CGHnormaliter: an iterative strategy to enhance normalization of array CGH data with imbalanced aberrations

Background: Array comparative genomic hybridization (aCGH) is a popular technique for detection of genomic copy number imbalances. These play a critical role in the onset of various types of cancer. In the analysis of aCGH data, normalization is deemed a critical pre-processing step. In general, aCGH normalization approaches are similar to those used for gene expression data, albeit both data-types differ inherently. A particular problem with aCGH data is that imbalanced copy numbers lead to improper normalization using conventional methods. Results: In this study we present a novel method, called CGHnormaliter, which addresses this issue by means of an iterative normalization procedure. First, provisory balanced copy numbers are identified and subsequently used for normalization. These two steps are then iterated to refine the normalization. We tested our method on three well-studied tumor-related aCGH datasets with experimentally confirmed copy numbers. Results were compared to a conventional normalization approach and two more recent state-of-the-art aCGH normalization strategies. Our findings show that, compared to these three methods, CGHnormaliter yields a higher specificity and precision in terms of identifying the 'true' copy numbers. Conclusion: We demonstrate that the normalization of aCGH data can be significantly enhanced using an iterative procedure that effectively eliminates the effect of imbalanced copy numbers. This also leads to a more reliable assessment of aberrations. An R-package containing the implementation of CGHnormaliter is available at http://www.ibi.vu.nl/programs/cghnormaliterwww. © 2009 van Houte et al; licensee BioMed Central Ltd

The Netherlands Biodiversity Data Services and the R package nbaR: Automated workflows for biodiversity data analysis

The value of data present in natural history collections for research in biodiversity, ecology and evolution cannot be overstated. Naturalis Biodiversity Center of the Netherlands, home to one of the largest natural history collections in the world, launched a large-scale digitisation project resulting in the registration of more than 38 million specimen objects, many of them annotated with descriptive metadata, such as geographic coordinates or multimedia content. Other resources hosted at Naturalis include species occurrence records and comprehensive taxonomic checklists, such as the Catalogue of Life. As our institution strongly believes in the Open Science paradigm, we seek to make our data available to the global biodiversity research community, enhancing data analysis workflows, as for example (i) the modelling of present, past and future species distributions using specimen occurrence data, (ii) time calibration of (molecular) phylogenies using dated specimen occurrences, (iii) taxonomic name resolution or (iv) image data mining. To this end, we developed the Netherlands Biodiversity Data services [1], providing centralized access to biodiversity data via state of the art, open access interfaces and a mechanism to assign persistent identifiers to all records. Data are retrieved from heterogeneous sources and harmonized into a document store that complies with international data standards such as ABCD (Access to Biological Collection Data [2]). Employing the Elasticsearch engine, our infrastructure features complex query options, near real-time queries, and scaling possibilities to secure foreseen data growth. Focusing on availability and accessibility, the services were designed as a versatile, low-level REST API to allow the use of our data in a broad variety of applications and services. For programmatic access to our data services, we developed client libraries for several programming languages. Here we present the R package ‘nbaR’ [3], a client especially targeted to an audience of biodiversity researchers. The R programming language has found wide acceptance in this field over the past years and our package facilitates convenient means to connect our data resources to existing tools for statistical modelling and analysis. The abstraction layer introduced by the client lets the user formulate even complex queries in a convenient manner, thereby lowering the access threshold to our data services. We will demonstrate the potential and benefits of services and R client by integrating nbaR with state-of-the art packages for species distribution modelling and time calibration of phylogenetic trees into a single analysis workflow. 1. Netherlands Biodiversity Data services – User documentation. http://docs.biodiversitydata.nl (accessed 17 May 2018). 2. Access to Biological Collections Data task group. 2007. Access to Biological Collection Data (ABCD), Version 2.06. Biodiversity Information Standards (TDWG) http://www.tdwg.org/standards/115 (accessed 17 May 2018). 3. nbaR GitHub repository. https://github.com/naturalis/ nbaR (accessed 17 May 2018)

Радіолокаційно-вихрострумовий метод виявлення металів

Сучасний георадар – це складний геофізичний прилад для неруйнівного контролю неоднорідностей середовища. В основі роботи георадару лежить підповерхневе зондуванняявище відбивання електромагнітної хвилі від межі поділу шарів з різною діелектричною чи магнітною проникністю. Такими межами є локальні неоднорідності різної природи. Георадари з великою вірогідністю визначають цю неоднорідність та глибину її залягання, але не можуть визначити склад неоднорідності, наприклад, це сталь чи золото. Тому виникла необхідність у створенні георадару без цього недоліку

Simulating the physiology of athletes during endurance sports events: modelling human energy conversion and metabolism

The human physiological system is stressed to its limits during endurance sports competition events. We describe a whole body computational model for energy conversion during bicycle racing. About 23 per cent of the metabolic energy is used for muscle work, the rest is converted to heat. We calculated heat transfer by conduction and blood flow inside the body, and heat transfer from the skin by radiation, convection and sweat evaporation, resulting in temperature changes in 25 body compartments. We simulated a mountain time trial to Alpe d'Huez during the Tour de France. To approach the time realized by Lance Armstrong in 2004, very high oxygen uptake must be sustained by the simulated cyclist. Temperature was predicted to reach 39°C in the brain, and 39.7°C in leg muscle. In addition to the macroscopic simulation, we analysed the buffering of bursts of high adenosine triphosphate hydrolysis by creatine kinase during cyclical muscle activity at the biochemical pathway level. To investigate the low oxygen to carbohydrate ratio for the brain, which takes up lactate during exercise, we calculated the flux distribution in cerebral energy metabolism. Computational modelling of the human body, describing heat exchange and energy metabolism, makes simulation of endurance sports events feasible

Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies

Background: The aerobic energy metabolism of cardiac muscle cells is of major importance for the contractile function of the heart. Because energy metabolism is very heterogeneously distributed in heart tissue, especially during coronary disease, a method to quantify metabolic fluxes in small tissue samples is desirable. Taking tissue biopsies after infusion of substrates labeled with stable carbon isotopes makes this possible in animal experiments. However, the appreciable noise level in NMR spectra of extracted tissue samples makes computational estimation of metabolic fluxes challenging and a good method to define confidence regions was not yet available.Results: Here we present a computational analysis method for nuclear magnetic resonance (NMR) measurements of tricarboxylic acid (TCA) cycle metabolites. The method was validated using measurements on extracts of single tissue biopsies taken from porcine heart in vivo. Isotopic enrichment of glutamate was measured by NMR spectroscopy in tissue samples taken at a single time point after the timed infusion of 13C labeled substrates for the TCA cycle. The NMR intensities for glutamate were analyzed with a computational model describing carbon transitions in the TCA cycle and carbon exchange with amino acids. The model dynamics depended on five flux parameters, which were optimized to fit the NMR measurements. To determine confidence regions for the estimated fluxes, we used the Metropolis-Hastings algorithm for Markov chain Monte Carlo (MCMC) sampling to generate extensive ensembles of feasible flux combinations that describe the data within meas

Enriched biodiversity data as a resource and service

Background: Recent years have seen a surge in projects that produce large volumes of structured, machine-readable biodiversity data. To make these data amenable to processing by generic, open source “data enrichment” workflows, they are increasingly being represented in a variety of standards-compliant interchange formats. Here, we report on an initiative in which software developers and taxonomists came together to address the challenges and highlight the opportunities in the enrichment of such biodiversity data by engaging in intensive, collaborative software development: The Biodiversity Data Enrichment Hackathon. Results: The hackathon brought together 37 participants (including developers and taxonomists, i.e. scientific professionals that gather, identify, name and classify species) from 10 countries: Belgium, Bulgaria, Canada, Finland, Germany, Italy, the Netherlands, New Zealand, the UK, and the US. The participants brought expertise in processing structured data, text mining, development of ontologies, digital identification keys, geographic information systems, niche modeling, natural language processing, provenance annotation, semantic integration, taxonomic name resolution, web service interfaces, workflow tools and visualisation. Most use cases and exemplar data were provided by taxonomists. One goal of the meeting was to facilitate re-use and enhancement of biodiversity knowledge by a broad range of stakeholders, such as taxonomists, systematists, ecologists, niche modelers, informaticians and ontologists. The suggested use cases resulted in nine breakout groups addressing three main themes: i) mobilising heritage biodiversity knowledge; ii) formalising and linking concepts; and iii) addressing interoperability between service platforms. Another goal was to further foster a community of experts in biodiversity informatics and to build human links between research projects and institutions, in response to recent calls to further such integration in this research domain. Conclusions: Beyond deriving prototype solutions for each use case, areas of inadequacy were discussed and are being pursued further. It was striking how many possible applications for biodiversity data there were and how quickly solutions could be put together when the normal constraints to collaboration were broken down for a week. Conversely, mobilising biodiversity knowledge from their silos in heritage literature and natural history collections will continue to require formalisation of the concepts (and the links between them) that define the research domain, as well as increased interoperability between the software platforms that operate on these concepts

The Elbow-EpiTrainer : A method of delivering graded resistance to the extensor carpi radialis brevis. Effectiveness of a prototype device in a healthy population

This document is the Accepted Manuscript version of the following article: Navsaria R, Ryder DM, Lewis JS, et al, 'The Elbow-EpiTrainer: a method of delivering graded resistance to the extensor carpi radialis brevi:. Effectiveness of a prototype device in a healthy population', British Journal of Sports Medicine, Vol. 49(5):318-322, March 2015, available online at: http://bjsm.bmj.com/content/49/5/318. Published by the BMJ Publishing Group Limited.Background: Tennis elbow or lateral epicondylopathy (LE) is experienced as the lateral elbow has a reported prevalence of 1.3%, with symptoms lasting up to 18 months. LE is most commonly attributed to tendinopathy involving the extensor carpi radialis brevis (ECRB) tendon. The aim of tendinopathy management is to alleviate symptoms and restore function that initially involves relative rest followed by progressive therapeutic exercise. Objective: To assess the effectiveness of two prototype exercises using commonly available clinical equipment to progressively increase resistance and activity of the ECRB. Method: Eighteen healthy participants undertook two exercise progressions. Surface electromyography was used to record ECRB activity during the two progressions, involving eccentric exercises of the wrist extensors and elbow pronation exercises using a prototype device. The two progressions were assessed for their linearity of progression using repeated ANOVA and linear regression analysis. Five participants repeated the study to assess reliability. Results: The exercise progressions led to an increase in ECRB electromyographic (EMG) activity (p0.7) between the first and second tests for five participants. Conclusions: Manipulation of resistance and leverage with the prototype exercises was effective in creating significant increases of ECRB normalised EMG activity in a linear manner that may, with future research, become useful to clinicians treating LE. In addition, between trial reliability for the device to generate a consistent load was acceptable.Peer reviewe

BioVeL : a virtual laboratory for data analysis and modelling in biodiversity science and ecology

Background: Making forecasts about biodiversity and giving support to policy relies increasingly on large collections of data held electronically, and on substantial computational capability and capacity to analyse, model, simulate and predict using such data. However, the physically distributed nature of data resources and of expertise in advanced analytical tools creates many challenges for the modern scientist. Across the wider biological sciences, presenting such capabilities on the Internet (as "Web services") and using scientific workflow systems to compose them for particular tasks is a practical way to carry out robust "in silico" science. However, use of this approach in biodiversity science and ecology has thus far been quite limited. Results: BioVeL is a virtual laboratory for data analysis and modelling in biodiversity science and ecology, freely accessible via the Internet. BioVeL includes functions for accessing and analysing data through curated Web services; for performing complex in silico analysis through exposure of R programs, workflows, and batch processing functions; for on- line collaboration through sharing of workflows and workflow runs; for experiment documentation through reproducibility and repeatability; and for computational support via seamless connections to supporting computing infrastructures. We developed and improved more than 60 Web services with significant potential in many different kinds of data analysis and modelling tasks. We composed reusable workflows using these Web services, also incorporating R programs. Deploying these tools into an easy-to-use and accessible 'virtual laboratory', free via the Internet, we applied the workflows in several diverse case studies. We opened the virtual laboratory for public use and through a programme of external engagement we actively encouraged scientists and third party application and tool developers to try out the services and contribute to the activity. Conclusions: Our work shows we can deliver an operational, scalable and flexible Internet-based virtual laboratory to meet new demands for data processing and analysis in biodiversity science and ecology. In particular, we have successfully integrated existing and popular tools and practices from different scientific disciplines to be used in biodiversity and ecological research.Peer reviewe