell cloning approaches. Following this method, we obtained three mTOR mutant 293T cell lines within 2 months, which included one homozygous mutant line. © 2014 Society for Laboratory Automation and Screening.

Liquid-phase sample preparation method for real-time monitoring of airborne asbestos fibers by dual-mode high-throughput microscopy.

Science.gov (United States)

Cho, Myoung-Ock; Kim, Jung Kyung; Han, Hwataik; Lee, Jeonghoon

2013-01-01

Asbestos that had been used widely as a construction material is a first-level carcinogen recognized by the World Health Organization. It can be accumulated in body by inhalation causing virulent respiratory diseases including lung cancer. In our previous study, we developed a high-throughput microscopy (HTM) system that can minimize human intervention accompanied by the conventional phase contrast microscopy (PCM) through automated counting of fibrous materials and thus significantly reduce analysis time and labor. Also, we attempted selective detection of chrysotile using DksA protein extracted from Escherichia coli through a recombinant protein production technique, and developed a dual-mode HTM (DM-HTM) by upgrading the HTM device. We demonstrated that fluorescently-labeled chrysotile asbestos fibers can be identified and enumerated automatically among other types of asbestos fibers or non-asbestos particles in a high-throughput manner through a newly modified HTM system for both reflection and fluorescence imaging. However there is a limitation to apply DM-HTM to airborne sample with current air collecting method due to the difficulty of applying the protein to dried asbestos sample. Here, we developed a technique for preparing liquid-phase asbestos sample using an impinger normally used to collect odor molecules in the air. It would be possible to improve the feasibility of the dual-mode HTM by integrating a sample preparation unit for making collected asbestos sample dispersed in a solution. The new technique developed for highly sensitive and automated asbestos detection can be a potential alternative to the conventional manual counting method, and it may be applied on site as a fast and reliable environmental monitoring tool.

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance.

Science.gov (United States)

Liu, Yongli; Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy.

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance

Science.gov (United States)

Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy. PMID:29795600

Stochastic nature of series of waiting times

Science.gov (United States)

Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H.; Salehi, E.; Behjat, E.; Qorbani, M.; Khazaei Nezhad, M.; Zirak, M.; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M. Reza Rahimi

2013-06-01

Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the “waiting times” series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2time distribution. We find that the logarithmic difference of waiting times series has a short-range correlation, and then we study its stochastic nature using the Markovian method and determine the corresponding Kramers-Moyal coefficients. As an example, we analyze the velocity fluctuations in high Reynolds number turbulence and determine the level dependence of Markov time scales, as well as the drift and diffusion coefficients. We show that the waiting time distributions exhibit power law tails, and we were able to model the distribution with a continuous time random walk.

Introduction to time series analysis and forecasting

CERN Document Server

Montgomery, Douglas C; Kulahci, Murat

2015-01-01

Praise for the First Edition ""…[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics."" -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts.    Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both

Multiple and high-throughput droplet reactions via combination of microsampling technique and microfluidic chip

KAUST Repository

Wu, Jinbo

2012-11-20

Microdroplets offer unique compartments for accommodating a large number of chemical and biological reactions in tiny volume with precise control. A major concern in droplet-based microfluidics is the difficulty to address droplets individually and achieve high throughput at the same time. Here, we have combined an improved cartridge sampling technique with a microfluidic chip to perform droplet screenings and aggressive reaction with minimal (nanoliter-scale) reagent consumption. The droplet composition, distance, volume (nanoliter to subnanoliter scale), number, and sequence could be precisely and digitally programmed through the improved sampling technique, while sample evaporation and cross-contamination are effectively eliminated. Our combined device provides a simple model to utilize multiple droplets for various reactions with low reagent consumption and high throughput. © 2012 American Chemical Society.

Kolmogorov Space in Time Series Data

OpenAIRE

Kanjamapornkul, K.; Pinčák, R.

2016-01-01

We provide the proof that the space of time series data is a Kolmogorov space with $T_{0}$-separation axiom using the loop space of time series data. In our approach we define a cyclic coordinate of intrinsic time scale of time series data after empirical mode decomposition. A spinor field of time series data comes from the rotation of data around price and time axis by defining a new extradimension to time series data. We show that there exist hidden eight dimensions in Kolmogorov space for ...

Filtering high-throughput protein-protein interaction data using a combination of genomic features

Directory of Open Access Journals (Sweden)

Patil Ashwini

2005-04-01

Full Text Available Abstract Background Protein-protein interaction data used in the creation or prediction of molecular networks is usually obtained from large scale or high-throughput experiments. This experimental data is liable to contain a large number of spurious interactions. Hence, there is a need to validate the interactions and filter out the incorrect data before using them in prediction studies. Results In this study, we use a combination of 3 genomic features – structurally known interacting Pfam domains, Gene Ontology annotations and sequence homology – as a means to assign reliability to the protein-protein interactions in Saccharomyces cerevisiae determined by high-throughput experiments. Using Bayesian network approaches, we show that protein-protein interactions from high-throughput data supported by one or more genomic features have a higher likelihood ratio and hence are more likely to be real interactions. Our method has a high sensitivity (90% and good specificity (63%. We show that 56% of the interactions from high-throughput experiments in Saccharomyces cerevisiae have high reliability. We use the method to estimate the number of true interactions in the high-throughput protein-protein interaction data sets in Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens to be 27%, 18% and 68% respectively. Our results are available for searching and downloading at http://helix.protein.osaka-u.ac.jp/htp/. Conclusion A combination of genomic features that include sequence, structure and annotation information is a good predictor of true interactions in large and noisy high-throughput data sets. The method has a very high sensitivity and good specificity and can be used to assign a likelihood ratio, corresponding to the reliability, to each interaction.

On the Use of Running Trends as Summary Statistics for Univariate Time Series and Time Series Association

OpenAIRE

Trottini, Mario; Vigo, Isabel; Belda, Santiago

2015-01-01

Given a time series, running trends analysis (RTA) involves evaluating least squares trends over overlapping time windows of L consecutive time points, with overlap by all but one observation. This produces a new series called the “running trends series,” which is used as summary statistics of the original series for further analysis. In recent years, RTA has been widely used in climate applied research as summary statistics for time series and time series association. There is no doubt that ...

Meeting Report: High-Throughput Technologies for In Vivo Imaging Agents

Directory of Open Access Journals (Sweden)

Robert J. Gillies

2005-04-01

Full Text Available Combinatorial chemistry and high-throughput screening have become standard tools for discovering new drug candidates with suitable pharmacological properties. Now, those same technologies are starting to be applied to the problem of discovering novel in vivo imaging agents. Important differences in the biological and pharmacological properties needed for imaging agents, compared to those for a therapeutic agent, require new screening methods that emphasize those characteristics, such as optimized residence time and tissue specificity, that make for a good imaging agent candidate.

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

Science.gov (United States)

Hensman, James; Lawrence, Neil D; Rattray, Magnus

2013-08-20

Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/.

Mathematical Modeling and Dynamic Simulation of Metabolic Reaction Systems Using Metabolome Time Series Data

Directory of Open Access Journals (Sweden)

Kansuporn eSriyudthsak

2016-05-01

Full Text Available The high-throughput acquisition of metabolome data is greatly anticipated for the complete understanding of cellular metabolism in living organisms. A variety of analytical technologies have been developed to acquire large-scale metabolic profiles under different biological or environmental conditions. Time series data are useful for predicting the most likely metabolic pathways because they provide important information regarding the accumulation of metabolites, which implies causal relationships in the metabolic reaction network. Considerable effort has been undertaken to utilize these data for constructing a mathematical model merging system properties and quantitatively characterizing a whole metabolic system in toto. However, there are technical difficulties between benchmarking the provision and utilization of data. Although hundreds of metabolites can be measured, which provide information on the metabolic reaction system, simultaneous measurement of thousands of metabolites is still challenging. In addition, it is nontrivial to logically predict the dynamic behaviors of unmeasurable metabolite concentrations without sufficient information on the metabolic reaction network. Yet, consolidating the advantages of advancements in both metabolomics and mathematical modeling remain to be accomplished. This review outlines the conceptual basis of and recent advances in technologies in both the research fields. It also highlights the potential for constructing a large-scale mathematical model by estimating model parameters from time series metabolome data in order to comprehensively understand metabolism at the systems level.

Mathematical Modeling and Dynamic Simulation of Metabolic Reaction Systems Using Metabolome Time Series Data.

Science.gov (United States)

Sriyudthsak, Kansuporn; Shiraishi, Fumihide; Hirai, Masami Yokota

2016-01-01

The high-throughput acquisition of metabolome data is greatly anticipated for the complete understanding of cellular metabolism in living organisms. A variety of analytical technologies have been developed to acquire large-scale metabolic profiles under different biological or environmental conditions. Time series data are useful for predicting the most likely metabolic pathways because they provide important information regarding the accumulation of metabolites, which implies causal relationships in the metabolic reaction network. Considerable effort has been undertaken to utilize these data for constructing a mathematical model merging system properties and quantitatively characterizing a whole metabolic system in toto. However, there are technical difficulties between benchmarking the provision and utilization of data. Although, hundreds of metabolites can be measured, which provide information on the metabolic reaction system, simultaneous measurement of thousands of metabolites is still challenging. In addition, it is nontrivial to logically predict the dynamic behaviors of unmeasurable metabolite concentrations without sufficient information on the metabolic reaction network. Yet, consolidating the advantages of advancements in both metabolomics and mathematical modeling remain to be accomplished. This review outlines the conceptual basis of and recent advances in technologies in both the research fields. It also highlights the potential for constructing a large-scale mathematical model by estimating model parameters from time series metabolome data in order to comprehensively understand metabolism at the systems level.

Multiple Indicator Stationary Time Series Models.

Science.gov (United States)

Sivo, Stephen A.

2001-01-01

Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

MIPHENO: Data normalization for high throughput metabolic analysis.

Science.gov (United States)

High throughput methodologies such as microarrays, mass spectrometry and plate-based small molecule screens are increasingly used to facilitate discoveries from gene function to drug candidate identification. These large-scale experiments are typically carried out over the course...

Identifying Inhibitors of Inflammation: A Novel High-Throughput MALDI-TOF Screening Assay for Salt-Inducible Kinases (SIKs).

Science.gov (United States)

Heap, Rachel E; Hope, Anthony G; Pearson, Lesley-Anne; Reyskens, Kathleen M S E; McElroy, Stuart P; Hastie, C James; Porter, David W; Arthur, J Simon C; Gray, David W; Trost, Matthias

2017-12-01

Matrix-assisted laser desorption/ionization time-of-flight (MALDI TOF) mass spectrometry has become a promising alternative for high-throughput drug discovery as new instruments offer high speed, flexibility and sensitivity, and the ability to measure physiological substrates label free. Here we developed and applied high-throughput MALDI TOF mass spectrometry to identify inhibitors of the salt-inducible kinase (SIK) family, which are interesting drug targets in the field of inflammatory disease as they control production of the anti-inflammatory cytokine interleukin-10 (IL-10) in macrophages. Using peptide substrates in in vitro kinase assays, we can show that hit identification of the MALDI TOF kinase assay correlates with indirect ADP-Hunter kinase assays. Moreover, we can show that both techniques generate comparable IC 50 data for a number of hit compounds and known inhibitors of SIK kinases. We further take these inhibitors to a fluorescence-based cellular assay using the SIK activity-dependent translocation of CRTC3 into the nucleus, thereby providing a complete assay pipeline for the identification of SIK kinase inhibitors in vitro and in cells. Our data demonstrate that MALDI TOF mass spectrometry is fully applicable to high-throughput kinase screening, providing label-free data comparable to that of current high-throughput fluorescence assays.

Inertial Microfluidic Cell Stretcher (iMCS): Fully Automated, High-Throughput, and Near Real-Time Cell Mechanotyping.

Science.gov (United States)

Deng, Yanxiang; Davis, Steven P; Yang, Fan; Paulsen, Kevin S; Kumar, Maneesh; Sinnott DeVaux, Rebecca; Wang, Xianhui; Conklin, Douglas S; Oberai, Assad; Herschkowitz, Jason I; Chung, Aram J

2017-07-01

Mechanical biomarkers associated with cytoskeletal structures have been reported as powerful label-free cell state identifiers. In order to measure cell mechanical properties, traditional biophysical (e.g., atomic force microscopy, micropipette aspiration, optical stretchers) and microfluidic approaches were mainly employed; however, they critically suffer from low-throughput, low-sensitivity, and/or time-consuming and labor-intensive processes, not allowing techniques to be practically used for cell biology research applications. Here, a novel inertial microfluidic cell stretcher (iMCS) capable of characterizing large populations of single-cell deformability near real-time is presented. The platform inertially controls cell positions in microchannels and deforms cells upon collision at a T-junction with large strain. The cell elongation motions are recorded, and thousands of cell deformability information is visualized near real-time similar to traditional flow cytometry. With a full automation, the entire cell mechanotyping process runs without any human intervention, realizing a user friendly and robust operation. Through iMCS, distinct cell stiffness changes in breast cancer progression and epithelial mesenchymal transition are reported, and the use of the platform for rapid cancer drug discovery is shown as well. The platform returns large populations of single-cell quantitative mechanical properties (e.g., shear modulus) on-the-fly with high statistical significances, enabling actual usages in clinical and biophysical studies. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High-Throughput Thermodynamic Modeling and Uncertainty Quantification for ICME

Science.gov (United States)

Otis, Richard A.; Liu, Zi-Kui

2017-05-01

One foundational component of the integrated computational materials engineering (ICME) and Materials Genome Initiative is the computational thermodynamics based on the calculation of phase diagrams (CALPHAD) method. The CALPHAD method pioneered by Kaufman has enabled the development of thermodynamic, atomic mobility, and molar volume databases of individual phases in the full space of temperature, composition, and sometimes pressure for technologically important multicomponent engineering materials, along with sophisticated computational tools for using the databases. In this article, our recent efforts will be presented in terms of developing new computational tools for high-throughput modeling and uncertainty quantification based on high-throughput, first-principles calculations and the CALPHAD method along with their potential propagations to downstream ICME modeling and simulations.

Controlling high-throughput manufacturing at the nano-scale

Science.gov (United States)

Cooper, Khershed P.

2013-09-01

Interest in nano-scale manufacturing research and development is growing. The reason is to accelerate the translation of discoveries and inventions of nanoscience and nanotechnology into products that would benefit industry, economy and society. Ongoing research in nanomanufacturing is focused primarily on developing novel nanofabrication techniques for a variety of applications—materials, energy, electronics, photonics, biomedical, etc. Our goal is to foster the development of high-throughput methods of fabricating nano-enabled products. Large-area parallel processing and highspeed continuous processing are high-throughput means for mass production. An example of large-area processing is step-and-repeat nanoimprinting, by which nanostructures are reproduced again and again over a large area, such as a 12 in wafer. Roll-to-roll processing is an example of continuous processing, by which it is possible to print and imprint multi-level nanostructures and nanodevices on a moving flexible substrate. The big pay-off is high-volume production and low unit cost. However, the anticipated cost benefits can only be realized if the increased production rate is accompanied by high yields of high quality products. To ensure product quality, we need to design and construct manufacturing systems such that the processes can be closely monitored and controlled. One approach is to bring cyber-physical systems (CPS) concepts to nanomanufacturing. CPS involves the control of a physical system such as manufacturing through modeling, computation, communication and control. Such a closely coupled system will involve in-situ metrology and closed-loop control of the physical processes guided by physics-based models and driven by appropriate instrumentation, sensing and actuation. This paper will discuss these ideas in the context of controlling high-throughput manufacturing at the nano-scale.

Automated profiling of individual cell-cell interactions from high-throughput time-lapse imaging microscopy in nanowell grids (TIMING).

Science.gov (United States)

Merouane, Amine; Rey-Villamizar, Nicolas; Lu, Yanbin; Liadi, Ivan; Romain, Gabrielle; Lu, Jennifer; Singh, Harjeet; Cooper, Laurence J N; Varadarajan, Navin; Roysam, Badrinath

2015-10-01

There is a need for effective automated methods for profiling dynamic cell-cell interactions with single-cell resolution from high-throughput time-lapse imaging data, especially, the interactions between immune effector cells and tumor cells in adoptive immunotherapy. Fluorescently labeled human T cells, natural killer cells (NK), and various target cells (NALM6, K562, EL4) were co-incubated on polydimethylsiloxane arrays of sub-nanoliter wells (nanowells), and imaged using multi-channel time-lapse microscopy. The proposed cell segmentation and tracking algorithms account for cell variability and exploit the nanowell confinement property to increase the yield of correctly analyzed nanowells from 45% (existing algorithms) to 98% for wells containing one effector and a single target, enabling automated quantification of cell locations, morphologies, movements, interactions, and deaths without the need for manual proofreading. Automated analysis of recordings from 12 different experiments demonstrated automated nanowell delineation accuracy >99%, automated cell segmentation accuracy >95%, and automated cell tracking accuracy of 90%, with default parameters, despite variations in illumination, staining, imaging noise, cell morphology, and cell clustering. An example analysis revealed that NK cells efficiently discriminate between live and dead targets by altering the duration of conjugation. The data also demonstrated that cytotoxic cells display higher motility than non-killers, both before and during contact. broysam@central.uh.edu or nvaradar@central.uh.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Quantitative high throughput analytics to support polysaccharide production process development.

Science.gov (United States)

Noyes, Aaron; Godavarti, Ranga; Titchener-Hooker, Nigel; Coffman, Jonathan; Mukhopadhyay, Tarit

2014-05-19

The rapid development of purification processes for polysaccharide vaccines is constrained by a lack of analytical tools current technologies for the measurement of polysaccharide recovery and process-related impurity clearance are complex, time-consuming, and generally not amenable to high throughput process development (HTPD). HTPD is envisioned to be central to the improvement of existing polysaccharide manufacturing processes through the identification of critical process parameters that potentially impact the quality attributes of the vaccine and to the development of de novo processes for clinical candidates, across the spectrum of downstream processing. The availability of a fast and automated analytics platform will expand the scope, robustness, and evolution of Design of Experiment (DOE) studies. This paper details recent advances in improving the speed, throughput, and success of in-process analytics at the micro-scale. Two methods, based on modifications of existing procedures, are described for the rapid measurement of polysaccharide titre in microplates without the need for heating steps. A simplification of a commercial endotoxin assay is also described that features a single measurement at room temperature. These assays, along with existing assays for protein and nucleic acids are qualified for deployment in the high throughput screening of polysaccharide feedstreams. Assay accuracy, precision, robustness, interference, and ease of use are assessed and described. In combination, these assays are capable of measuring the product concentration and impurity profile of a microplate of 96 samples in less than one day. This body of work relies on the evaluation of a combination of commercially available and clinically relevant polysaccharides to ensure maximum versatility and reactivity of the final assay suite. Together, these advancements reduce overall process time by up to 30-fold and significantly reduce sample volume over current practices. The

High-Throughput Analysis and Automation for Glycomics Studies

NARCIS (Netherlands)

Shubhakar, A.; Reiding, K.R.; Gardner, R.A.; Spencer, D.I.R.; Fernandes, D.L.; Wuhrer, M.

2015-01-01

This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glycosylation to support biopharmaceutical realization and the discovery of glycan biomarkers for human disease. For biopharmaceuticals, there is increasing

High-Throughput Cloning and Expression Library Creation for Functional Proteomics

Science.gov (United States)

Festa, Fernanda; Steel, Jason; Bian, Xiaofang; Labaer, Joshua

2013-01-01

The study of protein function usually requires the use of a cloned version of the gene for protein expression and functional assays. This strategy is particular important when the information available regarding function is limited. The functional characterization of the thousands of newly identified proteins revealed by genomics requires faster methods than traditional single gene experiments, creating the need for fast, flexible and reliable cloning systems. These collections of open reading frame (ORF) clones can be coupled with high-throughput proteomics platforms, such as protein microarrays and cell-based assays, to answer biological questions. In this tutorial we provide the background for DNA cloning, discuss the major high-throughput cloning systems (Gateway® Technology, Flexi® Vector Systems, and Creator™ DNA Cloning System) and compare them side-by-side. We also report an example of high-throughput cloning study and its application in functional proteomics. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP12). Details can be found at http://www.proteomicstutorials.org. PMID:23457047

Time Series Momentum

DEFF Research Database (Denmark)

Moskowitz, Tobias J.; Ooi, Yao Hua; Heje Pedersen, Lasse

2012-01-01

We document significant “time series momentum” in equity index, currency, commodity, and bond futures for each of the 58 liquid instruments we consider. We find persistence in returns for one to 12 months that partially reverses over longer horizons, consistent with sentiment theories of initial...... under-reaction and delayed over-reaction. A diversified portfolio of time series momentum strategies across all asset classes delivers substantial abnormal returns with little exposure to standard asset pricing factors and performs best during extreme markets. Examining the trading activities...

High-throughput bioinformatics with the Cyrille2 pipeline system

Directory of Open Access Journals (Sweden)

de Groot Joost CW

2008-02-01

Full Text Available Abstract Background Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses are often interdependent and chained together to form complex workflows or pipelines. Given the volume of the data used and the multitude of computational resources available, specialized pipeline software is required to make high-throughput analysis of large-scale omics datasets feasible. Results We have developed a generic pipeline system called Cyrille2. The system is modular in design and consists of three functionally distinct parts: 1 a web based, graphical user interface (GUI that enables a pipeline operator to manage the system; 2 the Scheduler, which forms the functional core of the system and which tracks what data enters the system and determines what jobs must be scheduled for execution, and; 3 the Executor, which searches for scheduled jobs and executes these on a compute cluster. Conclusion The Cyrille2 system is an extensible, modular system, implementing the stated requirements. Cyrille2 enables easy creation and execution of high throughput, flexible bioinformatics pipelines.

High throughput screening of phenoxy carboxylic acids with dispersive solid phase extraction followed by direct analysis in real time mass spectrometry.

Science.gov (United States)

Wang, Jiaqin; Zhu, Jun; Si, Ling; Du, Qi; Li, Hongli; Bi, Wentao; Chen, David Da Yong

2017-12-15

A high throughput, low environmental impact methodology for rapid determination of phenoxy carboxylic acids (PCAs) in water samples was developed by combing dispersive solid phase extraction (DSPE) using velvet-like graphitic carbon nitride (V-g-C 3 N 4 ) and direct analysis in real time mass spectrometry (DART-MS). Due to the large surface area and good dispersity of V-g-C 3 N 4 , the DSPE of PCAs in water was completed within 20 s, and the elution of PCAs was accomplished in 20 s as well using methanol. The eluents were then analyzed and quantified using DART ionization source coupled to a high resolution mass spectrometer, where an internal standard was added in the samples. The limit of detection ranged from 0.5 ng L -1 to 2 ng L -1 on the basis of 50 mL water sample; the recovery 79.9-119.1%; and the relative standard deviation 0.23%-9.82% (≥5 replicates). With the ease of use and speed of DART-MS, the whole protocol can complete within mere minutes, including sample preparation, extraction, elution, detection and quantitation. The methodology developed here is simple, fast, sensitive, quantitative, requiring little sample preparation and consuming significantly less toxic organic solvent, which can be used for high throughput screening of PCAs and potentially other contaminants in water. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of a high-throughput microscale cell disruption platform for Pichia pastoris in rapid bioprocess design.

Science.gov (United States)

Bláha, Benjamin A F; Morris, Stephen A; Ogonah, Olotu W; Maucourant, Sophie; Crescente, Vincenzo; Rosenberg, William; Mukhopadhyay, Tarit K

2018-01-01

The time and cost benefits of miniaturized fermentation platforms can only be gained by employing complementary techniques facilitating high-throughput at small sample volumes. Microbial cell disruption is a major bottleneck in experimental throughput and is often restricted to large processing volumes. Moreover, for rigid yeast species, such as Pichia pastoris, no effective high-throughput disruption methods exist. The development of an automated, miniaturized, high-throughput, noncontact, scalable platform based on adaptive focused acoustics (AFA) to disrupt P. pastoris and recover intracellular heterologous protein is described. Augmented modes of AFA were established by investigating vessel designs and a novel enzymatic pretreatment step. Three different modes of AFA were studied and compared to the performance high-pressure homogenization. For each of these modes of cell disruption, response models were developed to account for five different performance criteria. Using multiple responses not only demonstrated that different operating parameters are required for different response optima, with highest product purity requiring suboptimal values for other criteria, but also allowed for AFA-based methods to mimic large-scale homogenization processes. These results demonstrate that AFA-mediated cell disruption can be used for a wide range of applications including buffer development, strain selection, fermentation process development, and whole bioprocess integration. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 34:130-140, 2018. © 2017 American Institute of Chemical Engineers.

HTP-OligoDesigner: An Online Primer Design Tool for High-Throughput Gene Cloning and Site-Directed Mutagenesis.

Science.gov (United States)

Camilo, Cesar M; Lima, Gustavo M A; Maluf, Fernando V; Guido, Rafael V C; Polikarpov, Igor

2016-01-01

Following burgeoning genomic and transcriptomic sequencing data, biochemical and molecular biology groups worldwide are implementing high-throughput cloning and mutagenesis facilities in order to obtain a large number of soluble proteins for structural and functional characterization. Since manual primer design can be a time-consuming and error-generating step, particularly when working with hundreds of targets, the automation of primer design process becomes highly desirable. HTP-OligoDesigner was created to provide the scientific community with a simple and intuitive online primer design tool for both laboratory-scale and high-throughput projects of sequence-independent gene cloning and site-directed mutagenesis and a Tm calculator for quick queries.

High-throughput cloning and expression in recalcitrant bacteria

NARCIS (Netherlands)

Geertsma, Eric R.; Poolman, Bert

We developed a generic method for high-throughput cloning in bacteria that are less amenable to conventional DNA manipulations. The method involves ligation-independent cloning in an intermediary Escherichia coli vector, which is rapidly converted via vector-backbone exchange (VBEx) into an

Stochastic models for time series

CERN Document Server

Doukhan, Paul

2018-01-01

This book presents essential tools for modelling non-linear time series. The first part of the book describes the main standard tools of probability and statistics that directly apply to the time series context to obtain a wide range of modelling possibilities. Functional estimation and bootstrap are discussed, and stationarity is reviewed. The second part describes a number of tools from Gaussian chaos and proposes a tour of linear time series models. It goes on to address nonlinearity from polynomial or chaotic models for which explicit expansions are available, then turns to Markov and non-Markov linear models and discusses Bernoulli shifts time series models. Finally, the volume focuses on the limit theory, starting with the ergodic theorem, which is seen as the first step for statistics of time series. It defines the distributional range to obtain generic tools for limit theory under long or short-range dependences (LRD/SRD) and explains examples of LRD behaviours. More general techniques (central limit ...

Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs.

Science.gov (United States)

Rodgers, Joseph Lee; Beasley, William Howard; Schuelke, Matthew

2014-01-01

Many data structures, particularly time series data, are naturally seasonal, cyclical, or otherwise circular. Past graphical methods for time series have focused on linear plots. In this article, we move graphical analysis onto the circle. We focus on 2 particular methods, one old and one new. Rose diagrams are circular histograms and can be produced in several different forms using the RRose software system. In addition, we propose, develop, illustrate, and provide software support for a new circular graphical method, called Wrap-Around Time Series Plots (WATS Plots), which is a graphical method useful to support time series analyses in general but in particular in relation to interrupted time series designs. We illustrate the use of WATS Plots with an interrupted time series design evaluating the effect of the Oklahoma City bombing on birthrates in Oklahoma County during the 10 years surrounding the bombing of the Murrah Building in Oklahoma City. We compare WATS Plots with linear time series representations and overlay them with smoothing and error bands. Each method is shown to have advantages in relation to the other; in our example, the WATS Plots more clearly show the existence and effect size of the fertility differential.

Fluorescence-based high-throughput screening of dicer cleavage activity.

Science.gov (United States)

Podolska, Katerina; Sedlak, David; Bartunek, Petr; Svoboda, Petr

2014-03-01

Production of small RNAs by ribonuclease III Dicer is a key step in microRNA and RNA interference pathways, which employ Dicer-produced small RNAs as sequence-specific silencing guides. Further studies and manipulations of microRNA and RNA interference pathways would benefit from identification of small-molecule modulators. Here, we report a study of a fluorescence-based in vitro Dicer cleavage assay, which was adapted for high-throughput screening. The kinetic assay can be performed under single-turnover conditions (35 nM substrate and 70 nM Dicer) in a small volume (5 µL), which makes it suitable for high-throughput screening in a 1536-well format. As a proof of principle, a small library of bioactive compounds was analyzed, demonstrating potential of the assay.

Repurposing a Benchtop Centrifuge for High-Throughput Single-Molecule Force Spectroscopy.

Science.gov (United States)

Yang, Darren; Wong, Wesley P

2018-01-01

We present high-throughput single-molecule manipulation using a benchtop centrifuge, overcoming limitations common in other single-molecule approaches such as high cost, low throughput, technical difficulty, and strict infrastructure requirements. An inexpensive and compact Centrifuge Force Microscope (CFM) adapted to a commercial centrifuge enables use by nonspecialists, and integration with DNA nanoswitches facilitates both reliable measurements and repeated molecular interrogation. Here, we provide detailed protocols for constructing the CFM, creating DNA nanoswitch samples, and carrying out single-molecule force measurements.

X-ray phase microtomography with a single grating for high-throughput investigations of biological tissue.

Science.gov (United States)

Zdora, Marie-Christine; Vila-Comamala, Joan; Schulz, Georg; Khimchenko, Anna; Hipp, Alexander; Cook, Andrew C; Dilg, Daniel; David, Christian; Grünzweig, Christian; Rau, Christoph; Thibault, Pierre; Zanette, Irene

2017-02-01

The high-throughput 3D visualisation of biological specimens is essential for studying diseases and developmental disorders. It requires imaging methods that deliver high-contrast, high-resolution volumetric information at short sample preparation and acquisition times. Here we show that X-ray phase-contrast tomography using a single grating can provide a powerful alternative to commonly employed techniques, such as high-resolution episcopic microscopy (HREM). We present the phase tomography of a mouse embryo in paraffin obtained with an X-ray single-grating interferometer at I13-2 Beamline at Diamond Light Source and discuss the results in comparison with HREM measurements. The excellent contrast and quantitative density information achieved non-destructively and without staining using a simple, robust setup make X-ray single-grating interferometry an optimum candidate for high-throughput imaging of biological specimens as an alternative for existing methods like HREM.

Time Series with Long Memory

OpenAIRE

西埜, 晴久

2004-01-01

The paper investigates an application of long-memory processes to economic time series. We show properties of long-memory processes, which are motivated to model a long-memory phenomenon in economic time series. An FARIMA model is described as an example of long-memory model in statistical terms. The paper explains basic limit theorems and estimation methods for long-memory processes in order to apply long-memory models to economic time series.

Evaluation of Capacity on a High Throughput Vol-oxidizer for Operability

International Nuclear Information System (INIS)

Kim, Young Hwan; Park, Geun Il; Lee, Jung Won; Jung, Jae Hoo; Kim, Ki Ho; Lee, Yong Soon; Lee, Do Youn; Kim, Su Sung

2010-01-01

KAERI is developing a pyro-process. As a piece of process equipment, a high throughput vol-oxidizer which can handle a several tens kg HM/batch was developed to supply U 3 O 8 powders to an electrolytic reduction(ER) reactor. To increase the reduction yield, UO 2 pellets should be converted into uniform powders. In this paper, we aim at the evaluation of a high throughput vol-oxidizer for operability. The evaluation consisted of 3 targets, a mechanical motion test, a heating test and hull separation test. In order to test a high throughput vol-oxidizer, By using a control system, mechanical motion tests of the vol-oxidizer were conducted, and heating rates were analyzed. Also the separation tests of hulls for recovery rate were conducted. The test results of the vol-oxidizer are going to be applied for operability. A study on the characteristics of the volatile gas produced during a vol-oxidation process is not included in this study

Fun with High Throughput Toxicokinetics (CalEPA webinar)

Science.gov (United States)

Thousands of chemicals have been profiled by high-throughput screening (HTS) programs such as ToxCast and Tox21. These chemicals are tested in part because there are limited or no data on hazard, exposure, or toxicokinetics (TK). TK models aid in predicting tissue concentrations ...

Visibility Graph Based Time Series Analysis.

Science.gov (United States)

Stephen, Mutua; Gu, Changgui; Yang, Huijie

2015-01-01

Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.

Visibility Graph Based Time Series Analysis.

Directory of Open Access Journals (Sweden)

Mutua Stephen

Full Text Available Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.

Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.

Science.gov (United States)

Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A

2017-08-07

High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier

Time series momentum and contrarian effects in the Chinese stock market

Science.gov (United States)

Shi, Huai-Long; Zhou, Wei-Xing

2017-10-01

This paper concentrates on the time series momentum or contrarian effects in the Chinese stock market. We evaluate the performance of the time series momentum strategy applied to major stock indices in mainland China and explore the relation between the performance of time series momentum strategies and some firm-specific characteristics. Our findings indicate that there is a time series momentum effect in the short run and a contrarian effect in the long run in the Chinese stock market. The performances of the time series momentum and contrarian strategies are highly dependent on the look-back and holding periods and firm-specific characteristics.

Quantitative description on structure-property relationships of Li-ion battery materials for high-throughput computations

Science.gov (United States)

Wang, Youwei; Zhang, Wenqing; Chen, Lidong; Shi, Siqi; Liu, Jianjun

2017-12-01

Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure-property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure-property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure-property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials.

Subsidence Evaluation of High-Speed Railway in Shenyang Based on Time-Series Insar

Science.gov (United States)

Zhang, Yun; Wei, Lianhuan; Li, Jiayu; Liu, Shanjun; Mao, Yachun; Wu, Lixin

2018-04-01

More and more high-speed railway are under construction in China. The slow settlement along high-speed railway tracks and newly-built stations would lead to inhomogeneous deformation of local area, and the accumulation may be a threat to the safe operation of high-speed rail system. In this paper, surface deformation of the newly-built high-speed railway station as well as the railway lines in Shenyang region will be retrieved by time series InSAR analysis using multi-orbit COSMO-SkyMed images. This paper focuses on the non-uniform subsidence caused by the changing of local environment along the railway. The accuracy of the settlement results can be verified by cross validation of the results obtained from two different orbits during the same period.

High throughput second harmonic imaging for label-free biological applications

KAUST Repository

Macias Romero, Carlos; Didier, Marie E P; Jourdain, Pascal; Marquet, Pierre; Magistretti, Pierre J.; Tarun, Orly B.; Zubkovs, Vitalijs; Radenovic, Aleksandra; Roke, Sylvie

2014-01-01

Second harmonic generation (SHG) is inherently sensitive to the absence of spatial centrosymmetry, which can render it intrinsically sensitive to interfacial processes, chemical changes and electrochemical responses. Here, we seek to improve the imaging throughput of SHG microscopy by using a wide-field imaging scheme in combination with a medium-range repetition rate amplified near infrared femtosecond laser source and gated detection. The imaging throughput of this configuration is tested by measuring the optical image contrast for different image acquisition times of BaTiO3 nanoparticles in two different wide-field setups and one commercial point-scanning configuration. We find that the second harmonic imaging throughput is improved by 2-3 orders of magnitude compared to point-scan imaging. Capitalizing on this result, we perform low fluence imaging of (parts of) living mammalian neurons in culture.

Transition Icons for Time-Series Visualization and Exploratory Analysis.

Science.gov (United States)

Nickerson, Paul V; Baharloo, Raheleh; Wanigatunga, Amal A; Manini, Todd M; Tighe, Patrick J; Rashidi, Parisa

2018-03-01

The modern healthcare landscape has seen the rapid emergence of techniques and devices that temporally monitor and record physiological signals. The prevalence of time-series data within the healthcare field necessitates the development of methods that can analyze the data in order to draw meaningful conclusions. Time-series behavior is notoriously difficult to intuitively understand due to its intrinsic high-dimensionality, which is compounded in the case of analyzing groups of time series collected from different patients. Our framework, which we call transition icons, renders common patterns in a visual format useful for understanding the shared behavior within groups of time series. Transition icons are adept at detecting and displaying subtle differences and similarities, e.g., between measurements taken from patients receiving different treatment strategies or stratified by demographics. We introduce various methods that collectively allow for exploratory analysis of groups of time series, while being free of distribution assumptions and including simple heuristics for parameter determination. Our technique extracts discrete transition patterns from symbolic aggregate approXimation representations, and compiles transition frequencies into a bag of patterns constructed for each group. These transition frequencies are normalized and aligned in icon form to intuitively display the underlying patterns. We demonstrate the transition icon technique for two time-series datasets-postoperative pain scores, and hip-worn accelerometer activity counts. We believe transition icons can be an important tool for researchers approaching time-series data, as they give rich and intuitive information about collective time-series behaviors.

A hybrid MAC protocol design for energy-efficient very-high-throughput millimeter wave, wireless sensor communication networks

Science.gov (United States)

Jian, Wei; Estevez, Claudio; Chowdhury, Arshad; Jia, Zhensheng; Wang, Jianxin; Yu, Jianguo; Chang, Gee-Kung

2010-12-01

This paper presents an energy-efficient Medium Access Control (MAC) protocol for very-high-throughput millimeter-wave (mm-wave) wireless sensor communication networks (VHT-MSCNs) based on hybrid multiple access techniques of frequency division multiplexing access (FDMA) and time division multiplexing access (TDMA). An energy-efficient Superframe for wireless sensor communication network employing directional mm-wave wireless access technologies is proposed for systems that require very high throughput, such as high definition video signals, for sensing, processing, transmitting, and actuating functions. Energy consumption modeling for each network element and comparisons among various multi-access technologies in term of power and MAC layer operations are investigated for evaluating the energy-efficient improvement of proposed MAC protocol.

Luminex and other multiplex high throughput technologies for the identification of, and host response to, environmental triggers of type 1 diabetes.

Science.gov (United States)

Purohit, Sharad; Sharma, Ashok; She, Jin-Xiong

2015-01-01

Complex interactions between a series of environmental factors and genes result in progression to clinical type 1 diabetes in genetically susceptible individuals. Despite several decades of research in the area, these interactions remain poorly understood. Several studies have yielded associations of certain foods, infections, and immunizations with the onset and progression of diabetes autoimmunity, but most findings are still inconclusive. Environmental triggers are difficult to identify mainly due to (i) large number and complex nature of environmental exposures, including bacteria, viruses, dietary factors, and environmental pollutants, (ii) reliance on low throughput technology, (iii) less efforts in quantifying host response, (iv) long silent period between the exposure and clinical onset of T1D which may lead to loss of the exposure fingerprints, and (v) limited sample sets. Recent development in multiplex technologies has enabled systematic evaluation of different classes of molecules or macroparticles in a high throughput manner. However, the use of multiplex assays in type 1 diabetes research is limited to cytokine assays. In this review, we will discuss the potential use of multiplex high throughput technologies in identification of environmental triggers and host response in type 1 diabetes.

FPGA cluster for high-performance AO real-time control system

Science.gov (United States)

Geng, Deli; Goodsell, Stephen J.; Basden, Alastair G.; Dipper, Nigel A.; Myers, Richard M.; Saunter, Chris D.

2006-06-01

Whilst the high throughput and low latency requirements for the next generation AO real-time control systems have posed a significant challenge to von Neumann architecture processor systems, the Field Programmable Gate Array (FPGA) has emerged as a long term solution with high performance on throughput and excellent predictability on latency. Moreover, FPGA devices have highly capable programmable interfacing, which lead to more highly integrated system. Nevertheless, a single FPGA is still not enough: multiple FPGA devices need to be clustered to perform the required subaperture processing and the reconstruction computation. In an AO real-time control system, the memory bandwidth is often the bottleneck of the system, simply because a vast amount of supporting data, e.g. pixel calibration maps and the reconstruction matrix, need to be accessed within a short period. The cluster, as a general computing architecture, has excellent scalability in processing throughput, memory bandwidth, memory capacity, and communication bandwidth. Problems, such as task distribution, node communication, system verification, are discussed.

Reverse Phase Protein Arrays for High-throughput Toxicity Screening

DEFF Research Database (Denmark)

Pedersen, Marlene Lemvig; Block, Ines; List, Markus

High-throughput screening is extensively applied for identification of drug targets and drug discovery and recently it found entry into toxicity testing. Reverse phase protein arrays (RPPAs) are used widespread for quantification of protein markers. We reasoned that RPPAs also can be utilized...... beneficially in automated high-throughput toxicity testing. An advantage of using RPPAs is that, in addition to the baseline toxicity readout, they allow testing of multiple markers of toxicity, such as inflammatory responses, which do not necessarily cumulate in cell death. We used transfection of si......RNAs with known killing effects as a model system to demonstrate that RPPA-based protein quantification can serve as substitute readout of cell viability, hereby reliably reflecting toxicity. In terms of automation, cell exposure, protein harvest, serial dilution and sample reformatting were performed using...

Development of automatic image analysis methods for high-throughput and high-content screening

NARCIS (Netherlands)

Di, Zi

2013-01-01

This thesis focuses on the development of image analysis methods for ultra-high content analysis of high-throughput screens where cellular phenotype responses to various genetic or chemical perturbations that are under investigation. Our primary goal is to deliver efficient and robust image analysis

Determining the optimal size of small molecule mixtures for high throughput NMR screening

International Nuclear Information System (INIS)

Mercier, Kelly A.; Powers, Robert

2005-01-01

High-throughput screening (HTS) using NMR spectroscopy has become a common component of the drug discovery effort and is widely used throughout the pharmaceutical industry. NMR provides additional information about the nature of small molecule-protein interactions compared to traditional HTS methods. In order to achieve comparable efficiency, small molecules are often screened as mixtures in NMR-based assays. Nevertheless, an analysis of the efficiency of mixtures and a corresponding determination of the optimum mixture size (OMS) that minimizes the amount of material and instrumentation time required for an NMR screen has been lacking. A model for calculating OMS based on the application of the hypergeometric distribution function to determine the probability of a 'hit' for various mixture sizes and hit rates is presented. An alternative method for the deconvolution of large screening mixtures is also discussed. These methods have been applied in a high-throughput NMR screening assay using a small, directed library

Quantitative in vitro-to-in vivo extrapolation in a high-throughput environment

International Nuclear Information System (INIS)

Wetmore, Barbara A.

2015-01-01

High-throughput in vitro toxicity screening provides an efficient way to identify potential biological targets for environmental and industrial chemicals while conserving limited testing resources. However, reliance on the nominal chemical concentrations in these in vitro assays as an indicator of bioactivity may misrepresent potential in vivo effects of these chemicals due to differences in clearance, protein binding, bioavailability, and other pharmacokinetic factors. Development of high-throughput in vitro hepatic clearance and protein binding assays and refinement of quantitative in vitro-to-in vivo extrapolation (QIVIVE) methods have provided key tools to predict xenobiotic steady state pharmacokinetics. Using a process known as reverse dosimetry, knowledge of the chemical steady state behavior can be incorporated with HTS data to determine the external in vivo oral exposure needed to achieve internal blood concentrations equivalent to those eliciting bioactivity in the assays. These daily oral doses, known as oral equivalents, can be compared to chronic human exposure estimates to assess whether in vitro bioactivity would be expected at the dose-equivalent level of human exposure. This review will describe the use of QIVIVE methods in a high-throughput environment and the promise they hold in shaping chemical testing priorities and, potentially, high-throughput risk assessment strategies

Tracking Large Area Mangrove Deforestation with Time-Series of High Fidelity MODIS Imagery

Science.gov (United States)

Rahman, A. F.; Dragoni, D.; Didan, K.

2011-12-01

Mangrove forests are important coastal ecosystems of the tropical and subtropical regions. These forests provide critical ecosystem services, fulfill important socio-economic and environmental functions, and support coastal livelihoods. But these forest are also among the most vulnerable ecosystems, both to anthropogenic disturbance and climate change. Yet, there exists no map or published study showing detailed spatiotemporal trends of mangrove deforestation at local to regional scales. There is an immediate need of producing such detailed maps to further study the drivers, impacts and feedbacks of anthropogenic and climate factors on mangrove deforestation, and to develop local and regional scale adaptation/mitigation strategies. In this study we use a time-series of high fidelity imagery from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) for tracking changes in the greenness of mangrove forests of Kalimantan Island of Indonesia. A novel method of filtering satellite data for cloud, aerosol, and view angle effects was used to produce high fidelity MODIS time-series images at 250-meter spatial resolution and three-month temporal resolution for the period of 2000-2010. Enhanced Vegetation Index 2 (EVI2), a measure of vegetation greenness, was calculated from these images for each pixel at each time interval. Temporal variations in the EVI2 of each pixel were tracked as a proxy to deforestaton of mangroves using the statistical method of change-point analysis. Results of these change detection were validated using Monte Carlo simulation, photographs from Google-Earth, finer spatial resolution images from Landsat satellite, and ground based GIS data.

What marketing scholars should know about time series analysis : time series applications in marketing

NARCIS (Netherlands)

Horváth, Csilla; Kornelis, Marcel; Leeflang, Peter S.H.

2002-01-01

In this review, we give a comprehensive summary of time series techniques in marketing, and discuss a variety of time series analysis (TSA) techniques and models. We classify them in the sets (i) univariate TSA, (ii) multivariate TSA, and (iii) multiple TSA. We provide relevant marketing

High-throughput combinatorial chemical bath deposition: The case of doping Cu (In, Ga) Se film with antimony

Science.gov (United States)

Yan, Zongkai; Zhang, Xiaokun; Li, Guang; Cui, Yuxing; Jiang, Zhaolian; Liu, Wen; Peng, Zhi; Xiang, Yong

2018-01-01

The conventional methods for designing and preparing thin film based on wet process remain a challenge due to disadvantages such as time-consuming and ineffective, which hinders the development of novel materials. Herein, we present a high-throughput combinatorial technique for continuous thin film preparation relied on chemical bath deposition (CBD). The method is ideally used to prepare high-throughput combinatorial material library with low decomposition temperatures and high water- or oxygen-sensitivity at relatively high-temperature. To check this system, a Cu(In, Ga)Se (CIGS) thin films library doped with 0-19.04 at.% of antimony (Sb) was taken as an example to evaluate the regulation of varying Sb doping concentration on the grain growth, structure, morphology and electrical properties of CIGS thin film systemically. Combined with the Energy Dispersive Spectrometer (EDS), X-ray Photoelectron Spectroscopy (XPS), automated X-ray Diffraction (XRD) for rapid screening and Localized Electrochemical Impedance Spectroscopy (LEIS), it was confirmed that this combinatorial high-throughput system could be used to identify the composition with the optimal grain orientation growth, microstructure and electrical properties systematically, through accurately monitoring the doping content and material composition. According to the characterization results, a Sb2Se3 quasi-liquid phase promoted CIGS film-growth model has been put forward. In addition to CIGS thin film reported here, the combinatorial CBD also could be applied to the high-throughput screening of other sulfide thin film material systems.

High-throughput screening to enhance oncolytic virus immunotherapy

Directory of Open Access Journals (Sweden)

Allan KJ

2016-04-01

Full Text Available KJ Allan,1,2 David F Stojdl,1–3 SL Swift1 1Children’s Hospital of Eastern Ontario (CHEO Research Institute, 2Department of Biology, Microbiology and Immunology, 3Department of Pediatrics, University of Ottawa, Ottawa, ON, Canada Abstract: High-throughput screens can rapidly scan and capture large amounts of information across multiple biological parameters. Although many screens have been designed to uncover potential new therapeutic targets capable of crippling viruses that cause disease, there have been relatively few directed at improving the efficacy of viruses that are used to treat disease. Oncolytic viruses (OVs are biotherapeutic agents with an inherent specificity for treating malignant disease. Certain OV platforms – including those based on herpes simplex virus, reovirus, and vaccinia virus – have shown success against solid tumors in advanced clinical trials. Yet, many of these OVs have only undergone minimal engineering to solidify tumor specificity, with few extra modifications to manipulate additional factors. Several aspects of the interaction between an OV and a tumor-bearing host have clear value as targets to improve therapeutic outcomes. At the virus level, these include delivery to the tumor, infectivity, productivity, oncolysis, bystander killing, spread, and persistence. At the host level, these include engaging the immune system and manipulating the tumor microenvironment. Here, we review the chemical- and genome-based high-throughput screens that have been performed to manipulate such parameters during OV infection and analyze their impact on therapeutic efficacy. We further explore emerging themes that represent key areas of focus for future research. Keywords: oncolytic, virus, screen, high-throughput, cancer, chemical, genomic, immunotherapy

A High-Throughput Antibody-Based Microarray Typing Platform

Directory of Open Access Journals (Sweden)

Ashan Perera

2013-05-01

Full Text Available Many rapid methods have been developed for screening foods for the presence of pathogenic microorganisms. Rapid methods that have the additional ability to identify microorganisms via multiplexed immunological recognition have the potential for classification or typing of microbial contaminants thus facilitating epidemiological investigations that aim to identify outbreaks and trace back the contamination to its source. This manuscript introduces a novel, high throughput typing platform that employs microarrayed multiwell plate substrates and laser-induced fluorescence of the nucleic acid intercalating dye/stain SYBR Gold for detection of antibody-captured bacteria. The aim of this study was to use this platform for comparison of different sets of antibodies raised against the same pathogens as well as demonstrate its potential effectiveness for serotyping. To that end, two sets of antibodies raised against each of the “Big Six” non-O157 Shiga toxin-producing E. coli (STEC as well as E. coli O157:H7 were array-printed into microtiter plates, and serial dilutions of the bacteria were added and subsequently detected. Though antibody specificity was not sufficient for the development of an STEC serotyping method, the STEC antibody sets performed reasonably well exhibiting that specificity increased at lower capture antibody concentrations or, conversely, at lower bacterial target concentrations. The favorable results indicated that with sufficiently selective and ideally concentrated sets of biorecognition elements (e.g., antibodies or aptamers, this high-throughput platform can be used to rapidly type microbial isolates derived from food samples within ca. 80 min of total assay time. It can also potentially be used to detect the pathogens from food enrichments and at least serve as a platform for testing antibodies.

Automation of a Nile red staining assay enables high throughput quantification of microalgal lipid production.

Science.gov (United States)

Morschett, Holger; Wiechert, Wolfgang; Oldiges, Marco

2016-02-09

Within the context of microalgal lipid production for biofuels and bulk chemical applications, specialized higher throughput devices for small scale parallelized cultivation are expected to boost the time efficiency of phototrophic bioprocess development. However, the increasing number of possible experiments is directly coupled to the demand for lipid quantification protocols that enable reliably measuring large sets of samples within short time and that can deal with the reduced sample volume typically generated at screening scale. To meet these demands, a dye based assay was established using a liquid handling robot to provide reproducible high throughput quantification of lipids with minimized hands-on-time. Lipid production was monitored using the fluorescent dye Nile red with dimethyl sulfoxide as solvent facilitating dye permeation. The staining kinetics of cells at different concentrations and physiological states were investigated to successfully down-scale the assay to 96 well microtiter plates. Gravimetric calibration against a well-established extractive protocol enabled absolute quantification of intracellular lipids improving precision from ±8 to ±2 % on average. Implementation into an automated liquid handling platform allows for measuring up to 48 samples within 6.5 h, reducing hands-on-time to a third compared to manual operation. Moreover, it was shown that automation enhances accuracy and precision compared to manual preparation. It was revealed that established protocols relying on optical density or cell number for biomass adjustion prior to staining may suffer from errors due to significant changes of the cells' optical and physiological properties during cultivation. Alternatively, the biovolume was used as a measure for biomass concentration so that errors from morphological changes can be excluded. The newly established assay proved to be applicable for absolute quantification of algal lipids avoiding limitations of currently established

Leveraging the Power of High Performance Computing for Next Generation Sequencing Data Analysis: Tricks and Twists from a High Throughput Exome Workflow

Science.gov (United States)

Wonczak, Stephan; Thiele, Holger; Nieroda, Lech; Jabbari, Kamel; Borowski, Stefan; Sinha, Vishal; Gunia, Wilfried; Lang, Ulrich; Achter, Viktor; Nürnberg, Peter

2015-01-01

Next generation sequencing (NGS) has been a great success and is now a standard method of research in the life sciences. With this technology, dozens of whole genomes or hundreds of exomes can be sequenced in rather short time, producing huge amounts of data. Complex bioinformatics analyses are required to turn these data into scientific findings. In order to run these analyses fast, automated workflows implemented on high performance computers are state of the art. While providing sufficient compute power and storage to meet the NGS data challenge, high performance computing (HPC) systems require special care when utilized for high throughput processing. This is especially true if the HPC system is shared by different users. Here, stability, robustness and maintainability are as important for automated workflows as speed and throughput. To achieve all of these aims, dedicated solutions have to be developed. In this paper, we present the tricks and twists that we utilized in the implementation of our exome data processing workflow. It may serve as a guideline for other high throughput data analysis projects using a similar infrastructure. The code implementing our solutions is provided in the supporting information files. PMID:25942438

A Customizable Flow Injection System for Automated, High Throughput, and Time Sensitive Ion Mobility Spectrometry and Mass Spectrometry Measurements

Energy Technology Data Exchange (ETDEWEB)

Orton, Daniel J. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Tfaily, Malak M. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Moore, Ronald J. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; LaMarche, Brian L. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Zheng, Xueyun [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Fillmore, Thomas L. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Chu, Rosalie K. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Weitz, Karl K. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Monroe, Matthew E. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Kelly, Ryan T. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Smith, Richard D. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Baker, Erin S. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States

2017-12-13

To better understand disease conditions and environmental perturbations, multi-omic studies (i.e. proteomic, lipidomic, metabolomic, etc. analyses) are vastly increasing in popularity. In a multi-omic study, a single sample is typically extracted in multiple ways and numerous analyses are performed using different instruments. Thus, one sample becomes many analyses, making high throughput and reproducible evaluations a necessity. One way to address the numerous samples and varying instrumental conditions is to utilize a flow injection analysis (FIA) system for rapid sample injection. While some FIA systems have been created to address these challenges, many have limitations such as high consumable costs, low pressure capabilities, limited pressure monitoring and fixed flow rates. To address these limitations, we created an automated, customizable FIA system capable of operating at diverse flow rates (~50 nL/min to 500 µL/min) to accommodate low- and high-flow instrument sources. This system can also operate at varying analytical throughputs from 24 to 1200 samples per day to enable different MS analysis approaches. Applications ranging from native protein analyses to molecular library construction were performed using the FIA system. The results from these studies showed a highly robust platform, providing consistent performance over many days without carryover as long as washing buffers specific to each molecular analysis were utilized.

High-Throughput Platform for Synthesis of Melamine-Formaldehyde Microcapsules.

Science.gov (United States)

Çakir, Seda; Bauters, Erwin; Rivero, Guadalupe; Parasote, Tom; Paul, Johan; Du Prez, Filip E

2017-07-10

The synthesis of microcapsules via in situ polymerization is a labor-intensive and time-consuming process, where many composition and process factors affect the microcapsule formation and its morphology. Herein, we report a novel combinatorial technique for the preparation of melamine-formaldehyde microcapsules, using a custom-made and automated high-throughput platform (HTP). After performing validation experiments for ensuring the accuracy and reproducibility of the novel platform, a design of experiment study was performed. The influence of different encapsulation parameters was investigated, such as the effect of the surfactant, surfactant type, surfactant concentration and core/shell ratio. As a result, this HTP-platform is suitable to be used for the synthesis of different types of microcapsules in an automated and controlled way, allowing the screening of different reaction parameters in a shorter time compared to the manual synthetic techniques.

Data mining in time series databases

CERN Document Server

Kandel, Abraham; Bunke, Horst

2004-01-01

Adding the time dimension to real-world databases produces Time SeriesDatabases (TSDB) and introduces new aspects and difficulties to datamining and knowledge discovery. This book covers the state-of-the-artmethodology for mining time series databases. The novel data miningmethods presented in the book include techniques for efficientsegmentation, indexing, and classification of noisy and dynamic timeseries. A graph-based method for anomaly detection in time series isdescribed and the book also studies the implications of a novel andpotentially useful representation of time series as strings. Theproblem of detecting changes in data mining models that are inducedfrom temporal databases is additionally discussed.

Radiation metabolomics : a window to high throughput radiation biodosimetry

International Nuclear Information System (INIS)

Rana, Poonam

2016-01-01

In the event of an intentional or accidental release of ionizing radiation in a densely populated area, timely assessment and triage of the general population for radiation exposure is critical. In particular, a significant number of victims may sustain radiation injury, which increases mortality and worsens the overall prognosis of victims from radiation trauma. Availability of a high-throughput noninvasive in vivo biodosimetry tool for assessing the radiation exposure is of particular importance for timely diagnosis of radiation injury. In this study, we describe the potential NMR techniques in evaluating the radiation injury. NMR is the most versatile technique that has been extensively used in the diverse fields of science since its discovery. NMR and biomedical sciences have been going hand in hand since its application in clinical imaging as MRI and metabolic profiling of biofluids was identified. We have established an NMR based metabonomic and in vivo spectroscopy approach to analyse and identify metabolic profile to measure metabolic fingerprint for radiation exposure. NMR spectroscopy experiments were conducted on urine and serum samples collected from mice irradiated with different doses of radiation. Additionally, in vivo NMR spectroscopy was also performed in different region of brains post irradiation in animal model. A number of metabolites associated with energy metabolism, gut flora metabolites, osmolytes, amino acids and membrane metabolism were identified in serum and urine metabolome. Our results illustrated a metabolic fingerprint for radiation exposure that elucidates perturbed physiological functions. Quantitative as well as multivariate analysis/assessment of these metabolites demonstrated dose and time dependent toxicological effect. In vivo spectroscopy from brain showed radiation induced changes in hippocampus region indicating whole body radiation had striking effect on brain metabolism as well. The results of the present work lay a

High throughput screening of starch structures using carbohydrate microarrays

DEFF Research Database (Denmark)

Tanackovic, Vanja; Rydahl, Maja Gro; Pedersen, Henriette Lodberg

2016-01-01

In this study we introduce the starch-recognising carbohydrate binding module family 20 (CBM20) from Aspergillus niger for screening biological variations in starch molecular structure using high throughput carbohydrate microarray technology. Defined linear, branched and phosphorylated...

Models for dependent time series

CERN Document Server

Tunnicliffe Wilson, Granville; Haywood, John

2015-01-01

Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful, applicable, and statistically valid conclusions from multivariate (or vector) time series data.The first four chapters discuss the two main pillars of the subject that have been developed over the last 60 years: vector autoregressive modeling and multivariate spectral analysis. These chapters provide the foundational mater

Achieving high data throughput in research networks

International Nuclear Information System (INIS)

Matthews, W.; Cottrell, L.

2001-01-01

After less than a year of operation, the BaBar experiment at SLAC has collected almost 100 million particle collision events in a database approaching 165TB. Around 20 TB of data has been exported via the Internet to the BaBar regional center at IN2P3 in Lyon, France, and around 40TB of simulated data has been imported from the Lawrence Livermore National Laboratory (LLNL). BaBar collaborators plan to double data collection each year and export a third of the data to IN2P3. So within a few years the SLAC OC3 (155 Mbps) connection will be fully utilized by file transfer to France alone. Upgrades to infrastructure is essential and detailed understanding of performance issues and the requirements for reliable high throughput transfers is critical. In this talk results from active and passive monitoring and direct measurements of throughput will be reviewed. Methods for achieving the ambitious requirements will be discussed

Achieving High Data Throughput in Research Networks

International Nuclear Information System (INIS)

Matthews, W

2004-01-01

After less than a year of operation, the BaBar experiment at SLAC has collected almost 100 million particle collision events in a database approaching 165TB. Around 20 TB of data has been exported via the Internet to the BaBar regional center at IN2P3 in Lyon, France, and around 40TB of simulated data has been imported from the Lawrence Livermore National Laboratory (LLNL). BaBar collaborators plan to double data collection each year and export a third of the data to IN2P3. So within a few years the SLAC OC3 (155Mbps) connection will be fully utilized by file transfer to France alone. Upgrades to infrastructure is essential and detailed understanding of performance issues and the requirements for reliable high throughput transfers is critical. In this talk results from active and passive monitoring and direct measurements of throughput will be reviewed. Methods for achieving the ambitious requirements will be discussed

Time-variant power spectral analysis of heart-rate time series by ...

Indian Academy of Sciences (India)

Frequency domain representation of a short-term heart-rate time series (HRTS) signal is a popular method for evaluating the cardiovascular control system. The spectral parameters, viz. percentage power in low frequency band (%PLF), percentage power in high frequency band (%PHF), power ratio of low frequency to high ...

A priori Considerations When Conducting High-Throughput Amplicon-Based Sequence Analysis

Directory of Open Access Journals (Sweden)

Aditi Sengupta

2016-03-01

Full Text Available Amplicon-based sequencing strategies that include 16S rRNA and functional genes, alongside “meta-omics” analyses of communities of microorganisms, have allowed researchers to pose questions and find answers to “who” is present in the environment and “what” they are doing. Next-generation sequencing approaches that aid microbial ecology studies of agricultural systems are fast gaining popularity among agronomy, crop, soil, and environmental science researchers. Given the rapid development of these high-throughput sequencing techniques, researchers with no prior experience will desire information about the best practices that can be used before actually starting high-throughput amplicon-based sequence analyses. We have outlined items that need to be carefully considered in experimental design, sampling, basic bioinformatics, sequencing of mock communities and negative controls, acquisition of metadata, and in standardization of reaction conditions as per experimental requirements. Not all considerations mentioned here may pertain to a particular study. The overall goal is to inform researchers about considerations that must be taken into account when conducting high-throughput microbial DNA sequencing and sequences analysis.

Visual time series analysis

DEFF Research Database (Denmark)

Fischer, Paul; Hilbert, Astrid

2012-01-01

We introduce a platform which supplies an easy-to-handle, interactive, extendable, and fast analysis tool for time series analysis. In contrast to other software suits like Maple, Matlab, or R, which use a command-line-like interface and where the user has to memorize/look-up the appropriate...... commands, our application is select-and-click-driven. It allows to derive many different sequences of deviations for a given time series and to visualize them in different ways in order to judge their expressive power and to reuse the procedure found. For many transformations or model-ts, the user may...... choose between manual and automated parameter selection. The user can dene new transformations and add them to the system. The application contains efficient implementations of advanced and recent techniques for time series analysis including techniques related to extreme value analysis and filtering...

A high-throughput fluorescence resonance energy transfer (FRET)-based endothelial cell apoptosis assay and its application for screening vascular disrupting agents

International Nuclear Information System (INIS)

Zhu, Xiaoming; Fu, Afu; Luo, Kathy Qian

2012-01-01

Highlights: ► An endothelial cell apoptosis assay using FRET-based biosensor was developed. ► The fluorescence of the cells changed from green to blue during apoptosis. ► This method was developed into a high-throughput assay in 96-well plates. ► This assay was applied to screen vascular disrupting agents. -- Abstract: In this study, we developed a high-throughput endothelial cell apoptosis assay using a fluorescence resonance energy transfer (FRET)-based biosensor. After exposure to apoptotic inducer UV-irradiation or anticancer drugs such as paclitaxel, the fluorescence of the cells changed from green to blue. We developed this method into a high-throughput assay in 96-well plates by measuring the emission ratio of yellow fluorescent protein (YFP) to cyan fluorescent protein (CFP) to monitor the activation of a key protease, caspase-3, during apoptosis. The Z′ factor for this assay was above 0.5 which indicates that this assay is suitable for a high-throughput analysis. Finally, we applied this functional high-throughput assay for screening vascular disrupting agents (VDA) which could induce endothelial cell apoptosis from our in-house compounds library and dioscin was identified as a hit. As this assay allows real time and sensitive detection of cell apoptosis, it will be a useful tool for monitoring endothelial cell apoptosis in living cell situation and for identifying new VDA candidates via a high-throughput screening.

Creating high-resolution time series land-cover classifications in rapidly changing forested areas with BULC-U in Google Earth Engine

Science.gov (United States)

Cardille, J. A.; Lee, J.

2017-12-01

With the opening of the Landsat archive, there is a dramatically increased potential for creating high-quality time series of land use/land-cover (LULC) classifications derived from remote sensing. Although LULC time series are appealing, their creation is typically challenging in two fundamental ways. First, there is a need to create maximally correct LULC maps for consideration at each time step; and second, there is a need to have the elements of the time series be consistent with each other, without pixels that flip improbably between covers due only to unavoidable, stray classification errors. We have developed the Bayesian Updating of Land Cover - Unsupervised (BULC-U) algorithm to address these challenges simultaneously, and introduce and apply it here for two related but distinct purposes. First, with minimal human intervention, we produced an internally consistent, high-accuracy LULC time series in rapidly changing Mato Grosso, Brazil for a time interval (1986-2000) in which cropland area more than doubled. The spatial and temporal resolution of the 59 LULC snapshots allows users to witness the establishment of towns and farms at the expense of forest. The new time series could be used by policy-makers and analysts to unravel important considerations for conservation and management, including the timing and location of past development, the rate and nature of changes in forest connectivity, the connection with road infrastructure, and more. The second application of BULC-U is to sharpen the well-known GlobCover 2009 classification from 300m to 30m, while improving accuracy measures for every class. The greatly improved resolution and accuracy permits a better representation of the true LULC proportions, the use of this map in models, and quantification of the potential impacts of changes. Given that there may easily be thousands and potentially millions of images available to harvest for an LULC time series, it is imperative to build useful algorithms

Classification of Small-Scale Eucalyptus Plantations Based on NDVI Time Series Obtained from Multiple High-Resolution Datasets

Directory of Open Access Journals (Sweden)

Hailang Qiao

2016-02-01

Full Text Available Eucalyptus, a short-rotation plantation, has been expanding rapidly in southeast China in recent years owing to its short growth cycle and high yield of wood. Effective identification of eucalyptus, therefore, is important for monitoring land use changes and investigating environmental quality. For this article, we used remote sensing images over 15 years (one per year with a 30-m spatial resolution, including Landsat 5 thematic mapper images, Landsat 7-enhanced thematic mapper images, and HJ 1A/1B images. These data were used to construct a 15-year Normalized Difference Vegetation Index (NDVI time series for several cities in Guangdong Province, China. Eucalyptus reference NDVI time series sub-sequences were acquired, including one-year-long and two-year-long growing periods, using invested eucalyptus samples in the study region. In order to compensate for the discontinuity of the NDVI time series that is a consequence of the relatively coarse temporal resolution, we developed an inverted triangle area methodology. Using this methodology, the images were classified on the basis of the matching degree of the NDVI time series and two reference NDVI time series sub-sequences during the growing period of the eucalyptus rotations. Three additional methodologies (Bounding Envelope, City Block, and Standardized Euclidian Distance were also tested and used as a comparison group. Threshold coefficients for the algorithms were adjusted using commission–omission error criteria. The results show that the triangle area methodology out-performed the other methodologies in classifying eucalyptus plantations. Threshold coefficients and an optimal discriminant function were determined using a mosaic photograph that had been taken by an unmanned aerial vehicle platform. Good stability was found as we performed further validation using multiple-year data from the high-resolution Gaofen Satellite 1 (GF-1 observations of larger regions. Eucalyptus planting dates

Enzyme free cloning for high throughput gene cloning and expression

NARCIS (Netherlands)

de Jong, R.N.; Daniëls, M.; Kaptein, R.; Folkers, G.E.

2006-01-01

Structural and functional genomics initiatives significantly improved cloning methods over the past few years. Although recombinational cloning is highly efficient, its costs urged us to search for an alternative high throughput (HTP) cloning method. We implemented a modified Enzyme Free Cloning

High-throughput micro-scale cultivations and chromatography modeling: Powerful tools for integrated process development.

Science.gov (United States)

Baumann, Pascal; Hahn, Tobias; Hubbuch, Jürgen

2015-10-01

Upstream processes are rather complex to design and the productivity of cells under suitable cultivation conditions is hard to predict. The method of choice for examining the design space is to execute high-throughput cultivation screenings in micro-scale format. Various predictive in silico models have been developed for many downstream processes, leading to a reduction of time and material costs. This paper presents a combined optimization approach based on high-throughput micro-scale cultivation experiments and chromatography modeling. The overall optimized system must not necessarily be the one with highest product titers, but the one resulting in an overall superior process performance in up- and downstream. The methodology is presented in a case study for the Cherry-tagged enzyme Glutathione-S-Transferase from Escherichia coli SE1. The Cherry-Tag™ (Delphi Genetics, Belgium) which can be fused to any target protein allows for direct product analytics by simple VIS absorption measurements. High-throughput cultivations were carried out in a 48-well format in a BioLector micro-scale cultivation system (m2p-Labs, Germany). The downstream process optimization for a set of randomly picked upstream conditions producing high yields was performed in silico using a chromatography modeling software developed in-house (ChromX). The suggested in silico-optimized operational modes for product capturing were validated subsequently. The overall best system was chosen based on a combination of excellent up- and downstream performance. © 2015 Wiley Periodicals, Inc.

A Review of Subsequence Time Series Clustering

Directory of Open Access Journals (Sweden)

Seyedjamal Zolhavarieh

2014-01-01

Full Text Available Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

A review of subsequence time series clustering.

Science.gov (United States)

Zolhavarieh, Seyedjamal; Aghabozorgi, Saeed; Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

A Review of Subsequence Time Series Clustering

Science.gov (United States)

Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies. PMID:25140332

A rapid enzymatic assay for high-throughput screening of adenosine-producing strains

Science.gov (United States)

Dong, Huina; Zu, Xin; Zheng, Ping; Zhang, Dawei

2015-01-01

Adenosine is a major local regulator of tissue function and industrially useful as precursor for the production of medicinal nucleoside substances. High-throughput screening of adenosine overproducers is important for industrial microorganism breeding. An enzymatic assay of adenosine was developed by combined adenosine deaminase (ADA) with indophenol method. The ADA catalyzes the cleavage of adenosine to inosine and NH3, the latter can be accurately determined by indophenol method. The assay system was optimized to deliver a good performance and could tolerate the addition of inorganic salts and many nutrition components to the assay mixtures. Adenosine could be accurately determined by this assay using 96-well microplates. Spike and recovery tests showed that this assay can accurately and reproducibly determine increases in adenosine in fermentation broth without any pretreatment to remove proteins and potentially interfering low-molecular-weight molecules. This assay was also applied to high-throughput screening for high adenosine-producing strains. The high selectivity and accuracy of the ADA assay provides rapid and high-throughput analysis of adenosine in large numbers of samples. PMID:25580842

Scalable Prediction of Energy Consumption using Incremental Time Series Clustering

Energy Technology Data Exchange (ETDEWEB)

Simmhan, Yogesh; Noor, Muhammad Usman

2013-10-09

Time series datasets are a canonical form of high velocity Big Data, and often generated by pervasive sensors, such as found in smart infrastructure. Performing predictive analytics on time series data can be computationally complex, and requires approximation techniques. In this paper, we motivate this problem using a real application from the smart grid domain. We propose an incremental clustering technique, along with a novel affinity score for determining cluster similarity, which help reduce the prediction error for cumulative time series within a cluster. We evaluate this technique, along with optimizations, using real datasets from smart meters, totaling ~700,000 data points, and show the efficacy of our techniques in improving the prediction error of time series data within polynomial time.

High throughput nonparametric probability density estimation.

Science.gov (United States)

Farmer, Jenny; Jacobs, Donald

2018-01-01

In high throughput applications, such as those found in bioinformatics and finance, it is important to determine accurate probability distribution functions despite only minimal information about data characteristics, and without using human subjectivity. Such an automated process for univariate data is implemented to achieve this goal by merging the maximum entropy method with single order statistics and maximum likelihood. The only required properties of the random variables are that they are continuous and that they are, or can be approximated as, independent and identically distributed. A quasi-log-likelihood function based on single order statistics for sampled uniform random data is used to empirically construct a sample size invariant universal scoring function. Then a probability density estimate is determined by iteratively improving trial cumulative distribution functions, where better estimates are quantified by the scoring function that identifies atypical fluctuations. This criterion resists under and over fitting data as an alternative to employing the Bayesian or Akaike information criterion. Multiple estimates for the probability density reflect uncertainties due to statistical fluctuations in random samples. Scaled quantile residual plots are also introduced as an effective diagnostic to visualize the quality of the estimated probability densities. Benchmark tests show that estimates for the probability density function (PDF) converge to the true PDF as sample size increases on particularly difficult test probability densities that include cases with discontinuities, multi-resolution scales, heavy tails, and singularities. These results indicate the method has general applicability for high throughput statistical inference.

High-throughput screening for industrial enzyme production hosts by droplet microfluidics

DEFF Research Database (Denmark)

Sjostrom, Staffan L.; Bai, Yunpeng; Huang, Mingtao

2014-01-01

A high-throughput method for single cell screening by microfluidic droplet sorting is applied to a whole-genome mutated yeast cell library yielding improved production hosts of secreted industrial enzymes. The sorting method is validated by enriching a yeast strain 14 times based on its α......-amylase production, close to the theoretical maximum enrichment. Furthermore, a 105 member yeast cell library is screened yielding a clone with a more than 2-fold increase in α-amylase production. The increase in enzyme production results from an improvement of the cellular functions of the production host...

Adaptive time-variant models for fuzzy-time-series forecasting.

Science.gov (United States)

Wong, Wai-Keung; Bai, Enjian; Chu, Alice Wai-Ching

2010-12-01

A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, and other domains. Related studies mainly focus on three factors, namely, the partition of discourse, the content of forecasting rules, and the methods of defuzzification, all of which greatly influence the prediction accuracy of forecasting models. These studies use fixed analysis window sizes for forecasting. In this paper, an adaptive time-variant fuzzy-time-series forecasting model (ATVF) is proposed to improve forecasting accuracy. The proposed model automatically adapts the analysis window size of fuzzy time series based on the prediction accuracy in the training phase and uses heuristic rules to generate forecasting values in the testing phase. The performance of the ATVF model is tested using both simulated and actual time series including the enrollments at the University of Alabama, Tuscaloosa, and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). The experiment results show that the proposed ATVF model achieves a significant improvement in forecasting accuracy as compared to other fuzzy-time-series forecasting models.

Time Series Analysis and Forecasting by Example

CERN Document Server

Bisgaard, Soren

2011-01-01

An intuition-based approach enables you to master time series analysis with ease Time Series Analysis and Forecasting by Example provides the fundamental techniques in time series analysis using various examples. By introducing necessary theory through examples that showcase the discussed topics, the authors successfully help readers develop an intuitive understanding of seemingly complicated time series models and their implications. The book presents methodologies for time series analysis in a simplified, example-based approach. Using graphics, the authors discuss each presented example in

Alignment of high-throughput sequencing data inside in-memory databases.

Science.gov (United States)

Firnkorn, Daniel; Knaup-Gregori, Petra; Lorenzo Bermejo, Justo; Ganzinger, Matthias

2014-01-01

In times of high-throughput DNA sequencing techniques, performance-capable analysis of DNA sequences is of high importance. Computer supported DNA analysis is still an intensive time-consuming task. In this paper we explore the potential of a new In-Memory database technology by using SAP's High Performance Analytic Appliance (HANA). We focus on read alignment as one of the first steps in DNA sequence analysis. In particular, we examined the widely used Burrows-Wheeler Aligner (BWA) and implemented stored procedures in both, HANA and the free database system MySQL, to compare execution time and memory management. To ensure that the results are comparable, MySQL has been running in memory as well, utilizing its integrated memory engine for database table creation. We implemented stored procedures, containing exact and inexact searching of DNA reads within the reference genome GRCh37. Due to technical restrictions in SAP HANA concerning recursion, the inexact matching problem could not be implemented on this platform. Hence, performance analysis between HANA and MySQL was made by comparing the execution time of the exact search procedures. Here, HANA was approximately 27 times faster than MySQL which means, that there is a high potential within the new In-Memory concepts, leading to further developments of DNA analysis procedures in the future.

Time series with tailored nonlinearities

Science.gov (United States)

Räth, C.; Laut, I.

2015-10-01

It is demonstrated how to generate time series with tailored nonlinearities by inducing well-defined constraints on the Fourier phases. Correlations between the phase information of adjacent phases and (static and dynamic) measures of nonlinearities are established and their origin is explained. By applying a set of simple constraints on the phases of an originally linear and uncorrelated Gaussian time series, the observed scaling behavior of the intensity distribution of empirical time series can be reproduced. The power law character of the intensity distributions being typical for, e.g., turbulence and financial data can thus be explained in terms of phase correlations.

Quantifying Selection with Pool-Seq Time Series Data.

Science.gov (United States)

Taus, Thomas; Futschik, Andreas; Schlötterer, Christian

2017-11-01

Allele frequency time series data constitute a powerful resource for unraveling mechanisms of adaptation, because the temporal dimension captures important information about evolutionary forces. In particular, Evolve and Resequence (E&R), the whole-genome sequencing of replicated experimentally evolving populations, is becoming increasingly popular. Based on computer simulations several studies proposed experimental parameters to optimize the identification of the selection targets. No such recommendations are available for the underlying parameters selection strength and dominance. Here, we introduce a highly accurate method to estimate selection parameters from replicated time series data, which is fast enough to be applied on a genome scale. Using this new method, we evaluate how experimental parameters can be optimized to obtain the most reliable estimates for selection parameters. We show that the effective population size (Ne) and the number of replicates have the largest impact. Because the number of time points and sequencing coverage had only a minor effect, we suggest that time series analysis is feasible without major increase in sequencing costs. We anticipate that time series analysis will become routine in E&R studies. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit

Energy Technology Data Exchange (ETDEWEB)

Pronk, Sander [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Pall, Szilard [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Schulz, Roland [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Larsson, Per [Univ. of Virginia, Charlottesville, VA (United States); Bjelkmar, Par [Science for Life Lab., Stockholm (Sweden); Stockholm Univ., Stockholm (Sweden); Apostolov, Rossen [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Shirts, Michael R. [Univ. of Virginia, Charlottesville, VA (United States); Smith, Jeremy C. [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kasson, Peter M. [Univ. of Virginia, Charlottesville, VA (United States); van der Spoel, David [Science for Life Lab., Stockholm (Sweden); Uppsala Univ., Uppsala (Sweden); Hess, Berk [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Lindahl, Erik [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Stockholm Univ., Stockholm (Sweden)

2013-02-13

In this study, molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. As a result, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.

Prototype Systems Containing Human Cytochrome P450 for High-Throughput Real-Time Detection of DNA Damage by Compounds That Form DNA-Reactive Metabolites.

Science.gov (United States)

Brito Palma, Bernardo; Fisher, Charles W; Rueff, José; Kranendonk, Michel

2016-05-16

The formation of reactive metabolites through biotransformation is the suspected cause of many adverse drug reactions. Testing for the propensity of a drug to form reactive metabolites has increasingly become an integral part of lead-optimization strategy in drug discovery. DNA reactivity is one undesirable facet of a drug or its metabolites and can lead to increased risk of cancer and reproductive toxicity. Many drugs are metabolized by cytochromes P450 in the liver and other tissues, and these reactions can generate hard electrophiles. These hard electrophilic reactive metabolites may react with DNA and may be detected in standard in vitro genotoxicity assays; however, the majority of these assays fall short due to the use of animal-derived organ extracts that inadequately represent human metabolism. The current study describes the development of bacterial systems that efficiently detect DNA-damaging electrophilic reactive metabolites generated by human P450 biotransformation. These assays use a GFP reporter system that detects DNA damage through induction of the SOS response and a GFP reporter to control for cytotoxicity. Two human CYP1A2-competent prototypes presented here have appropriate characteristics for the detection of DNA-damaging reactive metabolites in a high-throughput manner. The advantages of this approach include a short assay time (120-180 min) with real-time measurement, sensitivity to small amounts of compound, and adaptability to a microplate format. These systems are suitable for high-throughput assays and can serve as prototypes for the development of future enhanced versions.

A high-throughput investigation of Fe-Cr-Al as a novel high-temperature coating for nuclear cladding materials.

Science.gov (United States)

Bunn, Jonathan Kenneth; Fang, Randy L; Albing, Mark R; Mehta, Apurva; Kramer, Matthew J; Besser, Matthew F; Hattrick-Simpers, Jason R

2015-07-10

High-temperature alloy coatings that can resist oxidation are urgently needed as nuclear cladding materials to mitigate the danger of hydrogen explosions during meltdown. Here we apply a combination of computationally guided materials synthesis, high-throughput structural characterization and data analysis tools to investigate the feasibility of coatings from the Fe–Cr–Al alloy system. Composition-spread samples were synthesized to cover the region of the phase diagram previous bulk studies have identified as forming protective oxides. The metallurgical and oxide phase evolution were studied via in situ synchrotron glancing incidence x-ray diffraction at temperatures up to 690 K. A composition region with an Al concentration greater than 3.08 at%, and between 20.0 at% and 32.9 at% Cr showed the least overall oxide growth. Subsequently, a series of samples were deposited on stubs and their oxidation behavior at 1373 K was observed. The continued presence of a passivating oxide was confirmed in this region over a period of 6 h.

High-throughput characterization for solar fuels materials discovery

Science.gov (United States)

Mitrovic, Slobodan; Becerra, Natalie; Cornell, Earl; Guevarra, Dan; Haber, Joel; Jin, Jian; Jones, Ryan; Kan, Kevin; Marcin, Martin; Newhouse, Paul; Soedarmadji, Edwin; Suram, Santosh; Xiang, Chengxiang; Gregoire, John; High-Throughput Experimentation Team

2014-03-01

In this talk I will present the status of the High-Throughput Experimentation (HTE) project of the Joint Center for Artificial Photosynthesis (JCAP). JCAP is an Energy Innovation Hub of the U.S. Department of Energy with a mandate to deliver a solar fuel generator based on an integrated photoelectrochemical cell (PEC). However, efficient and commercially viable catalysts or light absorbers for the PEC do not exist. The mission of HTE is to provide the accelerated discovery through combinatorial synthesis and rapid screening of material properties. The HTE pipeline also features high-throughput material characterization using x-ray diffraction and x-ray photoemission spectroscopy (XPS). In this talk I present the currently operating pipeline and focus on our combinatorial XPS efforts to build the largest free database of spectra from mixed-metal oxides, nitrides, sulfides and alloys. This work was performed at Joint Center for Artificial Photosynthesis, a DOE Energy Innovation Hub, supported through the Office of Science of the U.S. Department of Energy under Award No. DE-SC0004993.

Clustering of financial time series

Science.gov (United States)

D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo

2013-05-01

This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.

Fluorescent foci quantitation for high-throughput analysis

Directory of Open Access Journals (Sweden)

Elena Ledesma-Fernández

2015-06-01

Full Text Available A number of cellular proteins localize to discrete foci within cells, for example DNA repair proteins, microtubule organizing centers, P bodies or kinetochores. It is often possible to measure the fluorescence emission from tagged proteins within these foci as a surrogate for the concentration of that specific protein. We wished to develop tools that would allow quantitation of fluorescence foci intensities in high-throughput studies. As proof of principle we have examined the kinetochore, a large multi-subunit complex that is critical for the accurate segregation of chromosomes during cell division. Kinetochore perturbations lead to aneuploidy, which is a hallmark of cancer cells. Hence, understanding kinetochore homeostasis and regulation are important for a global understanding of cell division and genome integrity. The 16 budding yeast kinetochores colocalize within the nucleus to form a single focus. Here we have created a set of freely-available tools to allow high-throughput quantitation of kinetochore foci fluorescence. We use this ‘FociQuant’ tool to compare methods of kinetochore quantitation and we show proof of principle that FociQuant can be used to identify changes in kinetochore protein levels in a mutant that affects kinetochore function. This analysis can be applied to any protein that forms discrete foci in cells.

High-throughput electrical characterization for robust overlay lithography control

Science.gov (United States)

Devender, Devender; Shen, Xumin; Duggan, Mark; Singh, Sunil; Rullan, Jonathan; Choo, Jae; Mehta, Sohan; Tang, Teck Jung; Reidy, Sean; Holt, Jonathan; Kim, Hyung Woo; Fox, Robert; Sohn, D. K.

2017-03-01

Realizing sensitive, high throughput and robust overlay measurement is a challenge in current 14nm and advanced upcoming nodes with transition to 300mm and upcoming 450mm semiconductor manufacturing, where slight deviation in overlay has significant impact on reliability and yield1). Exponentially increasing number of critical masks in multi-patterning lithoetch, litho-etch (LELE) and subsequent LELELE semiconductor processes require even tighter overlay specification2). Here, we discuss limitations of current image- and diffraction- based overlay measurement techniques to meet these stringent processing requirements due to sensitivity, throughput and low contrast3). We demonstrate a new electrical measurement based technique where resistance is measured for a macro with intentional misalignment between two layers. Overlay is quantified by a parabolic fitting model to resistance where minima and inflection points are extracted to characterize overlay control and process window, respectively. Analyses using transmission electron microscopy show good correlation between actual overlay performance and overlay obtained from fitting. Additionally, excellent correlation of overlay from electrical measurements to existing image- and diffraction- based techniques is found. We also discuss challenges of integrating electrical measurement based approach in semiconductor manufacturing from Back End of Line (BEOL) perspective. Our findings open up a new pathway for accessing simultaneous overlay as well as process window and margins from a robust, high throughput and electrical measurement approach.

A High-Throughput, High-Accuracy System-Level Simulation Framework for System on Chips

Directory of Open Access Journals (Sweden)

Guanyi Sun

2011-01-01

Full Text Available Today's System-on-Chips (SoCs design is extremely challenging because it involves complicated design tradeoffs and heterogeneous design expertise. To explore the large solution space, system architects have to rely on system-level simulators to identify an optimized SoC architecture. In this paper, we propose a system-level simulation framework, System Performance Simulation Implementation Mechanism, or SPSIM. Based on SystemC TLM2.0, the framework consists of an executable SoC model, a simulation tool chain, and a modeling methodology. Compared with the large body of existing research in this area, this work is aimed at delivering a high simulation throughput and, at the same time, guaranteeing a high accuracy on real industrial applications. Integrating the leading TLM techniques, our simulator can attain a simulation speed that is not slower than that of the hardware execution by a factor of 35 on a set of real-world applications. SPSIM incorporates effective timing models, which can achieve a high accuracy after hardware-based calibration. Experimental results on a set of mobile applications proved that the difference between the simulated and measured results of timing performance is within 10%, which in the past can only be attained by cycle-accurate models.

Microengineering methods for cell-based microarrays and high-throughput drug-screening applications

International Nuclear Information System (INIS)

Xu Feng; Wu Jinhui; Wang Shuqi; Gurkan, Umut Atakan; Demirci, Utkan; Durmus, Naside Gozde

2011-01-01

Screening for effective therapeutic agents from millions of drug candidates is costly, time consuming, and often faces concerns due to the extensive use of animals. To improve cost effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems has facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell-based drug-screening models which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell-based drug-screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds great potential to provide repeatable 3D cell-based constructs with high temporal, spatial control and versatility.

Microengineering methods for cell-based microarrays and high-throughput drug-screening applications

Energy Technology Data Exchange (ETDEWEB)

Xu Feng; Wu Jinhui; Wang Shuqi; Gurkan, Umut Atakan; Demirci, Utkan [Department of Medicine, Demirci Bio-Acoustic-MEMS in Medicine (BAMM) Laboratory, Center for Biomedical Engineering, Brigham and Women' s Hospital, Harvard Medical School, Boston, MA (United States); Durmus, Naside Gozde, E-mail: udemirci@rics.bwh.harvard.edu [School of Engineering and Division of Biology and Medicine, Brown University, Providence, RI (United States)

2011-09-15

Screening for effective therapeutic agents from millions of drug candidates is costly, time consuming, and often faces concerns due to the extensive use of animals. To improve cost effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems has facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell-based drug-screening models which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell-based drug-screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds great potential to provide repeatable 3D cell-based constructs with high temporal, spatial control and versatility.

High Throughput In Situ XAFS Screening of Catalysts

International Nuclear Information System (INIS)

Tsapatsaris, Nikolaos; Beesley, Angela M.; Weiher, Norbert; Tatton, Helen; Schroeder, Sven L. M.; Dent, Andy J.; Mosselmans, Frederick J. W.; Tromp, Moniek; Russu, Sergio; Evans, John; Harvey, Ian; Hayama, Shu

2007-01-01

We outline and demonstrate the feasibility of high-throughput (HT) in situ XAFS for synchrotron radiation studies. An XAS data acquisition and control system for the analysis of dynamic materials libraries under control of temperature and gaseous environments has been developed. The system is compatible with the 96-well industry standard and coupled to multi-stream quadrupole mass spectrometry (QMS) analysis of reactor effluents. An automated analytical workflow generates data quickly compared to traditional individual spectrum acquisition and analyses them in quasi-real time using an HT data analysis tool based on IFFEFIT. The system was used for the automated characterization of a library of 91 catalyst precursors containing ternary combinations of Cu, Pt, and Au on γ-Al2O3, and for the in situ characterization of Au catalysts supported on Al2O3 and TiO2

Advances in analytical tools for high throughput strain engineering

DEFF Research Database (Denmark)

Marcellin, Esteban; Nielsen, Lars Keld

2018-01-01

The emergence of inexpensive, base-perfect genome editing is revolutionising biology. Modern industrial biotechnology exploits the advances in genome editing in combination with automation, analytics and data integration to build high-throughput automated strain engineering pipelines also known...... as biofoundries. Biofoundries replace the slow and inconsistent artisanal processes used to build microbial cell factories with an automated design–build–test cycle, considerably reducing the time needed to deliver commercially viable strains. Testing and hence learning remains relatively shallow, but recent...... advances in analytical chemistry promise to increase the depth of characterization possible. Analytics combined with models of cellular physiology in automated systems biology pipelines should enable deeper learning and hence a steeper pitch of the learning cycle. This review explores the progress...

: Signal Decomposition of High Resolution Time Series River data to Separate Local and Regional Components of Conductivity

Science.gov (United States)

Signal processing techniques were applied to high-resolution time series data obtained from conductivity loggers placed upstream and downstream of a wastewater treatment facility along a river. Data was collected over 14-60 days, and several seasons. The power spectral densit...

Data Mining Smart Energy Time Series

Directory of Open Access Journals (Sweden)

Janina POPEANGA

2015-07-01

Full Text Available With the advent of smart metering technology the amount of energy data will increase significantly and utilities industry will have to face another big challenge - to find relationships within time-series data and even more - to analyze such huge numbers of time series to find useful patterns and trends with fast or even real-time response. This study makes a small review of the literature in the field, trying to demonstrate how essential is the application of data mining techniques in the time series to make the best use of this large quantity of data, despite all the difficulties. Also, the most important Time Series Data Mining techniques are presented, highlighting their applicability in the energy domain.

High-throughput heterodyne thermoreflectance: Application to thermal conductivity measurements of a Fe-Si-Ge thin film alloy library

Science.gov (United States)

d'Acremont, Quentin; Pernot, Gilles; Rampnoux, Jean-Michel; Furlan, Andrej; Lacroix, David; Ludwig, Alfred; Dilhaire, Stefan

2017-07-01

A High-Throughput Time-Domain ThermoReflectance (HT-TDTR) technique was developed to perform fast thermal conductivity measurements with minimum user actions required. This new setup is based on a heterodyne picosecond thermoreflectance system. The use of two different laser oscillators has been proven to reduce the acquisition time by two orders of magnitude and avoid the experimental artefacts usually induced by moving the elements present in TDTR systems. An amplitude modulation associated to a lock-in detection scheme is included to maintain a high sensitivity to thermal properties. We demonstrate the capabilities of the HT-TDTR setup to perform high-throughput thermal analysis by mapping thermal conductivity and interface resistances of a ternary thin film silicide library FexSiyGe100-x-y (20 deposited by wedge-type multi-layer method on a 100 mm diameter sapphire wafer offering more than 300 analysis areas of different ternary alloy compositions.

Subnuclear foci quantification using high-throughput 3D image cytometry

Science.gov (United States)

Wadduwage, Dushan N.; Parrish, Marcus; Choi, Heejin; Engelward, Bevin P.; Matsudaira, Paul; So, Peter T. C.

2015-07-01

Ionising radiation causes various types of DNA damages including double strand breaks (DSBs). DSBs are often recognized by DNA repair protein ATM which forms gamma-H2AX foci at the site of the DSBs that can be visualized using immunohistochemistry. However most of such experiments are of low throughput in terms of imaging and image analysis techniques. Most of the studies still use manual counting or classification. Hence they are limited to counting a low number of foci per cell (5 foci per nucleus) as the quantification process is extremely labour intensive. Therefore we have developed a high throughput instrumentation and computational pipeline specialized for gamma-H2AX foci quantification. A population of cells with highly clustered foci inside nuclei were imaged, in 3D with submicron resolution, using an in-house developed high throughput image cytometer. Imaging speeds as high as 800 cells/second in 3D were achieved by using HiLo wide-field depth resolved imaging and a remote z-scanning technique. Then the number of foci per cell nucleus were quantified using a 3D extended maxima transform based algorithm. Our results suggests that while most of the other 2D imaging and manual quantification studies can count only up to about 5 foci per nucleus our method is capable of counting more than 100. Moreover we show that 3D analysis is significantly superior compared to the 2D techniques.

CauseMap: fast inference of causality from complex time series.

Science.gov (United States)

Maher, M Cyrus; Hernandez, Ryan D

2015-01-01

Background. Establishing health-related causal relationships is a central pursuit in biomedical research. Yet, the interdependent non-linearity of biological systems renders causal dynamics laborious and at times impractical to disentangle. This pursuit is further impeded by the dearth of time series that are sufficiently long to observe and understand recurrent patterns of flux. However, as data generation costs plummet and technologies like wearable devices democratize data collection, we anticipate a coming surge in the availability of biomedically-relevant time series data. Given the life-saving potential of these burgeoning resources, it is critical to invest in the development of open source software tools that are capable of drawing meaningful insight from vast amounts of time series data. Results. Here we present CauseMap, the first open source implementation of convergent cross mapping (CCM), a method for establishing causality from long time series data (≳25 observations). Compared to existing time series methods, CCM has the advantage of being model-free and robust to unmeasured confounding that could otherwise induce spurious associations. CCM builds on Takens' Theorem, a well-established result from dynamical systems theory that requires only mild assumptions. This theorem allows us to reconstruct high dimensional system dynamics using a time series of only a single variable. These reconstructions can be thought of as shadows of the true causal system. If reconstructed shadows can predict points from opposing time series, we can infer that the corresponding variables are providing views of the same causal system, and so are causally related. Unlike traditional metrics, this test can establish the directionality of causation, even in the presence of feedback loops. Furthermore, since CCM can extract causal relationships from times series of, e.g., a single individual, it may be a valuable tool to personalized medicine. We implement CCM in Julia, a

CauseMap: fast inference of causality from complex time series

Directory of Open Access Journals (Sweden)

M. Cyrus Maher

2015-03-01

Full Text Available Background. Establishing health-related causal relationships is a central pursuit in biomedical research. Yet, the interdependent non-linearity of biological systems renders causal dynamics laborious and at times impractical to disentangle. This pursuit is further impeded by the dearth of time series that are sufficiently long to observe and understand recurrent patterns of flux. However, as data generation costs plummet and technologies like wearable devices democratize data collection, we anticipate a coming surge in the availability of biomedically-relevant time series data. Given the life-saving potential of these burgeoning resources, it is critical to invest in the development of open source software tools that are capable of drawing meaningful insight from vast amounts of time series data.Results. Here we present CauseMap, the first open source implementation of convergent cross mapping (CCM, a method for establishing causality from long time series data (≳25 observations. Compared to existing time series methods, CCM has the advantage of being model-free and robust to unmeasured confounding that could otherwise induce spurious associations. CCM builds on Takens’ Theorem, a well-established result from dynamical systems theory that requires only mild assumptions. This theorem allows us to reconstruct high dimensional system dynamics using a time series of only a single variable. These reconstructions can be thought of as shadows of the true causal system. If reconstructed shadows can predict points from opposing time series, we can infer that the corresponding variables are providing views of the same causal system, and so are causally related. Unlike traditional metrics, this test can establish the directionality of causation, even in the presence of feedback loops. Furthermore, since CCM can extract causal relationships from times series of, e.g., a single individual, it may be a valuable tool to personalized medicine. We implement

A high throughput array microscope for the mechanical characterization of biomaterials

Science.gov (United States)

Cribb, Jeremy; Osborne, Lukas D.; Hsiao, Joe Ping-Lin; Vicci, Leandra; Meshram, Alok; O'Brien, E. Tim; Spero, Richard Chasen; Taylor, Russell; Superfine, Richard

2015-02-01

In the last decade, the emergence of high throughput screening has enabled the development of novel drug therapies and elucidated many complex cellular processes. Concurrently, the mechanobiology community has developed tools and methods to show that the dysregulation of biophysical properties and the biochemical mechanisms controlling those properties contribute significantly to many human diseases. Despite these advances, a complete understanding of the connection between biomechanics and disease will require advances in instrumentation that enable parallelized, high throughput assays capable of probing complex signaling pathways, studying biology in physiologically relevant conditions, and capturing specimen and mechanical heterogeneity. Traditional biophysical instruments are unable to meet this need. To address the challenge of large-scale, parallelized biophysical measurements, we have developed an automated array high-throughput microscope system that utilizes passive microbead diffusion to characterize mechanical properties of biomaterials. The instrument is capable of acquiring data on twelve-channels simultaneously, where each channel in the system can independently drive two-channel fluorescence imaging at up to 50 frames per second. We employ this system to measure the concentration-dependent apparent viscosity of hyaluronan, an essential polymer found in connective tissue and whose expression has been implicated in cancer progression.

Predicting chaotic time series

International Nuclear Information System (INIS)

Farmer, J.D.; Sidorowich, J.J.

1987-01-01

We present a forecasting technique for chaotic data. After embedding a time series in a state space using delay coordinates, we ''learn'' the induced nonlinear mapping using local approximation. This allows us to make short-term predictions of the future behavior of a time series, using information based only on past values. We present an error estimate for this technique, and demonstrate its effectiveness by applying it to several examples, including data from the Mackey-Glass delay differential equation, Rayleigh-Benard convection, and Taylor-Couette flow

Developing a novel fiber optic fluorescence device for multiplexed high-throughput cytotoxic screening.

Science.gov (United States)

Lee, Dennis; Barnes, Stephen

2010-01-01

The need for new pharmacological agents is unending. Yet the drug discovery process has changed substantially over the past decade and continues to evolve in response to new technologies. There is presently a high demand to reduce discovery time by improving specific lab disciplines and developing new technology platforms in the area of cell-based assay screening. Here we present the developmental concept and early stage testing of the Ab-Sniffer, a novel fiber optic fluorescence device for high-throughput cytotoxicity screening using an immobilized whole cell approach. The fused silica fibers are chemically functionalized with biotin to provide interaction with fluorescently labeled, streptavidin functionalized alginate-chitosan microspheres. The microspheres are also functionalized with Concanavalin A to facilitate binding to living cells. By using lymphoma cells and rituximab in an adaptation of a well-known cytotoxicity protocol we demonstrate the utility of the Ab-Sniffer for functional screening of potential drug compounds rather than indirect, non-functional screening via binding assay. The platform can be extended to any assay capable of being tied to a fluorescence response including multiple target cells in each well of a multi-well plate for high-throughput screening.

High-throughput bioinformatics with the Cyrille2 pipeline system.

NARCIS (Netherlands)

Fiers, M.W.E.J.; Burgt, van der A.; Datema, E.; Groot, de J.C.W.; Ham, van R.C.H.J.

2008-01-01

Background - Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses

Definition, modeling and simulation of a grid computing system for high throughput computing

CERN Document Server

Caron, E; Tsaregorodtsev, A Yu

2006-01-01

In this paper, we study and compare grid and global computing systems and outline the benefits of having an hybrid system called dirac. To evaluate the dirac scheduling for high throughput computing, a new model is presented and a simulator was developed for many clusters of heterogeneous nodes belonging to a local network. These clusters are assumed to be connected to each other through a global network and each cluster is managed via a local scheduler which is shared by many users. We validate our simulator by comparing the experimental and analytical results of a M/M/4 queuing system. Next, we do the comparison with a real batch system and we obtain an average error of 10.5% for the response time and 12% for the makespan. We conclude that the simulator is realistic and well describes the behaviour of a large-scale system. Thus we can study the scheduling of our system called dirac in a high throughput context. We justify our decentralized, adaptive and oppor! tunistic approach in comparison to a centralize...

Mosquitoes meet microfluidics: High-throughput microfluidic tools for insect-parasite ecology in field conditions

Science.gov (United States)

Prakash, Manu; Mukundarajan, Haripriya

2013-11-01

A simple bite from an insect is the transmission mechanism for many deadly diseases worldwide--including malaria, yellow fever, west nile and dengue. Very little is known about how populations of numerous insect species and disease-causing parasites interact in their natural habitats due to a lack of measurement techniques. At present, vector surveillance techniques involve manual capture by using humans as live bait, which is hard to justify on ethical grounds. Individual mosquitoes are manually dissected to isolate salivary glands to detect sporozites. With typical vector infection rates being very low even in endemic areas, it is almost impossible to get an accurate picture of disease distribution, in both space and time. Here we present novel high-throughput microfluidic tools for vector surveillance, specifically mosquitoes. A two-dimensional high density array with baits provide an integrated platform for multiplex PCR for detection of both vector and parasite species. Combining techniques from engineering and field ecology, methods and tools developed here will enable high-throughput measurement of infection rates for a number of diseases in mosquito populations in field conditions. Pew Foundation.

High-throughput preparation and testing of ion-exchanged zeolites

International Nuclear Information System (INIS)

Janssen, K.P.F.; Paul, J.S.; Sels, B.F.; Jacobs, P.A.

2007-01-01

A high-throughput research platform was developed for the preparation and subsequent catalytic liquid-phase screening of ion-exchanged zeolites, for instance with regard to their use as heterogeneous catalysts. In this system aqueous solutions and other liquid as well as solid reagents are employed as starting materials and 24 samples are prepared on a library plate with a 4 x 6 layout. Volumetric dispensing of metal precursor solutions, weighing of zeolite and subsequent mixing/washing cycles of the starting materials and distributing reaction mixtures to the library plate are automatically performed by liquid and solid handlers controlled by a single common and easy-to-use programming software interface. The thus prepared materials are automatically contacted with reagent solutions, heated, stirred and sampled continuously using a modified liquid handling. The high-throughput platform is highly promising in enhancing synthesis of catalysts and their screening. In this paper the preparation of lanthanum-exchanged NaY zeolites (LaNaY) on the platform is reported, along with their use as catalyst for the conversion of renewables

Measuring multiscaling in financial time-series

International Nuclear Information System (INIS)

Buonocore, R.J.; Aste, T.; Di Matteo, T.

2016-01-01

We discuss the origin of multiscaling in financial time-series and investigate how to best quantify it. Our methodology consists in separating the different sources of measured multifractality by analyzing the multi/uni-scaling behavior of synthetic time-series with known properties. We use the results from the synthetic time-series to interpret the measure of multifractality of real log-returns time-series. The main finding is that the aggregation horizon of the returns can introduce a strong bias effect on the measure of multifractality. This effect can become especially important when returns distributions have power law tails with exponents in the range (2, 5). We discuss the right aggregation horizon to mitigate this bias.

A Self-Reporting Photocatalyst for Online Fluorescence Monitoring of High Throughput RAFT Polymerization.

Science.gov (United States)

Yeow, Jonathan; Joshi, Sanket; Chapman, Robert; Boyer, Cyrille Andre Jean Marie

2018-04-25

Translating controlled/living radical polymerization (CLRP) from batch to the high throughput production of polymer libraries presents several challenges in terms of both polymer synthesis and characterization. Although recently there have been significant advances in the field of low volume, high throughput CLRP, techniques able to simultaneously monitor multiple polymerizations in an "online" manner have not yet been developed. Here, we report our discovery that 5,10,15,20-tetraphenyl-21H,23H-porphine zinc (ZnTPP) is a self-reporting photocatalyst that can mediate PET-RAFT polymerization as well as report on monomer conversion via changes in its fluorescence properties. This enables the use of a microplate reader to conduct high throughput "online" monitoring of PET-RAFT polymerizations performed directly in 384-well, low volume microtiter plates. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Time averaging, ageing and delay analysis of financial time series

Science.gov (United States)

Cherstvy, Andrey G.; Vinod, Deepak; Aghion, Erez; Chechkin, Aleksei V.; Metzler, Ralf

2017-06-01

We introduce three strategies for the analysis of financial time series based on time averaged observables. These comprise the time averaged mean squared displacement (MSD) as well as the ageing and delay time methods for varying fractions of the financial time series. We explore these concepts via statistical analysis of historic time series for several Dow Jones Industrial indices for the period from the 1960s to 2015. Remarkably, we discover a simple universal law for the delay time averaged MSD. The observed features of the financial time series dynamics agree well with our analytical results for the time averaged measurables for geometric Brownian motion, underlying the famed Black-Scholes-Merton model. The concepts we promote here are shown to be useful for financial data analysis and enable one to unveil new universal features of stock market dynamics.

Signal Decomposition of High Resolution Time Series River Data to Separate Local and Regional Components of Conductivity

Science.gov (United States)

Signal processing techniques were applied to high-resolution time series data obtained from conductivity loggers placed upstream and downstream of an oil and gas wastewater treatment facility along a river. Data was collected over 14-60 days. The power spectral density was us...

High-throughput fragment screening by affinity LC-MS.

Science.gov (United States)

Duong-Thi, Minh-Dao; Bergström, Maria; Fex, Tomas; Isaksson, Roland; Ohlson, Sten

2013-02-01

Fragment screening, an emerging approach for hit finding in drug discovery, has recently been proven effective by its first approved drug, vemurafenib, for cancer treatment. Techniques such as nuclear magnetic resonance, surface plasmon resonance, and isothemal titration calorimetry, with their own pros and cons, have been employed for screening fragment libraries. As an alternative approach, screening based on high-performance liquid chromatography separation has been developed. In this work, we present weak affinity LC/MS as a method to screen fragments under high-throughput conditions. Affinity-based capillary columns with immobilized thrombin were used to screen a collection of 590 compounds from a fragment library. The collection was divided into 11 mixtures (each containing 35 to 65 fragments) and screened by MS detection. The primary screening was performed in 3500 fragments per day). Thirty hits were defined, which subsequently entered a secondary screening using an active site-blocked thrombin column for confirmation of specificity. One hit showed selective binding to thrombin with an estimated dissociation constant (K (D)) in the 0.1 mM range. This study shows that affinity LC/MS is characterized by high throughput, ease of operation, and low consumption of target and fragments, and therefore it promises to be a valuable method for fragment screening.

Multiplex enrichment quantitative PCR (ME-qPCR): a high-throughput, highly sensitive detection method for GMO identification.

Science.gov (United States)

Fu, Wei; Zhu, Pengyu; Wei, Shuang; Zhixin, Du; Wang, Chenguang; Wu, Xiyang; Li, Feiwu; Zhu, Shuifang

2017-04-01

Among all of the high-throughput detection methods, PCR-based methodologies are regarded as the most cost-efficient and feasible methodologies compared with the next-generation sequencing or ChIP-based methods. However, the PCR-based methods can only achieve multiplex detection up to 15-plex due to limitations imposed by the multiplex primer interactions. The detection throughput cannot meet the demands of high-throughput detection, such as SNP or gene expression analysis. Therefore, in our study, we have developed a new high-throughput PCR-based detection method, multiplex enrichment quantitative PCR (ME-qPCR), which is a combination of qPCR and nested PCR. The GMO content detection results in our study showed that ME-qPCR could achieve high-throughput detection up to 26-plex. Compared to the original qPCR, the Ct values of ME-qPCR were lower for the same group, which showed that ME-qPCR sensitivity is higher than the original qPCR. The absolute limit of detection for ME-qPCR could achieve levels as low as a single copy of the plant genome. Moreover, the specificity results showed that no cross-amplification occurred for irrelevant GMO events. After evaluation of all of the parameters, a practical evaluation was performed with different foods. The more stable amplification results, compared to qPCR, showed that ME-qPCR was suitable for GMO detection in foods. In conclusion, ME-qPCR achieved sensitive, high-throughput GMO detection in complex substrates, such as crops or food samples. In the future, ME-qPCR-based GMO content identification may positively impact SNP analysis or multiplex gene expression of food or agricultural samples. Graphical abstract For the first-step amplification, four primers (A, B, C, and D) have been added into the reaction volume. In this manner, four kinds of amplicons have been generated. All of these four amplicons could be regarded as the target of second-step PCR. For the second-step amplification, three parallels have been taken for

Laser-Induced Fluorescence Detection in High-Throughput Screening of Heterogeneous Catalysts and Single Cells Analysis

Energy Technology Data Exchange (ETDEWEB)

Su, Hui [Iowa State Univ., Ames, IA (United States)

2001-01-01

Laser-induced fluorescence detection is one of the most sensitive detection techniques and it has found enormous applications in various areas. The purpose of this research was to develop detection approaches based on laser-induced fluorescence detection in two different areas, heterogeneous catalysts screening and single cell study. First, we introduced laser-induced imaging (LIFI) as a high-throughput screening technique for heterogeneous catalysts to explore the use of this high-throughput screening technique in discovery and study of various heterogeneous catalyst systems. This scheme is based on the fact that the creation or the destruction of chemical bonds alters the fluorescence properties of suitably designed molecules. By irradiating the region immediately above the catalytic surface with a laser, the fluorescence intensity of a selected product or reactant can be imaged by a charge-coupled device (CCD) camera to follow the catalytic activity as a function of time and space. By screening the catalytic activity of vanadium pentoxide catalysts in oxidation of naphthalene, we demonstrated LIFI has good detection performance and the spatial and temporal resolution needed for high-throughput screening of heterogeneous catalysts. The sample packing density can reach up to 250 x 250 subunits/cm₂ for 40-μm wells. This experimental set-up also can screen solid catalysts via near infrared thermography detection.

Laser-Induced Fluorescence Detection in High-Throughput Screening of Heterogeneous Catalysts and Single Cells Analysis

International Nuclear Information System (INIS)

Hui Su

2001-01-01

Laser-induced fluorescence detection is one of the most sensitive detection techniques and it has found enormous applications in various areas. The purpose of this research was to develop detection approaches based on laser-induced fluorescence detection in two different areas, heterogeneous catalysts screening and single cell study. First, we introduced laser-induced imaging (LIFI) as a high-throughput screening technique for heterogeneous catalysts to explore the use of this high-throughput screening technique in discovery and study of various heterogeneous catalyst systems. This scheme is based on the fact that the creation or the destruction of chemical bonds alters the fluorescence properties of suitably designed molecules. By irradiating the region immediately above the catalytic surface with a laser, the fluorescence intensity of a selected product or reactant can be imaged by a charge-coupled device (CCD) camera to follow the catalytic activity as a function of time and space. By screening the catalytic activity of vanadium pentoxide catalysts in oxidation of naphthalene, we demonstrated LIFI has good detection performance and the spatial and temporal resolution needed for high-throughput screening of heterogeneous catalysts. The sample packing density can reach up to 250 x 250 subunits/cm(sub 2) for 40-(micro)m wells. This experimental set-up also can screen solid catalysts via near infrared thermography detection

A gas trapping method for high-throughput metabolic experiments.

Science.gov (United States)

Krycer, James R; Diskin, Ciana; Nelson, Marin E; Zeng, Xiao-Yi; Fazakerley, Daniel J; James, David E

2018-01-01

Research into cellular metabolism has become more high-throughput, with typical cell-culture experiments being performed in multiwell plates (microplates). This format presents a challenge when trying to collect gaseous products, such as carbon dioxide (CO2), which requires a sealed environment and a vessel separate from the biological sample. To address this limitation, we developed a gas trapping protocol using perforated plastic lids in sealed cell-culture multiwell plates. We used this trap design to measure CO2 production from glucose and fatty acid metabolism, as well as hydrogen sulfide production from cysteine-treated cells. Our data clearly show that this gas trap can be applied to liquid and solid gas-collection media and can be used to study gaseous product generation by both adherent cells and cells in suspension. Since our gas traps can be adapted to multiwell plates of various sizes, they present a convenient, cost-effective solution that can accommodate the trend toward high-throughput measurements in metabolic research.

High-throughput technology for novel SO2 oxidation catalysts

International Nuclear Information System (INIS)

Loskyll, Jonas; Stoewe, Klaus; Maier, Wilhelm F

2011-01-01

We review the state of the art and explain the need for better SO 2 oxidation catalysts for the production of sulfuric acid. A high-throughput technology has been developed for the study of potential catalysts in the oxidation of SO 2 to SO 3 . High-throughput methods are reviewed and the problems encountered with their adaptation to the corrosive conditions of SO 2 oxidation are described. We show that while emissivity-corrected infrared thermography (ecIRT) can be used for primary screening, it is prone to errors because of the large variations in the emissivity of the catalyst surface. UV-visible (UV-Vis) spectrometry was selected instead as a reliable analysis method of monitoring the SO 2 conversion. Installing plain sugar absorbents at reactor outlets proved valuable for the detection and quantitative removal of SO 3 from the product gas before the UV-Vis analysis. We also overview some elements used for prescreening and those remaining after the screening of the first catalyst generations. (topical review)

A high-fidelity weather time series generator using the Markov Chain process on a piecewise level

Science.gov (United States)

Hersvik, K.; Endrerud, O.-E. V.

2017-12-01

A method is developed for generating a set of unique weather time-series based on an existing weather series. The method allows statistically valid weather variations to take place within repeated simulations of offshore operations. The numerous generated time series need to share the same statistical qualities as the original time series. Statistical qualities here refer mainly to the distribution of weather windows available for work, including durations and frequencies of such weather windows, and seasonal characteristics. The method is based on the Markov chain process. The core new development lies in how the Markov Process is used, specifically by joining small pieces of random length time series together rather than joining individual weather states, each from a single time step, which is a common solution found in the literature. This new Markov model shows favorable characteristics with respect to the requirements set forth and all aspects of the validation performed.

On Throughput Maximization in Constant Travel-Time Robotic Cells

OpenAIRE

Milind Dawande; Chelliah Sriskandarajah; Suresh Sethi

2002-01-01

We consider the problem of scheduling operations in bufferless robotic cells that produce identical parts. The objective is to find a cyclic sequence of robot moves that minimizes the long-run average time to produce a part or, equivalently, maximizes the throughput rate. The robot can be moved in simple cycles that produce one unit or, in more complicated cycles, that produce multiple units. Because one-unit cycles are the easiest to understand, implement, and control, they are widely used i...

Robust high-throughput batch screening method in 384-well format with optical in-line resin quantification.

Science.gov (United States)

Kittelmann, Jörg; Ottens, Marcel; Hubbuch, Jürgen

2015-04-15

High-throughput batch screening technologies have become an important tool in downstream process development. Although continuative miniaturization saves time and sample consumption, there is yet no screening process described in the 384-well microplate format. Several processes are established in the 96-well dimension to investigate protein-adsorbent interactions, utilizing between 6.8 and 50 μL resin per well. However, as sample consumption scales with resin volumes and throughput scales with experiments per microplate, they are limited in costs and saved time. In this work, a new method for in-well resin quantification by optical means, applicable in the 384-well format, and resin volumes as small as 0.1 μL is introduced. A HTS batch isotherm process is described, utilizing this new method in combination with optical sample volume quantification for screening of isotherm parameters in 384-well microplates. Results are qualified by confidence bounds determined by bootstrap analysis and a comprehensive Monte Carlo study of error propagation. This new approach opens the door to a variety of screening processes in the 384-well format on HTS stations, higher quality screening data and an increase in throughput. Copyright © 2015 Elsevier B.V. All rights reserved.

Entropic Analysis of Electromyography Time Series

Science.gov (United States)

Kaufman, Miron; Sung, Paul

2005-03-01

We are in the process of assessing the effectiveness of fractal and entropic measures for the diagnostic of low back pain from surface electromyography (EMG) time series. Surface electromyography (EMG) is used to assess patients with low back pain. In a typical EMG measurement, the voltage is measured every millisecond. We observed back muscle fatiguing during one minute, which results in a time series with 60,000 entries. We characterize the complexity of time series by computing the Shannon entropy time dependence. The analysis of the time series from different relevant muscles from healthy and low back pain (LBP) individuals provides evidence that the level of variability of back muscle activities is much larger for healthy individuals than for individuals with LBP. In general the time dependence of the entropy shows a crossover from a diffusive regime to a regime characterized by long time correlations (self organization) at about 0.01s.

High-resolution time series of Pseudomonas aeruginosa gene expression and rhamnolipid secretion through growth curve synchronization

Directory of Open Access Journals (Sweden)

Xavier João B

2011-06-01

Full Text Available Abstract Background Online spectrophotometric measurements allow monitoring dynamic biological processes with high-time resolution. Contrastingly, numerous other methods require laborious treatment of samples and can only be carried out offline. Integrating both types of measurement would allow analyzing biological processes more comprehensively. A typical example of this problem is acquiring quantitative data on rhamnolipid secretion by the opportunistic pathogen Pseudomonas aeruginosa. P. aeruginosa cell growth can be measured by optical density (OD600 and gene expression can be measured using reporter fusions with a fluorescent protein, allowing high time resolution monitoring. However, measuring the secreted rhamnolipid biosurfactants requires laborious sample processing, which makes this an offline measurement. Results Here, we propose a method to integrate growth curve data with endpoint measurements of secreted metabolites that is inspired by a model of exponential cell growth. If serial diluting an inoculum gives reproducible time series shifted in time, then time series of endpoint measurements can be reconstructed using calculated time shifts between dilutions. We illustrate the method using measured rhamnolipid secretion by P. aeruginosa as endpoint measurements and we integrate these measurements with high-resolution growth curves measured by OD600 and expression of rhamnolipid synthesis genes monitored using a reporter fusion. Two-fold serial dilution allowed integrating rhamnolipid measurements at a ~0.4 h-1 frequency with high-time resolved data measured at a 6 h-1 frequency. We show how this simple method can be used in combination with mutants lacking specific genes in the rhamnolipid synthesis or quorum sensing regulation to acquire rich dynamic data on P. aeruginosa virulence regulation. Additionally, the linear relation between the ratio of inocula and the time-shift between curves produces high-precision measurements of

Morphology control in polymer blend fibers—a high throughput computing approach

Science.gov (United States)

Sesha Sarath Pokuri, Balaji; Ganapathysubramanian, Baskar

2016-08-01

Fibers made from polymer blends have conventionally enjoyed wide use, particularly in textiles. This wide applicability is primarily aided by the ease of manufacturing such fibers. More recently, the ability to tailor the internal morphology of polymer blend fibers by carefully designing processing conditions has enabled such fibers to be used in technologically relevant applications. Some examples include anisotropic insulating properties for heat and anisotropic wicking of moisture, coaxial morphologies for optical applications as well as fibers with high internal surface area for filtration and catalysis applications. However, identifying the appropriate processing conditions from the large space of possibilities using conventional trial-and-error approaches is a tedious and resource-intensive process. Here, we illustrate a high throughput computational approach to rapidly explore and characterize how processing conditions (specifically blend ratio and evaporation rates) affect the internal morphology of polymer blends during solvent based fabrication. We focus on a PS: PMMA system and identify two distinct classes of morphologies formed due to variations in the processing conditions. We subsequently map the processing conditions to the morphology class, thus constructing a ‘phase diagram’ that enables rapid identification of processing parameters for specific morphology class. We finally demonstrate the potential for time dependent processing conditions to get desired features of the morphology. This opens up the possibility of rational stage-wise design of processing pathways for tailored fiber morphology using high throughput computing.

High-throughput screening of carbohydrate-degrading enzymes using novel insoluble chromogenic substrate assay kits

DEFF Research Database (Denmark)

Schückel, Julia; Kracun, Stjepan Kresimir; Willats, William George Tycho

2016-01-01

for this is that advances in genome and transcriptome sequencing, together with associated bioinformatics tools allow for rapid identification of candidate CAZymes, but technology for determining an enzyme's biochemical characteristics has advanced more slowly. To address this technology gap, a novel high-throughput assay...... CPH and ICB substrates are provided in a 96-well high-throughput assay system. The CPH substrates can be made in four different colors, enabling them to be mixed together and thus increasing assay throughput. The protocol describes a 96-well plate assay and illustrates how this assay can be used...... for screening the activities of enzymes, enzyme cocktails, and broths....

Development of a high-throughput screening assay for stearoyl-CoA desaturase using rat liver microsomes, deuterium labeled stearoyl-CoA and mass spectrometry

Energy Technology Data Exchange (ETDEWEB)

Soulard, Patricia; McLaughlin, Meg; Stevens, Jessica; Connolly, Brendan; Coli, Rocco; Wang Leyu [Research Technology Center, Pfizer Global Research and Development, Cambridge, MA (United States); Moore, Jennifer; Kuo, Ming-Shang T. [Pfizer Global Research and Development, San Diego, CA (United States); LaMarr, William A.; Ozbal, Can C. [Biotrove, Inc., Woburn, MA (United States); Bhat, B. Ganesh [Pfizer Global Research and Development, San Diego, CA (United States)], E-mail: gbhat@gnf.org

2008-10-03

Several recent reports suggest that stearoyl-CoA desaturase 1 (SCD1), the rate-limiting enzyme in monounsaturated fatty acid synthesis, plays an important role in regulating lipid homeostasis and lipid oxidation in metabolically active tissues. As several manifestations of type 2 diabetes and related metabolic disorders are associated with alterations in intracellular lipid partitioning, pharmacological manipulation of SCD1 activity might be of benefit in the treatment of these disease states. In an effort to identify small molecule inhibitors of SCD1, we have developed a mass spectrometry based high-throughput screening (HTS) assay using deuterium labeled stearoyl-CoA substrate and induced rat liver microsomes. The methodology developed allows the use of a nonradioactive substrate which avoids interference by the endogenous SCD1 substrate and/or product that exist in the non-purified enzyme source. Throughput of the assay was up to twenty 384-well assay plates per day. The assay was linear with protein concentration and time, and was saturable for stearoyl-CoA substrate (K{sub m} = 10.5 {mu}M). The assay was highly reproducible with an average Z' value = 0.6. Conjugated linoleic acid and sterculic acid, known inhibitors of SCD1, exhibited IC{sub 50} values of 0.88 and 0.12 {mu}M, respectively. High-throughput mass spectrometry screening of over 1.7 million compounds in compressed format demonstrated that the enzyme target is druggable. A total of 2515 hits were identified (0.1% hit rate), and 346 were confirmed active (>40% inhibition of total SCD activity at 20 {mu}M - 14% conformation rate). Of the confirmed hits 172 had IC{sub 50} values of <10 {mu}M, including 111 <1 {mu}M and 48 <100 nM. A large number of potent drug-like (MW < 450) hits representing six different chemical series were identified. The application of mass spectrometry to high-throughput screening permitted the development of a high-quality screening protocol for an otherwise intractable

Development of a high-throughput screening assay for stearoyl-CoA desaturase using rat liver microsomes, deuterium labeled stearoyl-CoA and mass spectrometry

International Nuclear Information System (INIS)

Soulard, Patricia; McLaughlin, Meg; Stevens, Jessica; Connolly, Brendan; Coli, Rocco; Wang Leyu; Moore, Jennifer; Kuo, Ming-Shang T.; LaMarr, William A.; Ozbal, Can C.; Bhat, B. Ganesh

2008-01-01

Several recent reports suggest that stearoyl-CoA desaturase 1 (SCD1), the rate-limiting enzyme in monounsaturated fatty acid synthesis, plays an important role in regulating lipid homeostasis and lipid oxidation in metabolically active tissues. As several manifestations of type 2 diabetes and related metabolic disorders are associated with alterations in intracellular lipid partitioning, pharmacological manipulation of SCD1 activity might be of benefit in the treatment of these disease states. In an effort to identify small molecule inhibitors of SCD1, we have developed a mass spectrometry based high-throughput screening (HTS) assay using deuterium labeled stearoyl-CoA substrate and induced rat liver microsomes. The methodology developed allows the use of a nonradioactive substrate which avoids interference by the endogenous SCD1 substrate and/or product that exist in the non-purified enzyme source. Throughput of the assay was up to twenty 384-well assay plates per day. The assay was linear with protein concentration and time, and was saturable for stearoyl-CoA substrate (K m = 10.5 μM). The assay was highly reproducible with an average Z' value = 0.6. Conjugated linoleic acid and sterculic acid, known inhibitors of SCD1, exhibited IC 50 values of 0.88 and 0.12 μM, respectively. High-throughput mass spectrometry screening of over 1.7 million compounds in compressed format demonstrated that the enzyme target is druggable. A total of 2515 hits were identified (0.1% hit rate), and 346 were confirmed active (>40% inhibition of total SCD activity at 20 μM - 14% conformation rate). Of the confirmed hits 172 had IC 50 values of <10 μM, including 111 <1 μM and 48 <100 nM. A large number of potent drug-like (MW < 450) hits representing six different chemical series were identified. The application of mass spectrometry to high-throughput screening permitted the development of a high-quality screening protocol for an otherwise intractable target, SCD1. Further medicinal

Micellar Surfactant Association in the Presence of a Glucoside-based Amphiphile Detected via High-Throughput Small Angle X-ray Scattering

Energy Technology Data Exchange (ETDEWEB)

Stanic, Vesna [Brazilian Synchrotron Light Source, Campinas (Brazil); Broadbent, Charlotte [Columbia Univ., New York, NY (United States). Engineering Dept.; DiMasi, Elaine [Brookhaven National Lab. (BNL), Upton, NY (United States). Photon Sciences Division; Galleguillos, Ramiro [Lubrizol Advanced Materials, Cleveland, OH (United States); Woodward, Valerie [Lubrizol Advanced Materials, Cleveland, OH (United States)

2016-11-14

The interactions of mixtures of anionic and amphoteric surfactants with sugar amphiphiles were studied via high throughput small angle x-ray scattering (SAXS). The sugar amphiphile was composed of Caprate, Caprylate, and Oleate mixed ester of methyl glucoside, MeGCCO. Optimal surfactant interactions are sought which have desirable physical properties, which must be identified in a cost effective manner that can access the large phase space of possible molecular combinations. X-ray scattering patterns obtained via high throughput SAXS can probe a combinatorial sample space and reveal the incorporation of MeGCCO into the micelles and the molecular associations between surfactant molecules. Such data make it possible to efficiently assess the effects of the new amphiphiles in the formulation. A specific finding of this study is that formulations containing comparatively monodisperse and homogeneous surfactant mixtures can be reliably tuned by addition of NaCl, which swells the surfactant micelles with a monotonic dependence on salt concentration. In contrast, the presence of multiple different surfactants destroys clear correlations with NaCl concentration, even in otherwise similar series of formulations.

GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit.

Science.gov (United States)

Pronk, Sander; Páll, Szilárd; Schulz, Roland; Larsson, Per; Bjelkmar, Pär; Apostolov, Rossen; Shirts, Michael R; Smith, Jeremy C; Kasson, Peter M; van der Spoel, David; Hess, Berk; Lindahl, Erik

2013-04-01

Molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations. GROMACS is an open source and free software available from http://www.gromacs.org. Supplementary data are available at Bioinformatics online.

The application of the high throughput sequencing technology in the transposable elements.

Science.gov (United States)

Liu, Zhen; Xu, Jian-hong

2015-09-01

High throughput sequencing technology has dramatically improved the efficiency of DNA sequencing, and decreased the costs to a great extent. Meanwhile, this technology usually has advantages of better specificity, higher sensitivity and accuracy. Therefore, it has been applied to the research on genetic variations, transcriptomics and epigenomics. Recently, this technology has been widely employed in the studies of transposable elements and has achieved fruitful results. In this review, we summarize the application of high throughput sequencing technology in the fields of transposable elements, including the estimation of transposon content, preference of target sites and distribution, insertion polymorphism and population frequency, identification of rare copies, transposon horizontal transfers as well as transposon tagging. We also briefly introduce the major common sequencing strategies and algorithms, their advantages and disadvantages, and the corresponding solutions. Finally, we envision the developing trends of high throughput sequencing technology, especially the third generation sequencing technology, and its application in transposon studies in the future, hopefully providing a comprehensive understanding and reference for related scientific researchers.

Micro-patterned agarose gel devices for single-cell high-throughput microscopy of E. coli cells.

Science.gov (United States)

Priest, David G; Tanaka, Nobuyuki; Tanaka, Yo; Taniguchi, Yuichi

2017-12-21

High-throughput microscopy of bacterial cells elucidated fundamental cellular processes including cellular heterogeneity and cell division homeostasis. Polydimethylsiloxane (PDMS)-based microfluidic devices provide advantages including precise positioning of cells and throughput, however device fabrication is time-consuming and requires specialised skills. Agarose pads are a popular alternative, however cells often clump together, which hinders single cell quantitation. Here, we imprint agarose pads with micro-patterned 'capsules', to trap individual cells and 'lines', to direct cellular growth outwards in a straight line. We implement this micro-patterning into multi-pad devices called CapsuleHotel and LineHotel for high-throughput imaging. CapsuleHotel provides ~65,000 capsule structures per mm 2 that isolate individual Escherichia coli cells. In contrast, LineHotel provides ~300 line structures per mm that direct growth of micro-colonies. With CapsuleHotel, a quantitative single cell dataset of ~10,000 cells across 24 samples can be acquired and analysed in under 1 hour. LineHotel allows tracking growth of > 10 micro-colonies across 24 samples simultaneously for up to 4 generations. These easy-to-use devices can be provided in kit format, and will accelerate discoveries in diverse fields ranging from microbiology to systems and synthetic biology.

A Customizable Flow Injection System for Automated, High Throughput, and Time Sensitive Ion Mobility Spectrometry and Mass Spectrometry Measurements.

Science.gov (United States)

Orton, Daniel J; Tfaily, Malak M; Moore, Ronald J; LaMarche, Brian L; Zheng, Xueyun; Fillmore, Thomas L; Chu, Rosalie K; Weitz, Karl K; Monroe, Matthew E; Kelly, Ryan T; Smith, Richard D; Baker, Erin S

2018-01-02

To better understand disease conditions and environmental perturbations, multiomic studies combining proteomic, lipidomic, and metabolomic analyses are vastly increasing in popularity. In a multiomic study, a single sample is typically extracted in multiple ways, and various analyses are performed using different instruments, most often based upon mass spectrometry (MS). Thus, one sample becomes many measurements, making high throughput and reproducible evaluations a necessity. One way to address the numerous samples and varying instrumental conditions is to utilize a flow injection analysis (FIA) system for rapid sample injections. While some FIA systems have been created to address these challenges, many have limitations such as costly consumables, low pressure capabilities, limited pressure monitoring, and fixed flow rates. To address these limitations, we created an automated, customizable FIA system capable of operating at a range of flow rates (∼50 nL/min to 500 μL/min) to accommodate both low- and high-flow MS ionization sources. This system also functions at varying analytical throughputs from 24 to 1200 samples per day to enable different MS analysis approaches. Applications ranging from native protein analyses to molecular library construction were performed using the FIA system, and results showed a highly robust and reproducible platform capable of providing consistent performance over many days without carryover, as long as washing buffers specific to each molecular analysis were utilized.

High-Throughput Cancer Cell Sphere Formation for 3D Cell Culture.

Science.gov (United States)

Chen, Yu-Chih; Yoon, Euisik

2017-01-01

Three-dimensional (3D) cell culture is critical in studying cancer pathology and drug response. Though 3D cancer sphere culture can be performed in low-adherent dishes or well plates, the unregulated cell aggregation may skew the results. On contrary, microfluidic 3D culture can allow precise control of cell microenvironments, and provide higher throughput by orders of magnitude. In this chapter, we will look into engineering innovations in a microfluidic platform for high-throughput cancer cell sphere formation and review the implementation methods in detail.

High-throughput differentiation of heparin from other glycosaminoglycans by pyrolysis mass spectrometry.

Science.gov (United States)

Nemes, Peter; Hoover, William J; Keire, David A

2013-08-06

Sensors with high chemical specificity and enhanced sample throughput are vital to screening food products and medical devices for chemical or biochemical contaminants that may pose a threat to public health. For example, the rapid detection of oversulfated chondroitin sulfate (OSCS) in heparin could prevent reoccurrence of heparin adulteration that caused hundreds of severe adverse events including deaths worldwide in 2007-2008. Here, rapid pyrolysis is integrated with direct analysis in real time (DART) mass spectrometry to rapidly screen major glycosaminoglycans, including heparin, chondroitin sulfate A, dermatan sulfate, and OSCS. The results demonstrate that, compared to traditional liquid chromatography-based analyses, pyrolysis mass spectrometry achieved at least 250-fold higher sample throughput and was compatible with samples volume-limited to about 300 nL. Pyrolysis yielded an abundance of fragment ions (e.g., 150 different m/z species), many of which were specific to the parent compound. Using multivariate and statistical data analysis models, these data enabled facile differentiation of the glycosaminoglycans with high throughput. After method development was completed, authentically contaminated samples obtained during the heparin crisis by the FDA were analyzed in a blinded manner for OSCS contamination. The lower limit of differentiation and detection were 0.1% (w/w) OSCS in heparin and 100 ng/μL (20 ng) OSCS in water, respectively. For quantitative purposes the linear dynamic range spanned approximately 3 orders of magnitude. Moreover, this chemical readout was successfully employed to find clues in the manufacturing history of the heparin samples that can be used for surveillance purposes. The presented technology and data analysis protocols are anticipated to be readily adaptable to other chemical and biochemical agents and volume-limited samples.

An Automated High Performance Capillary Liquid Chromatography Fourier Transform Ion Cyclotron Resonance Mass Spectrometer for High-Throughput Proteomics

International Nuclear Information System (INIS)

Belov, Mikhail E.; Anderson, Gordon A.; Wingerd, Mark A.; Udseth, Harold R.; Tang, Keqi; Prior, David C.; Swanson, Kenneth R.; Buschbach, Michael A.; Strittmatter, Eric F.; Moore, Ronald J.; Smith, Richard D.

2004-01-01

We report on a fully automated 9.4 tesla Fourier transform ion resonance cyclotron (FTICR) mass spectrometer coupled to reverse-phase chromatography for high-throughput proteomic studies. Modifications made to the front-end of a commercial FTICR instrument--a dual-ESI-emitter ion source; dual-channel electrodynamic ion funnel; and collisional-cooling, selection and accumulation quadrupoles--significantly improved the sensitivity, dynamic range and mass measurement accuracy of the mass spectrometer. A high-pressure capillary liquid chromatography (LC) system was incorporated with an autosampler that enabled 24 h/day operation. A novel method for accumulating ions in the ICR cell was also developed. Unattended operation of the instrument revealed the exceptional reproducibility (1-5% deviation in elution times for peptides from a bacterial proteome), repeatability (10-20% deviation in detected abundances for peptides from the same aliquot analyzed a few weeks apart) and robustness (high-throughput operation for 5 months without downtime) of the LC/FTICR system. When combined with modulated-ion-energy gated trapping, the internal calibration of FTICR mass spectra decreased dispersion of mass measurement errors for peptide identifications in conjunction with high resolution capillary LC separations to < 5 ppm over a dynamic range for each spectrum of 10 3

Nonlinear time series analysis with R

CERN Document Server

Huffaker, Ray; Rosa, Rodolfo

2017-01-01

In the process of data analysis, the investigator is often facing highly-volatile and random-appearing observed data. A vast body of literature shows that the assumption of underlying stochastic processes was not necessarily representing the nature of the processes under investigation and, when other tools were used, deterministic features emerged. Non Linear Time Series Analysis (NLTS) allows researchers to test whether observed volatility conceals systematic non linear behavior, and to rigorously characterize governing dynamics. Behavioral patterns detected by non linear time series analysis, along with scientific principles and other expert information, guide the specification of mechanistic models that serve to explain real-world behavior rather than merely reproducing it. Often there is a misconception regarding the complexity of the level of mathematics needed to understand and utilize the tools of NLTS (for instance Chaos theory). However, mathematics used in NLTS is much simpler than many other subjec...

A high-throughput in vitro ring assay for vasoactivity using magnetic 3D bioprinting

Science.gov (United States)

Tseng, Hubert; Gage, Jacob A.; Haisler, William L.; Neeley, Shane K.; Shen, Tsaiwei; Hebel, Chris; Barthlow, Herbert G.; Wagoner, Matthew; Souza, Glauco R.

2016-01-01

Vasoactive liabilities are typically assayed using wire myography, which is limited by its high cost and low throughput. To meet the demand for higher throughput in vitro alternatives, this study introduces a magnetic 3D bioprinting-based vasoactivity assay. The principle behind this assay is the magnetic printing of vascular smooth muscle cells into 3D rings that functionally represent blood vessel segments, whose contraction can be altered by vasodilators and vasoconstrictors. A cost-effective imaging modality employing a mobile device is used to capture contraction with high throughput. The goal of this study was to validate ring contraction as a measure of vasoactivity, using a small panel of known vasoactive drugs. In vitro responses of the rings matched outcomes predicted by in vivo pharmacology, and were supported by immunohistochemistry. Altogether, this ring assay robustly models vasoactivity, which could meet the need for higher throughput in vitro alternatives. PMID:27477945

Effective Feature Preprocessing for Time Series Forecasting

DEFF Research Database (Denmark)

Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

2006-01-01

Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...... series forecasting models....

Data reduction for a high-throughput neutron activation analysis system

International Nuclear Information System (INIS)

Bowman, W.W.

1979-01-01

To analyze samples collected as part of a geochemical survey for the National Uranium Resource Evaluation program, Savannah River Laboratory has installed a high-throughput neutron activation analysis system. As part of that system, computer programs have been developed to reduce raw data to elemental concentrations in two steps. Program RAGS reduces gamma-ray spectra to lists of photopeak energies, peak areas, and statistical errors. Program RICHES determines the elemental concentrations from photopeak and delayed-neutron data, detector efficiencies, analysis parameters (neutron flux and activation, decay, and counting times), and spectrometric and cross-section data from libraries. Both programs have been streamlined for on-line operation with a minicomputer, each requiring approx. 64 kbytes of core. 3 tables

High-Throughput Identification of Antimicrobial Peptides from Amphibious Mudskippers

Directory of Open Access Journals (Sweden)

Yunhai Yi

2017-11-01

Full Text Available Widespread existence of antimicrobial peptides (AMPs has been reported in various animals with comprehensive biological activities, which is consistent with the important roles of AMPs as the first line of host defense system. However, no big-data-based analysis on AMPs from any fish species is available. In this study, we identified 507 AMP transcripts on the basis of our previously reported genomes and transcriptomes of two representative amphibious mudskippers, Boleophthalmus pectinirostris (BP and Periophthalmus magnuspinnatus (PM. The former is predominantly aquatic with less time out of water, while the latter is primarily terrestrial with extended periods of time on land. Within these identified AMPs, 449 sequences are novel; 15 were reported in BP previously; 48 are identically overlapped between BP and PM; 94 were validated by mass spectrometry. Moreover, most AMPs presented differential tissue transcription patterns in the two mudskippers. Interestingly, we discovered two AMPs, hemoglobin β1 and amylin, with high inhibitions on Micrococcus luteus. In conclusion, our high-throughput screening strategy based on genomic and transcriptomic data opens an efficient pathway to discover new antimicrobial peptides for ongoing development of marine drugs.

High-Throughput Identification of Antimicrobial Peptides from Amphibious Mudskippers.

Science.gov (United States)

Yi, Yunhai; You, Xinxin; Bian, Chao; Chen, Shixi; Lv, Zhao; Qiu, Limei; Shi, Qiong

2017-11-22

Widespread existence of antimicrobial peptides (AMPs) has been reported in various animals with comprehensive biological activities, which is consistent with the important roles of AMPs as the first line of host defense system. However, no big-data-based analysis on AMPs from any fish species is available. In this study, we identified 507 AMP transcripts on the basis of our previously reported genomes and transcriptomes of two representative amphibious mudskippers, Boleophthalmus pectinirostris (BP) and Periophthalmus magnuspinnatus (PM). The former is predominantly aquatic with less time out of water, while the latter is primarily terrestrial with extended periods of time on land. Within these identified AMPs, 449 sequences are novel; 15 were reported in BP previously; 48 are identically overlapped between BP and PM; 94 were validated by mass spectrometry. Moreover, most AMPs presented differential tissue transcription patterns in the two mudskippers. Interestingly, we discovered two AMPs, hemoglobin β1 and amylin, with high inhibitions on Micrococcus luteus . In conclusion, our high-throughput screening strategy based on genomic and transcriptomic data opens an efficient pathway to discover new antimicrobial peptides for ongoing development of marine drugs.

A modified FASP protocol for high-throughput preparation of protein samples for mass spectrometry.

Directory of Open Access Journals (Sweden)

Jeremy Potriquet

Full Text Available To facilitate high-throughput proteomic analyses we have developed a modified FASP protocol which improves the rate at which protein samples can be processed prior to mass spectrometry. Adapting the original FASP protocol to a 96-well format necessitates extended spin times for buffer exchange due to the low centrifugation speeds tolerated by these devices. However, by using 96-well plates with a more robust polyethersulfone molecular weight cutoff membrane, instead of the cellulose membranes typically used in these devices, we could use isopropanol as a wetting agent, decreasing spin times required for buffer exchange from an hour to 30 minutes. In a typical work flow used in our laboratory this equates to a reduction of 3 hours per plate, providing processing times similar to FASP for the processing of up to 96 samples per plate. To test whether our modified protocol produced similar results to FASP and other FASP-like protocols we compared the performance of our modified protocol to the original FASP and the more recently described eFASP and MStern-blot. We show that all FASP-like methods, including our modified protocol, display similar performance in terms of proteins identified and reproducibility. Our results show that our modified FASP protocol is an efficient method for the high-throughput processing of protein samples for mass spectral analysis.

High-throughput purification of recombinant proteins using self-cleaving intein tags.

Science.gov (United States)

Coolbaugh, M J; Shakalli Tang, M J; Wood, D W

2017-01-01

High throughput methods for recombinant protein production using E. coli typically involve the use of affinity tags for simple purification of the protein of interest. One drawback of these techniques is the occasional need for tag removal before study, which can be hard to predict. In this work, we demonstrate two high throughput purification methods for untagged protein targets based on simple and cost-effective self-cleaving intein tags. Two model proteins, E. coli beta-galactosidase (βGal) and superfolder green fluorescent protein (sfGFP), were purified using self-cleaving versions of the conventional chitin-binding domain (CBD) affinity tag and the nonchromatographic elastin-like-polypeptide (ELP) precipitation tag in a 96-well filter plate format. Initial tests with shake flask cultures confirmed that the intein purification scheme could be scaled down, with >90% pure product generated in a single step using both methods. The scheme was then validated in a high throughput expression platform using 24-well plate cultures followed by purification in 96-well plates. For both tags and with both target proteins, the purified product was consistently obtained in a single-step, with low well-to-well and plate-to-plate variability. This simple method thus allows the reproducible production of highly pure untagged recombinant proteins in a convenient microtiter plate format. Copyright © 2016 Elsevier Inc. All rights reserved.

Drosophila melanogaster as a High-Throughput Model for Host–Microbiota Interactions

Directory of Open Access Journals (Sweden)

Gregor Reid

2017-04-01

Full Text Available Microbiota research often assumes that differences in abundance and identity of microorganisms have unique influences on host physiology. To test this concept mechanistically, germ-free mice are colonized with microbial communities to assess causation. Due to the cost, infrastructure challenges, and time-consuming nature of germ-free mouse models, an alternative approach is needed to investigate host–microbial interactions. Drosophila melanogaster (fruit flies can be used as a high throughput in vivo screening model of host–microbiome interactions as they are affordable, convenient, and replicable. D. melanogaster were essential in discovering components of the innate immune response to pathogens. However, axenic D. melanogaster can easily be generated for microbiome studies without the need for ethical considerations. The simplified microbiota structure enables researchers to evaluate permutations of how each microbial species within the microbiota contribute to host phenotypes of interest. This enables the possibility of thorough strain-level analysis of host and microbial properties relevant to physiological outcomes. Moreover, a wide range of mutant D. melanogaster strains can be affordably obtained from public stock centers. Given this, D. melanogaster can be used to identify candidate mechanisms of host–microbe symbioses relevant to pathogen exclusion, innate immunity modulation, diet, xenobiotics, and probiotic/prebiotic properties in a high throughput manner. This perspective comments on the most promising areas of microbiota research that could immediately benefit from using the D. melanogaster model.

Drosophila melanogaster as a High-Throughput Model for Host-Microbiota Interactions.

Science.gov (United States)

Trinder, Mark; Daisley, Brendan A; Dube, Josh S; Reid, Gregor

2017-01-01

Microbiota research often assumes that differences in abundance and identity of microorganisms have unique influences on host physiology. To test this concept mechanistically, germ-free mice are colonized with microbial communities to assess causation. Due to the cost, infrastructure challenges, and time-consuming nature of germ-free mouse models, an alternative approach is needed to investigate host-microbial interactions. Drosophila melanogaster (fruit flies) can be used as a high throughput in vivo screening model of host-microbiome interactions as they are affordable, convenient, and replicable. D. melanogaster were essential in discovering components of the innate immune response to pathogens. However, axenic D. melanogaster can easily be generated for microbiome studies without the need for ethical considerations. The simplified microbiota structure enables researchers to evaluate permutations of how each microbial species within the microbiota contribute to host phenotypes of interest. This enables the possibility of thorough strain-level analysis of host and microbial properties relevant to physiological outcomes. Moreover, a wide range of mutant D. melanogaster strains can be affordably obtained from public stock centers. Given this, D. melanogaster can be used to identify candidate mechanisms of host-microbe symbioses relevant to pathogen exclusion, innate immunity modulation, diet, xenobiotics, and probiotic/prebiotic properties in a high throughput manner. This perspective comments on the most promising areas of microbiota research that could immediately benefit from using the D. melanogaster model.

High-Throughput Screening Using Mass Spectrometry within Drug Discovery.

Science.gov (United States)

Rohman, Mattias; Wingfield, Jonathan

2016-01-01

In order to detect a biochemical analyte with a mass spectrometer (MS) it is necessary to ionize the analyte of interest. The analyte can be ionized by a number of different mechanisms, however, one common method is electrospray ionization (ESI). Droplets of analyte are sprayed through a highly charged field, the droplets pick up charge, and this is transferred to the analyte. High levels of salt in the assay buffer will potentially steal charge from the analyte and suppress the MS signal. In order to avoid this suppression of signal, salt is often removed from the sample prior to injection into the MS. Traditional ESI MS relies on liquid chromatography (LC) to remove the salt and reduce matrix effects, however, this is a lengthy process. Here we describe the use of RapidFire™ coupled to a triple-quadrupole MS for high-throughput screening. This system uses solid-phase extraction to de-salt samples prior to injection, reducing processing time such that a sample is injected into the MS ~every 10 s.

High-Throughput and Low-Latency Network Communication with NetIO

Science.gov (United States)

Schumacher, Jörn; Plessl, Christian; Vandelli, Wainer

2017-10-01

HPC network technologies like Infiniband, TrueScale or OmniPath provide low- latency and high-throughput communication between hosts, which makes them attractive options for data-acquisition systems in large-scale high-energy physics experiments. Like HPC networks, DAQ networks are local and include a well specified number of systems. Unfortunately traditional network communication APIs for HPC clusters like MPI or PGAS exclusively target the HPC community and are not suited well for DAQ applications. It is possible to build distributed DAQ applications using low-level system APIs like Infiniband Verbs, but it requires a non-negligible effort and expert knowledge. At the same time, message services like ZeroMQ have gained popularity in the HEP community. They make it possible to build distributed applications with a high-level approach and provide good performance. Unfortunately, their usage usually limits developers to TCP/IP- based networks. While it is possible to operate a TCP/IP stack on top of Infiniband and OmniPath, this approach may not be very efficient compared to a direct use of native APIs. NetIO is a simple, novel asynchronous message service that can operate on Ethernet, Infiniband and similar network fabrics. In this paper the design and implementation of NetIO is presented and described, and its use is evaluated in comparison to other approaches. NetIO supports different high-level programming models and typical workloads of HEP applications. The ATLAS FELIX project [1] successfully uses NetIO as its central communication platform. The architecture of NetIO is described in this paper, including the user-level API and the internal data-flow design. The paper includes a performance evaluation of NetIO including throughput and latency measurements. The performance is compared against the state-of-the- art ZeroMQ message service. Performance measurements are performed in a lab environment with Ethernet and FDR Infiniband networks.

Estimating serial correlation and self-similarity in financial time series-A diversification approach with applications to high frequency data

Science.gov (United States)

Gerlich, Nikolas; Rostek, Stefan

2015-09-01

We derive a heuristic method to estimate the degree of self-similarity and serial correlation in financial time series. Especially, we propagate the use of a tailor-made selection of different estimation techniques that are used in various fields of time series analysis but until now have not consequently found their way into the finance literature. Following the idea of portfolio diversification, we show that considerable improvements with respect to robustness and unbiasedness can be achieved by using a basket of estimation methods. With this methodological toolbox at hand, we investigate real market data to show that noticeable deviations from the assumptions of constant self-similarity and absence of serial correlation occur during certain periods. On the one hand, this may shed a new light on seemingly ambiguous scientific findings concerning serial correlation of financial time series. On the other hand, a proven time-changing degree of self-similarity may help to explain high-volatility clusters of stock price indices.

CrossCheck: an open-source web tool for high-throughput screen data analysis.

Science.gov (United States)

Najafov, Jamil; Najafov, Ayaz

2017-07-19

Modern high-throughput screening methods allow researchers to generate large datasets that potentially contain important biological information. However, oftentimes, picking relevant hits from such screens and generating testable hypotheses requires training in bioinformatics and the skills to efficiently perform database mining. There are currently no tools available to general public that allow users to cross-reference their screen datasets with published screen datasets. To this end, we developed CrossCheck, an online platform for high-throughput screen data analysis. CrossCheck is a centralized database that allows effortless comparison of the user-entered list of gene symbols with 16,231 published datasets. These datasets include published data from genome-wide RNAi and CRISPR screens, interactome proteomics and phosphoproteomics screens, cancer mutation databases, low-throughput studies of major cell signaling mediators, such as kinases, E3 ubiquitin ligases and phosphatases, and gene ontological information. Moreover, CrossCheck includes a novel database of predicted protein kinase substrates, which was developed using proteome-wide consensus motif searches. CrossCheck dramatically simplifies high-throughput screen data analysis and enables researchers to dig deep into the published literature and streamline data-driven hypothesis generation. CrossCheck is freely accessible as a web-based application at http://proteinguru.com/crosscheck.

Optimizing transformations for automated, high throughput analysis of flow cytometry data.

Science.gov (United States)

Finak, Greg; Perez, Juan-Manuel; Weng, Andrew; Gottardo, Raphael

2010-11-04

In a high throughput setting, effective flow cytometry data analysis depends heavily on proper data preprocessing. While usual preprocessing steps of quality assessment, outlier removal, normalization, and gating have received considerable scrutiny from the community, the influence of data transformation on the output of high throughput analysis has been largely overlooked. Flow cytometry measurements can vary over several orders of magnitude, cell populations can have variances that depend on their mean fluorescence intensities, and may exhibit heavily-skewed distributions. Consequently, the choice of data transformation can influence the output of automated gating. An appropriate data transformation aids in data visualization and gating of cell populations across the range of data. Experience shows that the choice of transformation is data specific. Our goal here is to compare the performance of different transformations applied to flow cytometry data in the context of automated gating in a high throughput, fully automated setting. We examine the most common transformations used in flow cytometry, including the generalized hyperbolic arcsine, biexponential, linlog, and generalized Box-Cox, all within the BioConductor flowCore framework that is widely used in high throughput, automated flow cytometry data analysis. All of these transformations have adjustable parameters whose effects upon the data are non-intuitive for most users. By making some modelling assumptions about the transformed data, we develop maximum likelihood criteria to optimize parameter choice for these different transformations. We compare the performance of parameter-optimized and default-parameter (in flowCore) data transformations on real and simulated data by measuring the variation in the locations of cell populations across samples, discovered via automated gating in both the scatter and fluorescence channels. We find that parameter-optimized transformations improve visualization, reduce

Optimizing transformations for automated, high throughput analysis of flow cytometry data

Directory of Open Access Journals (Sweden)

Weng Andrew

2010-11-01

Full Text Available Abstract Background In a high throughput setting, effective flow cytometry data analysis depends heavily on proper data preprocessing. While usual preprocessing steps of quality assessment, outlier removal, normalization, and gating have received considerable scrutiny from the community, the influence of data transformation on the output of high throughput analysis has been largely overlooked. Flow cytometry measurements can vary over several orders of magnitude, cell populations can have variances that depend on their mean fluorescence intensities, and may exhibit heavily-skewed distributions. Consequently, the choice of data transformation can influence the output of automated gating. An appropriate data transformation aids in data visualization and gating of cell populations across the range of data. Experience shows that the choice of transformation is data specific. Our goal here is to compare the performance of different transformations applied to flow cytometry data in the context of automated gating in a high throughput, fully automated setting. We examine the most common transformations used in flow cytometry, including the generalized hyperbolic arcsine, biexponential, linlog, and generalized Box-Cox, all within the BioConductor flowCore framework that is widely used in high throughput, automated flow cytometry data analysis. All of these transformations have adjustable parameters whose effects upon the data are non-intuitive for most users. By making some modelling assumptions about the transformed data, we develop maximum likelihood criteria to optimize parameter choice for these different transformations. Results We compare the performance of parameter-optimized and default-parameter (in flowCore data transformations on real and simulated data by measuring the variation in the locations of cell populations across samples, discovered via automated gating in both the scatter and fluorescence channels. We find that parameter

Interpretable Categorization of Heterogeneous Time Series Data

Science.gov (United States)

Lee, Ritchie; Kochenderfer, Mykel J.; Mengshoel, Ole J.; Silbermann, Joshua

2017-01-01

We analyze data from simulated aircraft encounters to validate and inform the development of a prototype aircraft collision avoidance system. The high-dimensional and heterogeneous time series dataset is analyzed to discover properties of near mid-air collisions (NMACs) and categorize the NMAC encounters. Domain experts use these properties to better organize and understand NMAC occurrences. Existing solutions either are not capable of handling high-dimensional and heterogeneous time series datasets or do not provide explanations that are interpretable by a domain expert. The latter is critical to the acceptance and deployment of safety-critical systems. To address this gap, we propose grammar-based decision trees along with a learning algorithm. Our approach extends decision trees with a grammar framework for classifying heterogeneous time series data. A context-free grammar is used to derive decision expressions that are interpretable, application-specific, and support heterogeneous data types. In addition to classification, we show how grammar-based decision trees can also be used for categorization, which is a combination of clustering and generating interpretable explanations for each cluster. We apply grammar-based decision trees to a simulated aircraft encounter dataset and evaluate the performance of four variants of our learning algorithm. The best algorithm is used to analyze and categorize near mid-air collisions in the aircraft encounter dataset. We describe each discovered category in detail and discuss its relevance to aircraft collision avoidance.

An Improved Method for Producing High Spatial-Resolution NDVI Time Series Datasets with Multi-Temporal MODIS NDVI Data and Landsat TM/ETM+ Images

Directory of Open Access Journals (Sweden)

Yuhan Rao

2015-06-01

Full Text Available Due to technical limitations, it is impossible to have high resolution in both spatial and temporal dimensions for current NDVI datasets. Therefore, several methods are developed to produce high resolution (spatial and temporal NDVI time-series datasets, which face some limitations including high computation loads and unreasonable assumptions. In this study, an unmixing-based method, NDVI Linear Mixing Growth Model (NDVI-LMGM, is proposed to achieve the goal of accurately and efficiently blending MODIS NDVI time-series data and multi-temporal Landsat TM/ETM+ images. This method firstly unmixes the NDVI temporal changes in MODIS time-series to different land cover types and then uses unmixed NDVI temporal changes to predict Landsat-like NDVI dataset. The test over a forest site shows high accuracy (average difference: −0.0070; average absolute difference: 0.0228; and average absolute relative difference: 4.02% and computation efficiency of NDVI-LMGM (31 seconds using a personal computer. Experiments over more complex landscape and long-term time-series demonstrated that NDVI-LMGM performs well in each stage of vegetation growing season and is robust in regions with contrasting spatial and spatial variations. Comparisons between NDVI-LMGM and current methods (i.e., Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM, Enhanced STARFM (ESTARFM and Weighted Linear Model (WLM show that NDVI-LMGM is more accurate and efficient than current methods. The proposed method will benefit land surface process research, which requires a dense NDVI time-series dataset with high spatial resolution.

Time Series Discord Detection in Medical Data using a Parallel Relational Database

Energy Technology Data Exchange (ETDEWEB)

Woodbridge, Diane; Rintoul, Mark Daniel; Wilson, Andrew T.; Goldstein, Richard

2015-10-01

Recent advances in sensor technology have made continuous real-time health monitoring available in both hospital and non-hospital settings. Since data collected from high frequency medical sensors includes a huge amount of data, storing and processing continuous medical data is an emerging big data area. Especially detecting anomaly in real time is important for patients’ emergency detection and prevention. A time series discord indicates a subsequence that has the maximum difference to the rest of the time series subsequences, meaning that it has abnormal or unusual data trends. In this study, we implemented two versions of time series discord detection algorithms on a high performance parallel database management system (DBMS) and applied them to 240 Hz waveform data collected from 9,723 patients. The initial brute force version of the discord detection algorithm takes each possible subsequence and calculates a distance to the nearest non-self match to find the biggest discords in time series. For the heuristic version of the algorithm, a combination of an array and a trie structure was applied to order time series data for enhancing time efficiency. The study results showed efficient data loading, decoding and discord searches in a large amount of data, benefiting from the time series discord detection algorithm and the architectural characteristics of the parallel DBMS including data compression, data pipe-lining, and task scheduling.

WormSizer: high-throughput analysis of nematode size and shape.

Directory of Open Access Journals (Sweden)

Brad T Moore

Full Text Available The fundamental phenotypes of growth rate, size and morphology are the result of complex interactions between genotype and environment. We developed a high-throughput software application, WormSizer, which computes size and shape of nematodes from brightfield images. Existing methods for estimating volume either coarsely model the nematode as a cylinder or assume the worm shape or opacity is invariant. Our estimate is more robust to changes in morphology or optical density as it only assumes radial symmetry. This open source software is written as a plugin for the well-known image-processing framework Fiji/ImageJ. It may therefore be extended easily. We evaluated the technical performance of this framework, and we used it to analyze growth and shape of several canonical Caenorhabditis elegans mutants in a developmental time series. We confirm quantitatively that a Dumpy (Dpy mutant is short and fat and that a Long (Lon mutant is long and thin. We show that daf-2 insulin-like receptor mutants are larger than wild-type upon hatching but grow slow, and WormSizer can distinguish dauer larvae from normal larvae. We also show that a Small (Sma mutant is actually smaller than wild-type at all stages of larval development. WormSizer works with Uncoordinated (Unc and Roller (Rol mutants as well, indicating that it can be used with mutants despite behavioral phenotypes. We used our complete data set to perform a power analysis, giving users a sense of how many images are needed to detect different effect sizes. Our analysis confirms and extends on existing phenotypic characterization of well-characterized mutants, demonstrating the utility and robustness of WormSizer.

Simultaneous measurements of auto-immune and infectious disease specific antibodies using a high throughput multiplexing tool.

Directory of Open Access Journals (Sweden)

Atul Asati

Full Text Available Considering importance of ganglioside antibodies as biomarkers in various immune-mediated neuropathies and neurological disorders, we developed a high throughput multiplexing tool for the assessment of gangliosides-specific antibodies based on Biolpex/Luminex platform. In this report, we demonstrate that the ganglioside high throughput multiplexing tool is robust, highly specific and demonstrating ∼100-fold higher concentration sensitivity for IgG detection than ELISA. In addition to the ganglioside-coated array, the high throughput multiplexing tool contains beads coated with influenza hemagglutinins derived from H1N1 A/Brisbane/59/07 and H1N1 A/California/07/09 strains. Influenza beads provided an added advantage of simultaneous detection of ganglioside- and influenza-specific antibodies, a capacity important for the assay of both infectious antigen-specific and autoimmune antibodies following vaccination or disease. Taken together, these results support the potential adoption of the ganglioside high throughput multiplexing tool for measuring ganglioside antibodies in various neuropathic and neurological disorders.

EZH2 and CD79B mutational status over time in B-cell non-Hodgkin lymphomas detected by high-throughput sequencing using minimal samples

Science.gov (United States)

Saieg, Mauro Ajaj; Geddie, William R; Boerner, Scott L; Bailey, Denis; Crump, Michael; da Cunha Santos, Gilda

2013-01-01

BACKGROUND: Numerous genomic abnormalities in B-cell non-Hodgkin lymphomas (NHLs) have been revealed by novel high-throughput technologies, including recurrent mutations in EZH2 (enhancer of zeste homolog 2) and CD79B (B cell antigen receptor complex-associated protein beta chain) genes. This study sought to determine the evolution of the mutational status of EZH2 and CD79B over time in different samples from the same patient in a cohort of B-cell NHLs, through use of a customized multiplex mutation assay. METHODS: DNA that was extracted from cytological material stored on FTA cards as well as from additional specimens, including archived frozen and formalin-fixed histological specimens, archived stained smears, and cytospin preparations, were submitted to a multiplex mutation assay specifically designed for the detection of point mutations involving EZH2 and CD79B, using MassARRAY spectrometry followed by Sanger sequencing. RESULTS: All 121 samples from 80 B-cell NHL cases were successfully analyzed. Mutations in EZH2 (Y646) and CD79B (Y196) were detected in 13.2% and 8% of the samples, respectively, almost exclusively in follicular lymphomas and diffuse large B-cell lymphomas. In one-third of the positive cases, a wild type was detected in a different sample from the same patient during follow-up. CONCLUSIONS: Testing multiple minimal tissue samples using a high-throughput multiplex platform exponentially increases tissue availability for molecular analysis and might facilitate future studies of tumor progression and the related molecular events. Mutational status of EZH2 and CD79B may vary in B-cell NHL samples over time and support the concept that individualized therapy should be based on molecular findings at the time of treatment, rather than on results obtained from previous specimens. Cancer (Cancer Cytopathol) 2013;121:377–386. © 2013 American Cancer Society. PMID:23361872

Statistical criteria for characterizing irradiance time series.

Energy Technology Data Exchange (ETDEWEB)

Stein, Joshua S.; Ellis, Abraham; Hansen, Clifford W.

2010-10-01

We propose and examine several statistical criteria for characterizing time series of solar irradiance. Time series of irradiance are used in analyses that seek to quantify the performance of photovoltaic (PV) power systems over time. Time series of irradiance are either measured or are simulated using models. Simulations of irradiance are often calibrated to or generated from statistics for observed irradiance and simulations are validated by comparing the simulation output to the observed irradiance. Criteria used in this comparison should derive from the context of the analyses in which the simulated irradiance is to be used. We examine three statistics that characterize time series and their use as criteria for comparing time series. We demonstrate these statistics using observed irradiance data recorded in August 2007 in Las Vegas, Nevada, and in June 2009 in Albuquerque, New Mexico.

Modular high-throughput test stand for versatile screening of thin-film materials libraries

International Nuclear Information System (INIS)

Thienhaus, Sigurd; Hamann, Sven; Ludwig, Alfred

2011-01-01

Versatile high-throughput characterization tools are required for the development of new materials using combinatorial techniques. Here, we describe a modular, high-throughput test stand for the screening of thin-film materials libraries, which can carry out automated electrical, magnetic and magnetoresistance measurements in the temperature range of −40 to 300 °C. As a proof of concept, we measured the temperature-dependent resistance of Fe–Pd–Mn ferromagnetic shape-memory alloy materials libraries, revealing reversible martensitic transformations and the associated transformation temperatures. Magneto-optical screening measurements of a materials library identify ferromagnetic samples, whereas resistivity maps support the discovery of new phases. A distance sensor in the same setup allows stress measurements in materials libraries deposited on cantilever arrays. A combination of these methods offers a fast and reliable high-throughput characterization technology for searching for new materials. Using this approach, a composition region has been identified in the Fe–Pd–Mn system that combines ferromagnetism and martensitic transformation.

Homogenising time series: beliefs, dogmas and facts

Science.gov (United States)

Domonkos, P.

2011-06-01

In the recent decades various homogenisation methods have been developed, but the real effects of their application on time series are still not known sufficiently. The ongoing COST action HOME (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As a part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed time series. This dataset offers much better opportunity than ever before to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. Empirical results show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities often have similar statistical characteristics than natural changes caused by climatic variability, thus the pure application of the classic theory that change-points of observed time series can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of time series are usually much closer to the reality than in raw time series. Some problems around detecting multiple structures of inhomogeneities, as well as that of time series comparisons within homogenisation procedures are discussed briefly in the study.

Ocean time-series near Bermuda: Hydrostation S and the US JGOFS Bermuda Atlantic time-series study

Science.gov (United States)

Michaels, Anthony F.; Knap, Anthony H.

1992-01-01

Bermuda is the site of two ocean time-series programs. At Hydrostation S, the ongoing biweekly profiles of temperature, salinity and oxygen now span 37 years. This is one of the longest open-ocean time-series data sets and provides a view of decadal scale variability in ocean processes. In 1988, the U.S. JGOFS Bermuda Atlantic Time-series Study began a wide range of measurements at a frequency of 14-18 cruises each year to understand temporal variability in ocean biogeochemistry. On each cruise, the data range from chemical analyses of discrete water samples to data from electronic packages of hydrographic and optics sensors. In addition, a range of biological and geochemical rate measurements are conducted that integrate over time-periods of minutes to days. This sampling strategy yields a reasonable resolution of the major seasonal patterns and of decadal scale variability. The Sargasso Sea also has a variety of episodic production events on scales of days to weeks and these are only poorly resolved. In addition, there is a substantial amount of mesoscale variability in this region and some of the perceived temporal patterns are caused by the intersection of the biweekly sampling with the natural spatial variability. In the Bermuda time-series programs, we have added a series of additional cruises to begin to assess these other sources of variation and their impacts on the interpretation of the main time-series record. However, the adequate resolution of higher frequency temporal patterns will probably require the introduction of new sampling strategies and some emerging technologies such as biogeochemical moorings and autonomous underwater vehicles.

MGI-oriented High-throughput Measurement of Interdiffusion Coefficient Matrices in Ni-based Superalloys

Directory of Open Access Journals (Sweden)

TANG Ying

2017-01-01

Full Text Available One of the research hotspots in the field of high-temperature alloys was to search the substitutional elements for Re in order to prepare the single-crystal Ni-based superalloys with less or even no Re addition. To find the elements with similar or even lower diffusion coefficients in comparison with that of Re was one of the effective strategies. In multicomponent alloys, the interdiffusivity matrix were used to comprehensively characterize the diffusion ability of any alloying elements. Therefore, accurate determination of the composition-dependant and temperature-dependent interdiffusivities matrices of different elements in γ and γ' phases of Ni-based superalloys was high priority. The paper briefly introduces of the status of the interdiffusivity matrices determination in Ni-based superalloys, and the methods for determining the interdiffusivities in multicomponent alloys, including the traditional Matano-Kirkaldy method and recently proposed numerical inverse method. Because the traditional Matano-Kirkaldy method is of low efficiency, the experimental reports on interdiffusivity matrices in ternary and higher order sub-systems of the Ni-based superalloys were very scarce in the literature. While the numerical inverse method newly proposed in our research group based on Fick's second law can be utilized for high-throughput measurement of accurate interdiffusivity matrices in alloys with any number of components. After that, the successful application of the numerical inverse method in the high-throughput measurement of interdiffusivity matrices in alloys is demonstrated in fcc (γ phase of the ternary Ni-Al-Ta system. Moreover, the validation of the resulting composition-dependant and temperature-dependent interdiffusivity matrices is also comprehensively made. Then, this paper summarizes the recent progress in the measurement of interdiffusivity matrices in γ and γ' phases of a series of core ternary Ni-based superalloys achieved in

Application Of Empirical Phase Diagrams For Multidimensional Data Visualization Of High Throughput Microbatch Crystallization Experiments.

Science.gov (United States)

Klijn, Marieke E; Hubbuch, Jürgen

2018-04-27

Protein phase diagrams are a tool to investigate cause and consequence of solution conditions on protein phase behavior. The effects are scored according to aggregation morphologies such as crystals or amorphous precipitates. Solution conditions affect morphological features, such as crystal size, as well as kinetic features, such as crystal growth time. Common used data visualization techniques include individual line graphs or symbols-based phase diagrams. These techniques have limitations in terms of handling large datasets, comprehensiveness or completeness. To eliminate these limitations, morphological and kinetic features obtained from crystallization images generated with high throughput microbatch experiments have been visualized with radar charts in combination with the empirical phase diagram (EPD) method. Morphological features (crystal size, shape, and number, as well as precipitate size) and kinetic features (crystal and precipitate onset and growth time) are extracted for 768 solutions with varying chicken egg white lysozyme concentration, salt type, ionic strength and pH. Image-based aggregation morphology and kinetic features were compiled into a single and easily interpretable figure, thereby showing that the EPD method can support high throughput crystallization experiments in its data amount as well as its data complexity. Copyright © 2018. Published by Elsevier Inc.

SensL B-Series and C-Series silicon photomultipliers for time-of-flight positron emission tomography

Energy Technology Data Exchange (ETDEWEB)

O' Neill, K., E-mail: koneill@sensl.com; Jackson, C., E-mail: cjackson@sensl.com

2015-07-01

Silicon photomultipliers from SensL are designed for high performance, uniformity and low cost. They demonstrate peak photon detection efficiency of 41% at 420 nm, which is matched to the output spectrum of cerium doped lutetium orthosilicate. Coincidence resolving time of less than 220 ps is demonstrated. New process improvements have lead to the development of C-Series SiPM which reduces the dark noise by over an order of magnitude. In this paper we will show characterization test results which include photon detection efficiency, dark count rate, crosstalk probability, afterpulse probability and coincidence resolving time comparing B-Series to the newest pre-production C-Series. Additionally we will discuss the effect of silicon photomultiplier microcell size on coincidence resolving time allowing the optimal microcell size choice to be made for time of flight positron emission tomography systems.

Spectrophotometric Enzyme Assays for High-Throughput Screening

Directory of Open Access Journals (Sweden)

Jean-Louis Reymond

2004-01-01

Full Text Available This paper reviews high-throughput screening enzyme assays developed in our laboratory over the last ten years. These enzyme assays were initially developed for the purpose of discovering catalytic antibodies by screening cell culture supernatants, but have proved generally useful for testing enzyme activities. Examples include TLC-based screening using acridone-labeled substrates, fluorogenic assays based on the β-elimination of umbelliferone or nitrophenol, and indirect assays such as the back-titration method with adrenaline and the copper-calcein fluorescence assay for aminoacids.

High-throughput and low-latency network communication with NetIO

CERN Document Server

AUTHOR|(CDS)2088631; The ATLAS collaboration

2017-01-01

HPC network technologies like Infiniband, TrueScale or OmniPath provide low-latency and high-throughput communication between hosts, which makes them attractive options for data-acquisition systems in large-scale high-energy physics experiments. Like HPC networks, DAQ networks are local and include a well specified number of systems. Unfortunately traditional network communication APIs for HPC clusters like MPI or PGAS target exclusively the HPC community and are not suited well for DAQ applications. It is possible to build distributed DAQ applications using low-level system APIs like Infiniband Verbs, but it requires a non-negligible effort and expert knowledge. At the same time, message services like ZeroMQ have gained popularity in the HEP community. They allow building distributed applications with a high-level approach and provide good performance. Unfortunately their usage usually limits developers to TCP/IP-based networks. While it is possible to operate a TCP/IP stack on top of Infiniband and OmniPath...

High-resolution and high-throughput multichannel Fourier transform spectrometer with two-dimensional interferogram warping compensation

Science.gov (United States)

Watanabe, A.; Furukawa, H.

2018-04-01

The resolution of multichannel Fourier transform (McFT) spectroscopy is insufficient for many applications despite its extreme advantage of high throughput. We propose an improved configuration to realise both performance using a two-dimensional area sensor. For the spectral resolution, we obtained the interferogram of a larger optical path difference by shifting the area sensor without altering any optical components. The non-linear phase error of the interferometer was successfully corrected using a phase-compensation calculation. Warping compensation was also applied to realise a higher throughput to accumulate the signal between vertical pixels. Our approach significantly improved the resolution and signal-to-noise ratio by factors of 1.7 and 34, respectively. This high-resolution and high-sensitivity McFT spectrometer will be useful for detecting weak light signals such as those in non-invasive diagnosis.

Kinetic Titration Series with Biolayer Interferometry

Science.gov (United States)

Frenzel, Daniel; Willbold, Dieter

2014-01-01

Biolayer interferometry is a method to analyze protein interactions in real-time. In this study, we illustrate the usefulness to quantitatively analyze high affinity protein ligand interactions employing a kinetic titration series for characterizing the interactions between two pairs of interaction patterns, in particular immunoglobulin G and protein G B1 as well as scFv IC16 and amyloid beta (1–42). Kinetic titration series are commonly used in surface plasmon resonance and involve sequential injections of analyte over a desired concentration range on a single ligand coated sensor chip without waiting for complete dissociation between the injections. We show that applying this method to biolayer interferometry is straightforward and i) circumvents problems in data evaluation caused by unavoidable sensor differences, ii) saves resources and iii) increases throughput if screening a multitude of different analyte/ligand combinations. PMID:25229647

Multivariate Time Series Decomposition into Oscillation Components.

Science.gov (United States)

Matsuda, Takeru; Komaki, Fumiyasu

2017-08-01

Many time series are considered to be a superposition of several oscillation components. We have proposed a method for decomposing univariate time series into oscillation components and estimating their phases (Matsuda & Komaki, 2017 ). In this study, we extend that method to multivariate time series. We assume that several oscillators underlie the given multivariate time series and that each variable corresponds to a superposition of the projections of the oscillators. Thus, the oscillators superpose on each variable with amplitude and phase modulation. Based on this idea, we develop gaussian linear state-space models and use them to decompose the given multivariate time series. The model parameters are estimated from data using the empirical Bayes method, and the number of oscillators is determined using the Akaike information criterion. Therefore, the proposed method extracts underlying oscillators in a data-driven manner and enables investigation of phase dynamics in a given multivariate time series. Numerical results show the effectiveness of the proposed method. From monthly mean north-south sunspot number data, the proposed method reveals an interesting phase relationship.

Multiplexed homogeneous proximity ligation assays for high throughput protein biomarker research in serological material

DEFF Research Database (Denmark)

Lundberg, Martin; Thorsen, Stine Buch; Assarsson, Erika

2011-01-01

A high throughput protein biomarker discovery tool has been developed based on multiplexed proximity ligation assays (PLA) in a homogeneous format in the sense of no washing steps. The platform consists of four 24-plex panels profiling 74 putative biomarkers with sub pM sensitivity each consuming...... sequences are united by DNA ligation upon simultaneous target binding forming a PCR amplicon. Multiplex PLA thereby converts multiple target analytes into real-time PCR amplicons that are individually quantificatied using microfluidic high capacity qPCR in nano liter volumes. The assay shows excellent...

High throughput, multiplexed pathogen detection authenticates plague waves in medieval Venice, Italy.

Science.gov (United States)

Tran, Thi-Nguyen-Ny; Signoli, Michel; Fozzati, Luigi; Aboudharam, Gérard; Raoult, Didier; Drancourt, Michel

2011-03-10

Historical records suggest that multiple burial sites from the 14th-16th centuries in Venice, Italy, were used during the Black Death and subsequent plague epidemics. High throughput, multiplexed real-time PCR detected DNA of seven highly transmissible pathogens in 173 dental pulp specimens collected from 46 graves. Bartonella quintana DNA was identified in five (2.9%) samples, including three from the 16th century and two from the 15th century, and Yersinia pestis DNA was detected in three (1.7%) samples, including two from the 14th century and one from the 16th century. Partial glpD gene sequencing indicated that the detected Y. pestis was the Orientalis biotype. These data document for the first time successive plague epidemics in the medieval European city where quarantine was first instituted in the 14th century.

Forecasting Enrollments with Fuzzy Time Series.

Science.gov (United States)

Song, Qiang; Chissom, Brad S.

The concept of fuzzy time series is introduced and used to forecast the enrollment of a university. Fuzzy time series, an aspect of fuzzy set theory, forecasts enrollment using a first-order time-invariant model. To evaluate the model, the conventional linear regression technique is applied and the predicted values obtained are compared to the…

Computational tools for high-throughput discovery in biology

OpenAIRE

Jones, Neil Christopher

2007-01-01

High throughput data acquisition technology has inarguably transformed the landscape of the life sciences, in part by making possible---and necessary---the computational disciplines of bioinformatics and biomedical informatics. These fields focus primarily on developing tools for analyzing data and generating hypotheses about objects in nature, and it is in this context that we address three pressing problems in the fields of the computational life sciences which each require computing capaci...

A comparison of high-throughput techniques for assaying circadian rhythms in plants.

Science.gov (United States)

Tindall, Andrew J; Waller, Jade; Greenwood, Mark; Gould, Peter D; Hartwell, James; Hall, Anthony

2015-01-01

Over the last two decades, the development of high-throughput techniques has enabled us to probe the plant circadian clock, a key coordinator of vital biological processes, in ways previously impossible. With the circadian clock increasingly implicated in key fitness and signalling pathways, this has opened up new avenues for understanding plant development and signalling. Our tool-kit has been constantly improving through continual development and novel techniques that increase throughput, reduce costs and allow higher resolution on the cellular and subcellular levels. With circadian assays becoming more accessible and relevant than ever to researchers, in this paper we offer a review of the techniques currently available before considering the horizons in circadian investigation at ever higher throughputs and resolutions.

A high-throughput method for GMO multi-detection using a microfluidic dynamic array.

Science.gov (United States)

Brod, Fábio Cristiano Angonesi; van Dijk, Jeroen P; Voorhuijzen, Marleen M; Dinon, Andréia Zilio; Guimarães, Luis Henrique S; Scholtens, Ingrid M J; Arisi, Ana Carolina Maisonnave; Kok, Esther J

2014-02-01

The ever-increasing production of genetically modified crops generates a demand for high-throughput DNA-based methods for the enforcement of genetically modified organisms (GMO) labelling requirements. The application of standard real-time PCR will become increasingly costly with the growth of the number of GMOs that is potentially present in an individual sample. The present work presents the results of an innovative approach in genetically modified crops analysis by DNA based methods, which is the use of a microfluidic dynamic array as a high throughput multi-detection system. In order to evaluate the system, six test samples with an increasing degree of complexity were prepared, preamplified and subsequently analysed in the Fluidigm system. Twenty-eight assays targeting different DNA elements, GM events and species-specific reference genes were used in the experiment. The large majority of the assays tested presented expected results. The power of low level detection was assessed and elements present at concentrations as low as 0.06 % were successfully detected. The approach proposed in this work presents the Fluidigm system as a suitable and promising platform for GMO multi-detection.

Coded throughput performance simulations for the time-varying satellite channel. M.S. Thesis

Science.gov (United States)

Han, LI

1995-01-01

The design of a reliable satellite communication link involving the data transfer from a small, low-orbit satellite to a ground station, but through a geostationary satellite, was examined. In such a scenario, the received signal power to noise density ratio increases as the transmitting low-orbit satellite comes into view, and then decreases as it then departs, resulting in a short-duration, time-varying communication link. The optimal values of the small satellite antenna beamwidth, signaling rate, modulation scheme and the theoretical link throughput (in bits per day) have been determined. The goal of this thesis is to choose a practical coding scheme which maximizes the daily link throughput while satisfying a prescribed probability of error requirement. We examine the throughput of both fixed rate and variable rate concatenated forward error correction (FEC) coding schemes for the additive white Gaussian noise (AWGN) channel, and then examine the effect of radio frequency interference (RFI) on the best coding scheme among them. Interleaving is used to mitigate degradation due to RFI. It was found that the variable rate concatenated coding scheme could achieve 74 percent of the theoretical throughput, equivalent to 1.11 Gbits/day based on the cutoff rate R(sub 0). For comparison, 87 percent is achievable for AWGN-only case.

High-throughput microplate technique for enzymatic hydrolysis of lignocellulosic biomass.

Science.gov (United States)

Chundawat, Shishir P S; Balan, Venkatesh; Dale, Bruce E

2008-04-15

Several factors will influence the viability of a biochemical platform for manufacturing lignocellulosic based fuels and chemicals, for example, genetically engineering energy crops, reducing pre-treatment severity, and minimizing enzyme loading. Past research on biomass conversion has focused largely on acid based pre-treatment technologies that fractionate lignin and hemicellulose from cellulose. However, for alkaline based (e.g., AFEX) and other lower severity pre-treatments it becomes critical to co-hydrolyze cellulose and hemicellulose using an optimized enzyme cocktail. Lignocellulosics are appropriate substrates to assess hydrolytic activity of enzyme mixtures compared to conventional unrealistic substrates (e.g., filter paper, chromogenic, and fluorigenic compounds) for studying synergistic hydrolysis. However, there are few, if any, high-throughput lignocellulosic digestibility analytical platforms for optimizing biomass conversion. The 96-well Biomass Conversion Research Lab (BCRL) microplate method is a high-throughput assay to study digestibility of lignocellulosic biomass as a function of biomass composition, pre-treatment severity, and enzyme composition. The most suitable method for delivering milled biomass to the microplate was through multi-pipetting slurry suspensions. A rapid bio-enzymatic, spectrophotometric assay was used to determine fermentable sugars. The entire procedure was automated using a robotic pipetting workstation. Several parameters that affect hydrolysis in the microplate were studied and optimized (i.e., particle size reduction, slurry solids concentration, glucan loading, mass transfer issues, and time period for hydrolysis). The microplate method was optimized for crystalline cellulose (Avicel) and ammonia fiber expansion (AFEX) pre-treated corn stover. Copyright 2008 Wiley Periodicals, Inc.

A high-throughput two channel discrete wavelet transform architecture for the JPEG2000 standard

Science.gov (United States)

Badakhshannoory, Hossein; Hashemi, Mahmoud R.; Aminlou, Alireza; Fatemi, Omid

2005-07-01

The Discrete Wavelet Transform (DWT) is increasingly recognized in image and video compression standards, as indicated by its use in JPEG2000. The lifting scheme algorithm is an alternative DWT implementation that has a lower computational complexity and reduced resource requirement. In the JPEG2000 standard two lifting scheme based filter banks are introduced: the 5/3 and 9/7. In this paper a high throughput, two channel DWT architecture for both of the JPEG2000 DWT filters is presented. The proposed pipelined architecture has two separate input channels that process the incoming samples simultaneously with minimum memory requirement for each channel. The architecture had been implemented in VHDL and synthesized on a Xilinx Virtex2 XCV1000. The proposed architecture applies DWT on a 2K by 1K image at 33 fps with a 75 MHZ clock frequency. This performance is achieved with 70% less resources than two independent single channel modules. The high throughput and reduced resource requirement has made this architecture the proper choice for real time applications such as Digital Cinema.

Engineering a vitamin B12 high-throughput screening system by riboswitch sensor in Sinorhizobium meliloti.

Science.gov (United States)

Cai, Yingying; Xia, Miaomiao; Dong, Huina; Qian, Yuan; Zhang, Tongcun; Zhu, Beiwei; Wu, Jinchuan; Zhang, Dawei

2018-05-11

As a very important coenzyme in the cell metabolism, Vitamin B 12 (cobalamin, VB 12 ) has been widely used in food and medicine fields. The complete biosynthesis of VB 12 requires approximately 30 genes, but overexpression of these genes did not result in expected increase of VB 12 production. High-yield VB 12 -producing strains are usually obtained by mutagenesis treatments, thus developing an efficient screening approach is urgently needed. By the help of engineered strains with varied capacities of VB 12 production, a riboswitch library was constructed and screened, and the btuB element from Salmonella typhimurium was identified as the best regulatory device. A flow cytometry high-throughput screening system was developed based on the btuB riboswitch with high efficiency to identify positive mutants. Mutation of Sinorhizobium meliloti (S. meliloti) was optimized using the novel mutation technique of atmospheric and room temperature plasma (ARTP). Finally, the mutant S. meliloti MC5-2 was obtained and considered as a candidate for industrial applications. After 7 d's cultivation on a rotary shaker at 30 °C, the VB 12 titer of S. meliloti MC5-2 reached 156 ± 4.2 mg/L, which was 21.9% higher than that of the wild type strain S. meliloti 320 (128 ± 3.2 mg/L). The genome of S. meliloti MC5-2 was sequenced, and gene mutations were identified and analyzed. To our knowledge, it is the first time that a riboswitch element was used in S. meliloti. The flow cytometry high-throughput screening system was successfully developed and a high-yield VB 12 producing strain was obtained. The identified and analyzed gene mutations gave useful information for developing high-yield strains by metabolic engineering. Overall, this work provides a useful high-throughput screening method for developing high VB 12 -yield strains.

Use of a Fluorometric Imaging Plate Reader in high-throughput screening

Science.gov (United States)

Groebe, Duncan R.; Gopalakrishnan, Sujatha; Hahn, Holly; Warrior, Usha; Traphagen, Linda; Burns, David J.

1999-04-01

High-throughput screening (HTS) efforts at Abbott Laboratories have been greatly facilitated by the use of a Fluorometric Imaging Plate Reader. The FLIPR consists of an incubated cabinet with integrated 96-channel pipettor and fluorometer. An argon laser is used to excite fluorophores in a 96-well microtiter plate and the emitted fluorometer. An argon laser is used to excite fluorophores in a 96-well microtiter plate and the emitted fluorescence is imaged by a cooled CCD camera. The image data is downloaded from the camera and processed to average the signal form each well of the microtiter pate for each time point. The data is presented in real time on the computer screen, facilitating interpretation and trouble-shooting. In addition to fluorescence, the camera can also detect luminescence form firefly luciferase.

The JCSG high-throughput structural biology pipeline

International Nuclear Information System (INIS)

Elsliger, Marc-André; Deacon, Ashley M.; Godzik, Adam; Lesley, Scott A.; Wooley, John; Wüthrich, Kurt; Wilson, Ian A.

2010-01-01

The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years and has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe. The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years. The JCSG has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe, as well as making substantial inroads into structural coverage of an entire organism. Targets are processed through an extensive combination of bioinformatics and biophysical analyses to efficiently characterize and optimize each target prior to selection for structure determination. The pipeline uses parallel processing methods at almost every step in the process and can adapt to a wide range of protein targets from bacterial to human. The construction, expansion and optimization of the JCSG gene-to-structure pipeline over the years have resulted in many technological and methodological advances and developments. The vast number of targets and the enormous amounts of associated data processed through the multiple stages of the experimental pipeline required the development of variety of valuable resources that, wherever feasible, have been converted to free-access web-based tools and applications

High-throughput selection for cellulase catalysts using chemical complementation.

Science.gov (United States)

Peralta-Yahya, Pamela; Carter, Brian T; Lin, Hening; Tao, Haiyan; Cornish, Virginia W

2008-12-24

Efficient enzymatic hydrolysis of lignocellulosic material remains one of the major bottlenecks to cost-effective conversion of biomass to ethanol. Improvement of glycosylhydrolases, however, is limited by existing medium-throughput screening technologies. Here, we report the first high-throughput selection for cellulase catalysts. This selection was developed by adapting chemical complementation to provide a growth assay for bond cleavage reactions. First, a URA3 counter selection was adapted to link chemical dimerizer activated gene transcription to cell death. Next, the URA3 counter selection was shown to detect cellulase activity based on cleavage of a tetrasaccharide chemical dimerizer substrate and decrease in expression of the toxic URA3 reporter. Finally, the utility of the cellulase selection was assessed by isolating cellulases with improved activity from a cellulase library created by family DNA shuffling. This application provides further evidence that chemical complementation can be readily adapted to detect different enzymatic activities for important chemical transformations for which no natural selection exists. Because of the large number of enzyme variants that selections can now test as compared to existing medium-throughput screens for cellulases, this assay has the potential to impact the discovery of improved cellulases and other glycosylhydrolases for biomass conversion from libraries of cellulases created by mutagenesis or obtained from natural biodiversity.

Blood group genotyping: from patient to high-throughput donor screening.

Science.gov (United States)

Veldhuisen, B; van der Schoot, C E; de Haas, M

2009-10-01

Blood group antigens, present on the cell membrane of red blood cells and platelets, can be defined either serologically or predicted based on the genotypes of genes encoding for blood group antigens. At present, the molecular basis of many antigens of the 30 blood group systems and 17 human platelet antigens is known. In many laboratories, blood group genotyping assays are routinely used for diagnostics in cases where patient red cells cannot be used for serological typing due to the presence of auto-antibodies or after recent transfusions. In addition, DNA genotyping is used to support (un)-expected serological findings. Fetal genotyping is routinely performed when there is a risk of alloimmune-mediated red cell or platelet destruction. In case of patient blood group antigen typing, it is important that a genotyping result is quickly available to support the selection of donor blood, and high-throughput of the genotyping method is not a prerequisite. In addition, genotyping of blood donors will be extremely useful to obtain donor blood with rare phenotypes, for example lacking a high-frequency antigen, and to obtain a fully typed donor database to be used for a better matching between recipient and donor to prevent adverse transfusion reactions. Serological typing of large cohorts of donors is a labour-intensive and expensive exercise and hampered by the lack of sufficient amounts of approved typing reagents for all blood group systems of interest. Currently, high-throughput genotyping based on DNA micro-arrays is a very feasible method to obtain a large pool of well-typed blood donors. Several systems for high-throughput blood group genotyping are developed and will be discussed in this review.

Development and operation of a high-throughput accurate-wavelength lens-based spectrometer

Energy Technology Data Exchange (ETDEWEB)

Bell, Ronald E., E-mail: rbell@pppl.gov [Princeton Plasma Physics Laboratory, Princeton, New Jersey 08543 (United States)

2014-11-15

A high-throughput spectrometer for the 400–820 nm wavelength range has been developed for charge exchange recombination spectroscopy or general spectroscopy. A large 2160 mm{sup −1} grating is matched with fast f/1.8 200 mm lenses, which provide stigmatic imaging. A precision optical encoder measures the grating angle with an accuracy ≤0.075 arc sec. A high quantum efficiency low-etaloning CCD detector allows operation at longer wavelengths. A patch panel allows input fibers to interface with interchangeable fiber holders that attach to a kinematic mount at the entrance slit. Computer-controlled hardware allows automated control of wavelength, timing, f-number, automated data collection, and wavelength calibration.

Factors impacting arthroscopic rotator cuff repair operational throughput time at an ambulatory care center

Directory of Open Access Journals (Sweden)

Emily J. Curry

2018-03-01

Full Text Available Identifying patient factors influencing operational throughput time is becoming more imperative due to an increasing focus on value and cost savings in healthcare. The primary objective of this study was to determine patient factors influencing throughput time for primary rotator cuff repairs. Demographic information, medical history and operative reports of 318 patients from one ambulatory care center were retrospectively reviewed. Operating room set up, incision to closure and recovery room time were collected from anesthesia records. Univariate analysis was performed for both continuous and categorical variables. A stepwise, multivariable regression analysis was performed to determine factors associated with operating room time (incision to closure and recovery room time. Of the 318 patients, the mean age was 54.4±10.0 and 197 (61% were male. Male patients had a significantly longer OR time than females (115.5 vs. 100.8 minutes; P<0.001. Furthermore, patients set up in the beach chair position had a significantly longer OR time than patients positioned lateral decubitus (115.8 vs. 89.6 mins, P<0.0001. Number of tendons involved, and inclusion of distal clavicle excision, biceps tenodesis and labral debridement also added significant OR time. Type and number of support staff present also significantly affected OR time. Recovery room time was significantly longer patients who had surgery in the beach chair position (+9.61 minutes and for those who had a cardiac-related medical comorbidity (+11.7 minutes. Our study found that patients positioned in a beach chair spent significantly more time in the operating and recovery rooms. While ease of set up has been a stated advantage ofbeach chair position, we found the perceived ease of set up does not result in more efficient OR throughput.

High-throughput assessment of context-dependent effects of chromatin proteins

NARCIS (Netherlands)

Brueckner, L. (Laura); Van Arensbergen, J. (Joris); Akhtar, W. (Waseem); L. Pagie (Ludo); B. van Steensel (Bas)

2016-01-01

textabstractBackground: Chromatin proteins control gene activity in a concerted manner. We developed a high-throughput assay to study the effects of the local chromatin environment on the regulatory activity of a protein of interest. The assay combines a previously reported multiplexing strategy

High-throughput open source computational methods for genetics and genomics

NARCIS (Netherlands)

Prins, J.C.P.

2015-01-01

Biology is increasingly data driven by virtue of the development of high-throughput technologies, such as DNA and RNA sequencing. Computational biology and bioinformatics are scientific disciplines that cross-over between the disciplines of biology, informatics and statistics; which is clearly

tcpl: The ToxCast Pipeline for High-Throughput Screening Data

Science.gov (United States)

Motivation: The large and diverse high-throughput chemical screening efforts carried out by the US EPAToxCast program requires an efficient, transparent, and reproducible data pipeline.Summary: The tcpl R package and its associated MySQL database provide a generalized platform fo...

Useful Pattern Mining on Time Series

DEFF Research Database (Denmark)

Goumatianos, Nikitas; Christou, Ioannis T; Lindgren, Peter

2013-01-01

We present the architecture of a “useful pattern” mining system that is capable of detecting thousands of different candlestick sequence patterns at the tick or any higher granularity levels. The system architecture is highly distributed and performs most of its highly compute-intensive aggregation...... calculations as complex but efficient distributed SQL queries on the relational databases that store the time-series. We present initial results from mining all frequent candlestick sequences with the characteristic property that when they occur then, with an average at least 60% probability, they signal a 2...

Forecasting Cryptocurrencies Financial Time Series

DEFF Research Database (Denmark)

Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco

2018-01-01

This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely...

Forecasting Cryptocurrencies Financial Time Series

OpenAIRE

Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco

2018-01-01

This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely on Dynamic Model Averaging to combine a large set of univariate Dynamic Linear Models and several multivariate Vector Autoregressive models with different forms of time variation. We find statistical si...

Combinatorial chemoenzymatic synthesis and high-throughput screening of sialosides.

Science.gov (United States)

Chokhawala, Harshal A; Huang, Shengshu; Lau, Kam; Yu, Hai; Cheng, Jiansong; Thon, Vireak; Hurtado-Ziola, Nancy; Guerrero, Juan A; Varki, Ajit; Chen, Xi

2008-09-19

Although the vital roles of structures containing sialic acid in biomolecular recognition are well documented, limited information is available on how sialic acid structural modifications, sialyl linkages, and the underlying glycan structures affect the binding or the activity of sialic acid-recognizing proteins and related downstream biological processes. A novel combinatorial chemoenzymatic method has been developed for the highly efficient synthesis of biotinylated sialosides containing different sialic acid structures and different underlying glycans in 96-well plates from biotinylated sialyltransferase acceptors and sialic acid precursors. By transferring the reaction mixtures to NeutrAvidin-coated plates and assaying for the yields of enzymatic reactions using lectins recognizing sialyltransferase acceptors but not the sialylated products, the biotinylated sialoside products can be directly used, without purification, for high-throughput screening to quickly identify the ligand specificity of sialic acid-binding proteins. For a proof-of-principle experiment, 72 biotinylated alpha2,6-linked sialosides were synthesized in 96-well plates from 4 biotinylated sialyltransferase acceptors and 18 sialic acid precursors using a one-pot three-enzyme system. High-throughput screening assays performed in NeutrAvidin-coated microtiter plates show that whereas Sambucus nigra Lectin binds to alpha2,6-linked sialosides with high promiscuity, human Siglec-2 (CD22) is highly selective for a number of sialic acid structures and the underlying glycans in its sialoside ligands.

High Channel Count Time-to-Digital Converter and Lasercom Processor, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — High-channel-count, high-precision, and high-throughput time-to-digital converters (TDC) are needed to support detector arrays used in deep-space optical...

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

Science.gov (United States)

Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio

2015-12-01

This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.

40 CFR Table 3 to Subpart Eeee of... - Operating Limits-High Throughput Transfer Racks

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 12 2010-07-01 2010-07-01 true Operating Limits-High Throughput Transfer Racks 3 Table 3 to Subpart EEEE of Part 63 Protection of Environment ENVIRONMENTAL PROTECTION... Throughput Transfer Racks As stated in § 63.2346(e), you must comply with the operating limits for existing...

Time series modeling, computation, and inference

CERN Document Server

Prado, Raquel

2010-01-01

The authors systematically develop a state-of-the-art analysis and modeling of time series. … this book is well organized and well written. The authors present various statistical models for engineers to solve problems in time series analysis. Readers no doubt will learn state-of-the-art techniques from this book.-Hsun-Hsien Chang, Computing Reviews, March 2012My favorite chapters were on dynamic linear models and vector AR and vector ARMA models.-William Seaver, Technometrics, August 2011… a very modern entry to the field of time-series modelling, with a rich reference list of the current lit

Time Series Analysis Forecasting and Control

CERN Document Server

Box, George E P; Reinsel, Gregory C

2011-01-01

A modernized new edition of one of the most trusted books on time series analysis. Since publication of the first edition in 1970, Time Series Analysis has served as one of the most influential and prominent works on the subject. This new edition maintains its balanced presentation of the tools for modeling and analyzing time series and also introduces the latest developments that have occurred n the field over the past decade through applications from areas such as business, finance, and engineering. The Fourth Edition provides a clearly written exploration of the key methods for building, cl

Management of High-Throughput DNA Sequencing Projects: Alpheus.

Science.gov (United States)

Miller, Neil A; Kingsmore, Stephen F; Farmer, Andrew; Langley, Raymond J; Mudge, Joann; Crow, John A; Gonzalez, Alvaro J; Schilkey, Faye D; Kim, Ryan J; van Velkinburgh, Jennifer; May, Gregory D; Black, C Forrest; Myers, M Kathy; Utsey, John P; Frost, Nicholas S; Sugarbaker, David J; Bueno, Raphael; Gullans, Stephen R; Baxter, Susan M; Day, Steve W; Retzel, Ernest F

2008-12-26

High-throughput DNA sequencing has enabled systems biology to begin to address areas in health, agricultural and basic biological research. Concomitant with the opportunities is an absolute necessity to manage significant volumes of high-dimensional and inter-related data and analysis. Alpheus is an analysis pipeline, database and visualization software for use with massively parallel DNA sequencing technologies that feature multi-gigabase throughput characterized by relatively short reads, such as Illumina-Solexa (sequencing-by-synthesis), Roche-454 (pyrosequencing) and Applied Biosystem's SOLiD (sequencing-by-ligation). Alpheus enables alignment to reference sequence(s), detection of variants and enumeration of sequence abundance, including expression levels in transcriptome sequence. Alpheus is able to detect several types of variants, including non-synonymous and synonymous single nucleotide polymorphisms (SNPs), insertions/deletions (indels), premature stop codons, and splice isoforms. Variant detection is aided by the ability to filter variant calls based on consistency, expected allele frequency, sequence quality, coverage, and variant type in order to minimize false positives while maximizing the identification of true positives. Alpheus also enables comparisons of genes with variants between cases and controls or bulk segregant pools. Sequence-based differential expression comparisons can be developed, with data export to SAS JMP Genomics for statistical analysis.

High-Throughput Next-Generation Sequencing of Polioviruses

Science.gov (United States)

Montmayeur, Anna M.; Schmidt, Alexander; Zhao, Kun; Magaña, Laura; Iber, Jane; Castro, Christina J.; Chen, Qi; Henderson, Elizabeth; Ramos, Edward; Shaw, Jing; Tatusov, Roman L.; Dybdahl-Sissoko, Naomi; Endegue-Zanga, Marie Claire; Adeniji, Johnson A.; Oberste, M. Steven; Burns, Cara C.

2016-01-01

ABSTRACT The poliovirus (PV) is currently targeted for worldwide eradication and containment. Sanger-based sequencing of the viral protein 1 (VP1) capsid region is currently the standard method for PV surveillance. However, the whole-genome sequence is sometimes needed for higher resolution global surveillance. In this study, we optimized whole-genome sequencing protocols for poliovirus isolates and FTA cards using next-generation sequencing (NGS), aiming for high sequence coverage, efficiency, and throughput. We found that DNase treatment of poliovirus RNA followed by random reverse transcription (RT), amplification, and the use of the Nextera XT DNA library preparation kit produced significantly better results than other preparations. The average viral reads per total reads, a measurement of efficiency, was as high as 84.2% ± 15.6%. PV genomes covering >99 to 100% of the reference length were obtained and validated with Sanger sequencing. A total of 52 PV genomes were generated, multiplexing as many as 64 samples in a single Illumina MiSeq run. This high-throughput, sequence-independent NGS approach facilitated the detection of a diverse range of PVs, especially for those in vaccine-derived polioviruses (VDPV), circulating VDPV, or immunodeficiency-related VDPV. In contrast to results from previous studies on other viruses, our results showed that filtration and nuclease treatment did not discernibly increase the sequencing efficiency of PV isolates. However, DNase treatment after nucleic acid extraction to remove host DNA significantly improved the sequencing results. This NGS method has been successfully implemented to generate PV genomes for molecular epidemiology of the most recent PV isolates. Additionally, the ability to obtain full PV genomes from FTA cards will aid in facilitating global poliovirus surveillance. PMID:27927929

Satellite image time series simulation for environmental monitoring

Science.gov (United States)

Guo, Tao

2014-11-01

The performance of environmental monitoring heavily depends on the availability of consecutive observation data and it turns out an increasing demand in remote sensing community for satellite image data in the sufficient resolution with respect to both spatial and temporal requirements, which appear to be conflictive and hard to tune tradeoffs. Multiple constellations could be a solution if without concerning cost, and thus it is so far interesting but very challenging to develop a method which can simultaneously improve both spatial and temporal details. There are some research efforts to deal with the problem from various aspects, a type of approaches is to enhance the spatial resolution using techniques of super resolution, pan-sharpen etc. which can produce good visual effects, but mostly cannot preserve spectral signatures and result in losing analytical value. Another type is to fill temporal frequency gaps by adopting time interpolation, which actually doesn't increase informative context at all. In this paper we presented a novel method to generate satellite images in higher spatial and temporal details, which further enables satellite image time series simulation. Our method starts with a pair of high-low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and the temporal change is then projected onto high resolution data plane and assigned to each high resolution pixel referring the predefined temporal change patterns of each type of ground objects to generate a simulated high resolution data. A preliminary experiment shows that our method can simulate a high resolution data with a good accuracy. We consider the contribution of our method is to enable timely monitoring of temporal changes through analysis of low resolution images time series only, and usage of

Robotic high-throughput purification of affinity-tagged recombinant proteins.

Science.gov (United States)

Wiesler, Simone C; Weinzierl, Robert O J

2015-01-01

Affinity purification of recombinant proteins has become the method of choice to obtain good quantities and qualities of proteins for a variety of downstream biochemical applications. While manual or FPLC-assisted purification techniques are generally time-consuming and labor-intensive, the advent of high-throughput technologies and liquid handling robotics has simplified and accelerated this process significantly. Additionally, without the human factor as a potential source of error, automated purification protocols allow for the generation of large numbers of proteins simultaneously and under directly comparable conditions. The delivered material is ideal for activity comparisons of different variants of the same protein. Here, we present our strategy for the simultaneous purification of up to 24 affinity-tagged proteins for activity measurements in biochemical assays. The protocol described is suitable for the scale typically required in individual research laboratories.

Costationarity of Locally Stationary Time Series Using costat

OpenAIRE

Cardinali, Alessandro; Nason, Guy P.

2013-01-01

This article describes the R package costat. This package enables a user to (i) perform a test for time series stationarity; (ii) compute and plot time-localized autocovariances, and (iii) to determine and explore any costationary relationship between two locally stationary time series. Two locally stationary time series are said to be costationary if there exists two time-varying combination functions such that the linear combination of the two series with the functions produces another time...

High throughput nanostructure-initiator mass spectrometry screening of microbial growth conditions for maximal β-glucosidase production.

Science.gov (United States)

Cheng, Xiaoliang; Hiras, Jennifer; Deng, Kai; Bowen, Benjamin; Simmons, Blake A; Adams, Paul D; Singer, Steven W; Northen, Trent R

2013-01-01

Production of biofuels via enzymatic hydrolysis of complex plant polysaccharides is a subject of intense global interest. Microbial communities are known to express a wide range of enzymes necessary for the saccharification of lignocellulosic feedstocks and serve as a powerful reservoir for enzyme discovery. However, the growth temperature and conditions that yield high cellulase activity vary widely, and the throughput to identify optimal conditions has been limited by the slow handling and conventional analysis. A rapid method that uses small volumes of isolate culture to resolve specific enzyme activity is needed. In this work, a high throughput nanostructure-initiator mass spectrometry (NIMS)-based approach was developed for screening a thermophilic cellulolytic actinomycete, Thermobispora bispora, for β-glucosidase production under various growth conditions. Media that produced high β-glucosidase activity were found to be I/S + glucose or microcrystalline cellulose (MCC), Medium 84 + rolled oats, and M9TE + MCC at 45°C. Supernatants of cell cultures grown in M9TE + 1% MCC cleaved 2.5 times more substrate at 45°C than at all other temperatures. While T. bispora is reported to grow optimally at 60°C in Medium 84 + rolled oats and M9TE + 1% MCC, approximately 40% more conversion was observed at 45°C. This high throughput NIMS approach may provide an important tool in discovery and characterization of enzymes from environmental microbes for industrial and biofuel applications.

High throughput nanostructure-initiator mass spectrometry screening of microbial growth conditions for maximal β-glucosidase production

Directory of Open Access Journals (Sweden)

Xiaoliang eCheng

2013-12-01

Full Text Available Production of biofuels via enzymatic hydrolysis of complex plant polysaccharides is a subject of intense global interest. Microbial communities are known to express a wide range of enzymes necessary for the saccharification of lignocellulosic feedstocks and serve as a powerful reservoir for enzyme discovery. However, the growth temperature and conditions that yield high cellulase activity vary widely, and the throughput to identify optimal conditions has been limited by the slow handling and conventional analysis. A rapid method that uses small volumes of isolate culture to resolve specific enzyme activity is needed. In this work, a high throughput nanostructure-initiator mass spectrometry (NIMS based approach was developed for screening a thermophilic cellulolytic actinomycete, Thermobispora bispora, for β-glucosidase production under various growth conditions. Media that produced high β-glucosidase activity were found to be I/S + glucose or microcrystalline cellulose (MCC, Medium 84 + rolled oats, and M9TE + MCC at 45 °C. Supernatants of cell cultures grown in M9TE + 1% MCC cleaved 2.5 times more substrate at 45 °C than at all other temperatures. While T. bispora is reported to grow optimally at 60 °C in Medium 84 + rolled oats and M9TE + 1% MCC, approximately 40% more conversion was observed at 45 °C. This high throughput NIMS approach may provide an important tool in discovery and characterization of enzymes from environmental microbes for industrial and biofuel applications.

Detecting nonlinear structure in time series

International Nuclear Information System (INIS)

Theiler, J.

1991-01-01

We describe an approach for evaluating the statistical significance of evidence for nonlinearity in a time series. The formal application of our method requires the careful statement of a null hypothesis which characterizes a candidate linear process, the generation of an ensemble of ''surrogate'' data sets which are similar to the original time series but consistent with the null hypothesis, and the computation of a discriminating statistic for the original and for each of the surrogate data sets. The idea is to test the original time series against the null hypothesis by checking whether the discriminating statistic computed for the original time series differs significantly from the statistics computed for each of the surrogate sets. While some data sets very cleanly exhibit low-dimensional chaos, there are many cases where the evidence is sketchy and difficult to evaluate. We hope to provide a framework within which such claims of nonlinearity can be evaluated. 5 refs., 4 figs

Virtual high screening throughput and design of 14α-lanosterol ...

African Journals Online (AJOL)

STORAGESEVER

2009-07-06

Jul 6, 2009 ... Virtual high screening throughput and design of. 14α-lanosterol demethylase inhibitors against. Mycobacterium tuberculosis. Hildebert B. Maurice1*, Esther Tuarira1 and Kennedy Mwambete2. 1School of Pharmaceutical Sciences, Institute of Allied Health Sciences, Muhimbili University of Health and.

Introduction to time series and forecasting

CERN Document Server

Brockwell, Peter J

2016-01-01

This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space mod...

PUFKEY: A High-Security and High-Throughput Hardware True Random Number Generator for Sensor Networks

Directory of Open Access Journals (Sweden)

Dongfang Li

2015-10-01

Full Text Available Random number generators (RNG play an important role in many sensor network systems and applications, such as those requiring secure and robust communications. In this paper, we develop a high-security and high-throughput hardware true random number generator, called PUFKEY, which consists of two kinds of physical unclonable function (PUF elements. Combined with a conditioning algorithm, true random seeds are extracted from the noise on the start-up pattern of SRAM memories. These true random seeds contain full entropy. Then, the true random seeds are used as the input for a non-deterministic hardware RNG to generate a stream of true random bits with a throughput as high as 803 Mbps. The experimental results show that the bitstream generated by the proposed PUFKEY can pass all standard national institute of standards and technology (NIST randomness tests and is resilient to a wide range of security attacks.

PUFKEY: a high-security and high-throughput hardware true random number generator for sensor networks.

Science.gov (United States)

Li, Dongfang; Lu, Zhaojun; Zou, Xuecheng; Liu, Zhenglin

2015-10-16

Random number generators (RNG) play an important role in many sensor network systems and applications, such as those requiring secure and robust communications. In this paper, we develop a high-security and high-throughput hardware true random number generator, called PUFKEY, which consists of two kinds of physical unclonable function (PUF) elements. Combined with a conditioning algorithm, true random seeds are extracted from the noise on the start-up pattern of SRAM memories. These true random seeds contain full entropy. Then, the true random seeds are used as the input for a non-deterministic hardware RNG to generate a stream of true random bits with a throughput as high as 803 Mbps. The experimental results show that the bitstream generated by the proposed PUFKEY can pass all standard national institute of standards and technology (NIST) randomness tests and is resilient to a wide range of security attacks.

High-throughput fractionation of human plasma for fast enrichment of low- and high-abundance proteins.

Science.gov (United States)

Breen, Lucas; Cao, Lulu; Eom, Kirsten; Srajer Gajdosik, Martina; Camara, Lila; Giacometti, Jasminka; Dupuy, Damian E; Josic, Djuro

2012-05-01

Fast, cost-effective and reproducible isolation of IgM from plasma is invaluable to the study of IgM and subsequent understanding of the human immune system. Additionally, vast amounts of information regarding human physiology and disease can be derived from analysis of the low abundance proteome of the plasma. In this study, methods were optimized for both the high-throughput isolation of IgM from human plasma, and the high-throughput isolation and fractionation of low abundance plasma proteins. To optimize the chromatographic isolation of IgM from human plasma, many variables were examined including chromatography resin, mobile phases, and order of chromatographic separations. Purification of IgM was achieved most successfully through isolation of immunoglobulin from human plasma using Protein A chromatography with a specific resin followed by subsequent fractionation using QA strong anion exchange chromatography. Through these optimization experiments, an additional method was established to prepare plasma for analysis of low abundance proteins. This method involved chromatographic depletion of high-abundance plasma proteins and reduction of plasma proteome complexity through further chromatographic fractionation. Purification of IgM was achieved with high purity as confirmed by SDS-PAGE and IgM-specific immunoblot. Isolation and fractionation of low abundance protein was also performed successfully, as confirmed by SDS-PAGE and mass spectrometry analysis followed by label-free quantitative spectral analysis. The level of purity of the isolated IgM allows for further IgM-specific analysis of plasma samples. The developed fractionation scheme can be used for high throughput screening of human plasma in order to identify low and high abundance proteins as potential prognostic and diagnostic disease biomarkers.

Object-Based Classification of Grasslands from High Resolution Satellite Image Time Series Using Gaussian Mean Map Kernels

Directory of Open Access Journals (Sweden)

Mailys Lopes

2017-07-01

Full Text Available This paper deals with the classification of grasslands using high resolution satellite image time series. Grasslands considered in this work are semi-natural elements in fragmented landscapes, i.e., they are heterogeneous and small elements. The first contribution of this study is to account for grassland heterogeneity while working at the object level by modeling its pixels distributions by a Gaussian distribution. To measure the similarity between two grasslands, a new kernel is proposed as a second contribution: the α -Gaussian mean kernel. It allows one to weight the influence of the covariance matrix when comparing two Gaussian distributions. This kernel is introduced in support vector machines for the supervised classification of grasslands from southwest France. A dense intra-annual multispectral time series of the Formosat-2 satellite is used for the classification of grasslands’ management practices, while an inter-annual NDVI time series of Formosat-2 is used for old and young grasslands’ discrimination. Results are compared to other existing pixel- and object-based approaches in terms of classification accuracy and processing time. The proposed method is shown to be a good compromise between processing speed and classification accuracy. It can adapt to the classification constraints, and it encompasses several similarity measures known in the literature. It is appropriate for the classification of small and heterogeneous objects such as grasslands.

High Throughput Measurement of Locomotor Sensitization to Volatilized Cocaine in Drosophila melanogaster.

Science.gov (United States)

Filošević, Ana; Al-Samarai, Sabina; Andretić Waldowski, Rozi

2018-01-01

Drosophila melanogaster can be used to identify genes with novel functional roles in neuronal plasticity induced by repeated consumption of addictive drugs. Behavioral sensitization is a relatively simple behavioral output of plastic changes that occur in the brain after repeated exposures to drugs of abuse. The development of screening procedures for genes that control behavioral sensitization has stalled due to a lack of high-throughput behavioral tests that can be used in genetically tractable organism, such as Drosophila . We have developed a new behavioral test, FlyBong, which combines delivery of volatilized cocaine (vCOC) to individually housed flies with objective quantification of their locomotor activity. There are two main advantages of FlyBong: it is high-throughput and it allows for comparisons of locomotor activity of individual flies before and after single or multiple exposures. At the population level, exposure to vCOC leads to transient and concentration-dependent increase in locomotor activity, representing sensitivity to an acute dose. A second exposure leads to further increase in locomotion, representing locomotor sensitization. We validate FlyBong by showing that locomotor sensitization at either the population or individual level is absent in the mutants for circadian genes period (per) , Clock (Clk) , and cycle (cyc) . The locomotor sensitization that is present in timeless (tim) and pigment dispersing factor (pdf) mutant flies is in large part not cocaine specific, but derived from increased sensitivity to warm air. Circadian genes are not only integral part of the neural mechanism that is required for development of locomotor sensitization, but in addition, they modulate the intensity of locomotor sensitization as a function of the time of day. Motor-activating effects of cocaine are sexually dimorphic and require a functional dopaminergic transporter. FlyBong is a new and improved method for inducing and measuring locomotor sensitization

High Throughput Measurement of Locomotor Sensitization to Volatilized Cocaine in Drosophila melanogaster

Directory of Open Access Journals (Sweden)

Ana Filošević

2018-02-01

Full Text Available Drosophila melanogaster can be used to identify genes with novel functional roles in neuronal plasticity induced by repeated consumption of addictive drugs. Behavioral sensitization is a relatively simple behavioral output of plastic changes that occur in the brain after repeated exposures to drugs of abuse. The development of screening procedures for genes that control behavioral sensitization has stalled due to a lack of high-throughput behavioral tests that can be used in genetically tractable organism, such as Drosophila. We have developed a new behavioral test, FlyBong, which combines delivery of volatilized cocaine (vCOC to individually housed flies with objective quantification of their locomotor activity. There are two main advantages of FlyBong: it is high-throughput and it allows for comparisons of locomotor activity of individual flies before and after single or multiple exposures. At the population level, exposure to vCOC leads to transient and concentration-dependent increase in locomotor activity, representing sensitivity to an acute dose. A second exposure leads to further increase in locomotion, representing locomotor sensitization. We validate FlyBong by showing that locomotor sensitization at either the population or individual level is absent in the mutants for circadian genes period (per, Clock (Clk, and cycle (cyc. The locomotor sensitization that is present in timeless (tim and pigment dispersing factor (pdf mutant flies is in large part not cocaine specific, but derived from increased sensitivity to warm air. Circadian genes are not only integral part of the neural mechanism that is required for development of locomotor sensitization, but in addition, they modulate the intensity of locomotor sensitization as a function of the time of day. Motor-activating effects of cocaine are sexually dimorphic and require a functional dopaminergic transporter. FlyBong is a new and improved method for inducing and measuring locomotor

High-Throughput DNA sequencing of ancient wood.

Science.gov (United States)

Wagner, Stefanie; Lagane, Frédéric; Seguin-Orlando, Andaine; Schubert, Mikkel; Leroy, Thibault; Guichoux, Erwan; Chancerel, Emilie; Bech-Hebelstrup, Inger; Bernard, Vincent; Billard, Cyrille; Billaud, Yves; Bolliger, Matthias; Croutsch, Christophe; Čufar, Katarina; Eynaud, Frédérique; Heussner, Karl Uwe; Köninger, Joachim; Langenegger, Fabien; Leroy, Frédéric; Lima, Christine; Martinelli, Nicoletta; Momber, Garry; Billamboz, André; Nelle, Oliver; Palomo, Antoni; Piqué, Raquel; Ramstein, Marianne; Schweichel, Roswitha; Stäuble, Harald; Tegel, Willy; Terradas, Xavier; Verdin, Florence; Plomion, Christophe; Kremer, Antoine; Orlando, Ludovic

2018-03-01

Reconstructing the colonization and demographic dynamics that gave rise to extant forests is essential to forecasts of forest responses to environmental changes. Classical approaches to map how population of trees changed through space and time largely rely on pollen distribution patterns, with only a limited number of studies exploiting DNA molecules preserved in wooden tree archaeological and subfossil remains. Here, we advance such analyses by applying high-throughput (HTS) DNA sequencing to wood archaeological and subfossil material for the first time, using a comprehensive sample of 167 European white oak waterlogged remains spanning a large temporal (from 550 to 9,800 years) and geographical range across Europe. The successful characterization of the endogenous DNA and exogenous microbial DNA of 140 (~83%) samples helped the identification of environmental conditions favouring long-term DNA preservation in wood remains, and started to unveil the first trends in the DNA decay process in wood material. Additionally, the maternally inherited chloroplast haplotypes of 21 samples from three periods of forest human-induced use (Neolithic, Bronze Age and Middle Ages) were found to be consistent with those of modern populations growing in the same geographic areas. Our work paves the way for further studies aiming at using ancient DNA preserved in wood to reconstruct the micro-evolutionary response of trees to climate change and human forest management. © 2018 John Wiley & Sons Ltd.

A simpler sampling interface of venturi easy ambient sonic-spray ionization mass spectrometry for high-throughput screening enzyme inhibitors.

Science.gov (United States)

Liu, Ning; Liu, Yang; Yang, YuHan; He, Lan; Ouyang, Jin

2016-03-24

High-throughput screening (HTS) is often required in enzyme inhibitor drugs screening. Mass spectrometry (MS) provides a powerful method for high-throughput screening enzyme inhibitors because its high speed, sensitivity and property of lable free. However, most of the MS methods need complicated sampling interface system. Overall throughput was limited by sample loading in these cases. In this study, we develop a simple interface which coupled droplet segmented system to a venturi easy ambient sonic-spray ionization mass spectrometer. It is fabricated by using a single capillary to act as both sampling probe and the emitter, which simplifies the construction, reduces the cost and shorten the sampling time. Samples sucked by venturi effect are segmented to nanoliter plugs by air, then the plugs can be detected by MS directly. This system eliminated the need for flow injection which was popular used in classic scheme. The new system is applied to screen angiotensin converting enzyme inhibitors. High-throughput was achieved in analyzing 96 samples at 1.6 s per sample. The plugs formation was at 0.5s per sample. Carry-over between samples was less than 5%, the peak height RSD was 2.92% (n = 15). Dose-response curves of 3 known inhibitors were also measured to validate its potential in drug discovery. The calculated IC50 agreed well with reported values. Copyright © 2016 Elsevier B.V. All rights reserved.

TIME SERIES ANALYSIS USING A UNIQUE MODEL OF TRANSFORMATION

Directory of Open Access Journals (Sweden)

Goran Klepac

2007-12-01

Full Text Available REFII1 model is an authorial mathematical model for time series data mining. The main purpose of that model is to automate time series analysis, through a unique transformation model of time series. An advantage of this approach of time series analysis is the linkage of different methods for time series analysis, linking traditional data mining tools in time series, and constructing new algorithms for analyzing time series. It is worth mentioning that REFII model is not a closed system, which means that we have a finite set of methods. At first, this is a model for transformation of values of time series, which prepares data used by different sets of methods based on the same model of transformation in a domain of problem space. REFII model gives a new approach in time series analysis based on a unique model of transformation, which is a base for all kind of time series analysis. The advantage of REFII model is its possible application in many different areas such as finance, medicine, voice recognition, face recognition and text mining.

High-throughput verification of transcriptional starting sites by Deep-RACE

DEFF Research Database (Denmark)

Olivarius, Signe; Plessy, Charles; Carninci, Piero

2009-01-01

We present a high-throughput method for investigating the transcriptional starting sites of genes of interest, which we named Deep-RACE (Deep–rapid amplification of cDNA ends). Taking advantage of the latest sequencing technology, it allows the parallel analysis of multiple genes and is free...

Frontiers in Time Series and Financial Econometrics

OpenAIRE

Ling, S.; McAleer, M.J.; Tong, H.

2015-01-01

__Abstract__ Two of the fastest growing frontiers in econometrics and quantitative finance are time series and financial econometrics. Significant theoretical contributions to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time series analysis. The purpose of this special issue of the journal on “Frontiers in Time Series and Financial Econometrics” is to highlight several areas of research by leading academics in which novel methods have contrib...

High Throughput, Multiplexed Pathogen Detection Authenticates Plague Waves in Medieval Venice, Italy

Science.gov (United States)

Tran, Thi-Nguyen-Ny; Signoli, Michel; Fozzati, Luigi; Aboudharam, Gérard; Raoult, Didier; Drancourt, Michel

2011-01-01

Background Historical records suggest that multiple burial sites from the 14th–16th centuries in Venice, Italy, were used during the Black Death and subsequent plague epidemics. Methodology/Principal Findings High throughput, multiplexed real-time PCR detected DNA of seven highly transmissible pathogens in 173 dental pulp specimens collected from 46 graves. Bartonella quintana DNA was identified in five (2.9%) samples, including three from the 16th century and two from the 15th century, and Yersinia pestis DNA was detected in three (1.7%) samples, including two from the 14th century and one from the 16th century. Partial glpD gene sequencing indicated that the detected Y. pestis was the Orientalis biotype. Conclusions These data document for the first time successive plague epidemics in the medieval European city where quarantine was first instituted in the 14th century. PMID:21423736

Crystal Symmetry Algorithms in a High-Throughput Framework for Materials

Science.gov (United States)

Taylor, Richard

The high-throughput framework AFLOW that has been developed and used successfully over the last decade is improved to include fully-integrated software for crystallographic symmetry characterization. The standards used in the symmetry algorithms conform with the conventions and prescriptions given in the International Tables of Crystallography (ITC). A standard cell choice with standard origin is selected, and the space group, point group, Bravais lattice, crystal system, lattice system, and representative symmetry operations are determined. Following the conventions of the ITC, the Wyckoff sites are also determined and their labels and site symmetry are provided. The symmetry code makes no assumptions on the input cell orientation, origin, or reduction and has been integrated in the AFLOW high-throughput framework for materials discovery by adding to the existing code base and making use of existing classes and functions. The software is written in object-oriented C++ for flexibility and reuse. A performance analysis and examination of the algorithms scaling with cell size and symmetry is also reported.

Development of Control Applications for High-Throughput Protein Crystallography Experiments

International Nuclear Information System (INIS)

Gaponov, Yurii A.; Matsugaki, Naohiro; Honda, Nobuo; Sasajima, Kumiko; Igarashi, Noriyuki; Hiraki, Masahiko; Yamada, Yusuke; Wakatsuki, Soichi

2007-01-01

An integrated client-server control system (PCCS) with a unified relational database (PCDB) has been developed for high-throughput protein crystallography experiments on synchrotron beamlines. The major steps in protein crystallographic experiments (purification, crystallization, crystal harvesting, data collection, and data processing) are integrated into the software. All information necessary for performing protein crystallography experiments is stored in the PCDB database (except raw X-ray diffraction data, which is stored in the Network File Server). To allow all members of a protein crystallography group to participate in experiments, the system was developed as a multi-user system with secure network access based on TCP/IP secure UNIX sockets. Secure remote access to the system is possible from any operating system with X-terminal and SSH/X11 (Secure Shell with graphical user interface) support. Currently, the system covers the high-throughput X-ray data collection stages and is being commissioned at BL5A and NW12A (PF, PF-AR, KEK, Tsukuba, Japan)

Scale-dependent intrinsic entropies of complex time series.

Science.gov (United States)

Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E

2016-04-13

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).

Elements of nonlinear time series analysis and forecasting

CERN Document Server

De Gooijer, Jan G

2017-01-01

This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible...