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Whilst the array of techniques available for quantitative proteomics continues to grow, the attendant bioinformatic software tools are similarly expanding in number. The data capture and analysis of such quantitative data is obviously crucial to the experiment and the methods used to process it will critically affect the quality of the data obtained. These tools must deal with a variety of issues, including identification of labelled and unlabelled peptide species, location of the corresponding mass spectrometry scans in the experiment, construction of representative ion chromatograms, location of the true peptide ion chromatogram start and end, elimination of background signal in the mass spectrum and chromatogram, and calculation of both peptide and protein ratios/abundances. A variety of tools and approaches are available, in part restricted by the nature of the experiment to be performed and available instrumentation. Currently, although there is no single consensus on precisely how to calculate protein and peptide abundances, many common themes have emerged which identify and reduce many of the key sources of error. These issues will be discussed, along with those relating to deposition of quantitative data. At present, mature data standards for quantitative proteomics are not yet available, although formats are beginning to emerge.

With the recent advent of RNA-seq technology the proteomics community has begun to generate sample-specific protein databases for peptide and protein identification, an approach we call proteomics informed by transcriptomics (PIT). This approach has gained a lot of interest, particularly among researchers who work with nonmodel organisms or with particularly dynamic proteomes such as those observed in developmental biology and host-pathogen studies. PIT has been shown to improve coverage of known proteins, and to reveal potential novel gene products. However, many groups are impeded in their use of PIT by the complexity of the required data analysis. Necessarily, this analysis requires complex integration of a number of different software tools from at least two different communities, and because PIT has a range of biological applications a single software pipeline is not suitable for all use cases. To overcome these problems, we have created GIO, a software system that uses the well-established Galaxy platform to make PIT analysis available to the typical bench scientist via a simple web interface. Within GIO we provide workflows for four common use cases: a standard search against a reference proteome; PIT protein identification without a reference genome; PIT protein identification using a genome guide; and PIT genome annotation. These workflows comprise individual tools that can be reconfigured and rearranged within the web interface to create new workflows to support additional use cases.

International audience; We present a long-term assessment of the radiometric calibration and degradation of the Large Yield Radiometer (LYRA), which has been on orbit since 2009. LYRA is an ultraviolet (UV) solar radiometer and is the first space experiment using aboard a pioneering diamond detector technology. We show that LYRA has degraded after the commissioning phase but is still exploitable scientifically after almost 5 years on orbit thanks to its redundancy design and calibration strategy correcting for instrument degradation. We focus on the inflight detector’s calibration and show that diamond photodetectors have not degraded while silicon reference photodiodes that are even less exposed to the Sun show an increase of their dark current and a decrease of their photoresponse.

The theme of the third annual Spring workshop of the HUPO-PSI was "proteomics and beyond" and its underlying goal was to reach beyond the boundaries of the proteomics community to interact with groups working on the similar issues of developing interchange standards and minimal reporting requirements. Significant developments in many of the HUPO-PSI XML interchange formats, minimal reporting requirements and accompanying controlled vocabularies were reported, with many of these now feeding into the broader efforts of the Functional Genomics Experiment (FuGE) data model and Functional Genomics Ontology (FuGO) ontologies.

This is an interim report on the Functional Genomics Experiment (FuGE) Object Model. FuGE is a framework for creating data standards for high-throughput biological experiments, developed by a consortium of researchers from academia and industry. FuGE supports rich annotation of samples, protocols, instruments, and software, as well as providing extension points for technology specific details. It has been adopted by microarray and proteomics standards bodies as a basis for forthcoming standards. It is hoped that standards developers for other omics techniques will join this collaborative effort; widespread adoption will allow uniform annotation of common parts of functional genomics workflows, reduce standard development and learning times through the sharing of consistent practice, and ease the construction of software for accessing and integrating functional genomics data. This paper is part of the special issue of OMICS on data standards.

Short-duration fluctuations in the concentration of airborne substances can be important in a variety of atmospheric dispersion problems, especially when assessing the risks posed by harmful materials. This paper discusses a simulation technique for generating individual realisations of fluctuating concentration time series in dispersing plumes based on target probability distributions and spectral functions. The scheme uses a correlation-distortion approach to simulate these time series. Gaussian processes with modified spectral characteristics are generated and then transformed to yield non-Gaussian processes with the desired spectral characteristics. The simulation scheme is initially developed for a single receptor, and is then extended to model pairs of correlated time series at two receptors. In fact, the modelling technique can be generalised to an arbitrary number of receptors and this provides, in principal, an approach that is applicable to a wide class of similar problems (such as the modelling of instantaneous puff releases or the response of line-of-sight detection systems). The simulation technique is illustrated using observations made during recent field experiments, conducted both in the United Kingdom and in the U.S.A., investigating the short-range dispersion of a passive tracer.

Volcanic eruptions take place in Iceland about once every 3 to 5 years. Ash emissions from these eruptions can cause significant disruption to air traffic over Europe and the North Atlantic as is evident from the 2010 eruption of Eyjafjallajokull. Sulfur dioxide (SO2) is also emitted by volcanoes, but there are no criteria to define when airspace is considered hazardous or nonhazardous. However, SO2 is a well-known ground-level pollutant that can have detrimental effects on human health. We have used the United Kingdom Met Office's NAME (Numerical Atmospheric-dispersion Modelling Environment) model to simulate SO2 mass concentrations that could occur in European and North Atlantic airspace for a range of hypothetical explosive eruptions in Iceland with a probability to occur about once every 3 to 5 years. Model performance was evaluated for the 2010 Eyjafjallajokull summit eruption against SO2 vertical column density retrievals from the Ozone Monitoring Instrument and in situ measurements from the United Kingdom Facility for Airborne Atmospheric Measurements research aircraft. We show that at no time during the 2010 Eyjafjallajokull eruption did SO2 mass concentrations at flight altitudes violate European air quality standards. In contrast, during a hypothetical short-duration explosive eruption similar to Hekla in 2000 (emitting 0.2 Tg of SO2 within 2 h, or an average SO2 release rate 250 times that of Eyjafjallajokull 2010), simulated SO2 concentrations are greater than 1063 µg/m3 for about 48 h in a small area of European and North Atlantic airspace. By calculating the occurrence of aircraft encounters with the volcanic plume of a short-duration eruption, we show that a 15 min or longer exposure of aircraft and passengers to concentrations ≥500 µg/m3 has a probability of about 0.1%. Although exposure of humans to such concentrations may lead to irritations to the eyes, nose and, throat and cause increased airway resistance even in healthy individuals, the risk is very low. However, the fact that volcanic ash and sulfur species are not always collocated and that passenger comfort could be compromised might be incentives to provide real-time information on the presence or absence of volcanic SO2. Such information could aid aviation risk management during and after volcanic eruptions.

Proteomics data can supplement genome annotation efforts, for example being used to confirm gene models or correct gene annotation errors. Here, we present a large-scale proteogenomics study of two important apicomplexan pathogens: Toxoplasma gondii and Neospora caninum. We queried proteomics data against a panel of official and alternate gene models generated directly from RNASeq data, using several newly generated and some previously published MS datasets for this meta-analysis. We identified a total of 201 996 and 39 953 peptide-spectrum matches for T. gondii and N. caninum, respectively, at a 1% peptide FDR threshold. This equated to the identification of 30 494 distinct peptide sequences and 2921 proteins (matches to official gene models) for T. gondii, and 8911 peptides/1273 proteins for N. caninum following stringent protein-level thresholding. We have also identified 289 and 140 loci for T. gondii and N. caninum, respectively, which mapped to RNA-Seq-derived gene models used in our analysis and apparently absent from the official annotation (release 10 from EuPathDB) of these species. We present several examples in our study where the RNA-Seq evidence can help in correction of the current gene model and can help in discovery of potential new genes. The findings of this study have been integrated into the EuPathDB. The data have been deposited to the ProteomeXchange with identifiers PXD000297and PXD000298.

Experiments have been performed to test the efficiency with which a novel fluidised bed technique could separate different metallic powders in terms of size and density. The overall aim was to assess the potential of this technique for the commercial separation of defective powder fractions from mechanically alloyed (MA), iron based powders. Separation in terms of size was readily achieved, with the largest powder particles sinking to the bottom of the fluidised bed. In a simulated commercial process, density separation of defective Fe3Al powder could not be demonstrated as any differences in density were overshadowed by size and morphology differences. However, from a batch of iron based powder (p=8.02 g cm(-3)), seeded with six other metallic powders, aluminium powder (p=2.70 g cm(-3)) segregated strongly to the top of the bed from where samples containing 93 vol.-%Al were taken. The process is thought to be sensitive to differences in density of a factor of 1.1-3.

Mechanically alloyed, Fe 3 Al-based, oxide dispersion strengthened alloys form a surface oxide scale during powder processing. This scale becomes entrained in the consolidated alloy, and may have a significant effect on subsequent recrystallisation behaviour. The high oxidation rates found in these alloys are mainly due to the bulk alloy composition. However, batch-to-batch differences in oxidation mass gain occur in powders with ostensibly identical compositions. Batches PMWY2 and PMWY3 were studied and parameters such as alloy composition and homogeneity, powder surface area to volume ratios and scale thickening rates considered. Batch PMWY2 showed 20-90% faster weight gain than PMWY3 and reached the onset of breakaway oxidation approximately twice as quickly. PMWY2 was found to contain aluminium-depleted regions, whereas PMWY3 is much more homogeneous. The surface area to volume ratio for PMWY2 was 44% higher than that of PMWY3, and batch PMWY2 was found to contain extremely fine powder particles. The scale on batch PMWY2 thickened more quickly than that on batch PMWY3, with rates 20-40% higher at different stages in the oxidation. The major contributory factor to the difference in oxidation mass gain between the two alloy batches is scale thickening rate and factors influencing thickening rates are discussed.

Motivation: Large-scale functional genomics analysis is now feasible and presents significant challenges in data analysis, storage and querying. Data standards are required to enable the development of public data repositories and to improve data sharing. There is an established data format for microarrays (microarray gene expression markup language, MAGE-ML) and a draft standard for proteomics (PEDRo). We believe that all types of functional genomics experiments should be annotated in a consistent manner, and we hope to open up new ways of comparing multiple datasets used in functional genomics. Results: We have created a functional genomics experiment object model (FGE-OM), developed from the microarray model, MAGE-OM and two models for proteomics, PEDRo and our own model (Gla-PSI—Glasgow Proposal for the Proteomics Standards Initiative). FGE-OM comprises three namespaces representing (i) the parts of the model common to all functional genomics experiments; (ii) microarray-specific components; and (iii) proteomics-specific components. We believe that FGE-OM should initiate discussion about the contents and structure of the next version of MAGE and the future of proteomics standards. A prototype database called RNA And Protein Abundance Database (RAPAD), based on FGE-OM, has been implemented and populated with data from microbial pathogenesis. Availability: FGE-OM and the RAPAD schema are available from http://www.gusdb.org/fge.html, along with a set of more detailed diagrams. RAPAD can be accessed by registration at the site.

Oxide dispersion strengthened (ODS) alloys prepared by mechanical alloying (MA) and subsequent consolidation are usually subjected to a series of heat treatments during production, typically comprising a degassing process at ≊600°C and a preconsolidation high temperature 'soak' at ≊1000°C, both under vacuum. In the current work, the oxidation behaviour of a prototype ODS Fe3Al alloy and a commercial FeCrAl alloy has been studied during simulation of these temperature and pressure regimes. After the high temperature 'soak' simulation, oxidation had taken place on both alloys with a significantly thicker scale forming on the ODS Fe3Al. This scale is believed to be the source of much of the high alumina content found in fully consolidated ODS Fe3Al. Variation in the amount of particulate alumina found in different batches of commercially consolidated powder is discussed. Novel processes involving hydrogen purging and powder precompaction have been employed to decrease oxidation and thereby increase s...

The global analysis of proteins is now feasible due to improvements in techniques such as two-dimensional gel electrophoresis (2-DE), mass spectrometry, yeast two-hybrid systems and the development of bioinformatics applications. The experiments form the basis of proteomics, and present significant challenges in data analysis, storage and querying. We argue that a standard format for proteome data is required to enable the storage, exchange and subsequent re-analysis of large datasets. We describe the criteria that must be met for the development of a standard for proteomics. We have developed a model to represent data from 2-DE experiments, including difference gel electrophoresis along with image analysis and statistical analysis across multiple gels. This part of proteomics analysis is not represented in current proposals for proteomics standards. We are working with the Proteomics Standards Initiative to develop a model encompassing biological sample origin, experimental protocols, a number of separation techniques and mass spectrometry. The standard format will facilitate the development of central repositories of data, enabling results to be verified or re-analysed, and the correlation of results produced by different research groups using a variety of laboratory techniques.

Urban development and planning are increasingly centered on matters of sustainability, balancing economic development with ecosystem services and biotic structures within urban environments. In addition to these institutional and structural factors, the decision-making process within individual households must be understood to address rising concerns about water use. Therefore, individual characteristics and preferences that influence the use of water also warrant examination. In response to a survey of occupants of single-family residences in the Fresno Clovis Metropolitan Area of California, contextual interviews and focus group interviews with a homeowner sub-sample, we find evidence of an interplay of social-structural, institutional, and cultural factors involved in influencing individual water use behaviors and landscape decision making. The complexity of residential behaviors and decision-making poses some potential issues with regards to the interactions between individual households and institutional actors in matters of water usage and landscaping, as survey respondents indicate relatively little confidence in institutions and groups to make wise water policy decisions. We conclude that the promotion and implementation of sustainable water use practices will require not only environmental education for the citizenry, but also a tailoring of information for environmental educational initiatives that address the particularities of individual neighborhoods and communities.

Aim The human leukocyte antigen (HLA) class I molecules are the ligands for several killer-cell immunoglobulin-like receptors (KIR) genes. Interactions between KIR and their appropriate ligands on target cells result in the production of positive or negative signals, which regulate natural killer (NK) cell function. In this study, we present the development of a new section in the Allele Frequency Net Database (AFND, www.allelefrequencies.net ), called KIR/HLA-DB, for the storage of KIR and HLA ligands across worldwide populations. Methods A total of 50 worldwide populations with data for KIR and HLA ligands was collected comprising more than 7,121 individuals, which were also stored in AFND. Data have been collected for 15 KIR genes and HLA epitope/allele level. Results We created a new section in AFND called KIR/HLA-DB, which allows users to search for KIR and HLA ligand data. Users are able to filter results using their own criteria. We also provide shortcuts and statistics for most commonly known ligands (e.g. HLA-C1: KIR2DL2/KIR2DL3; HLA-C2: KIR2DL1; HLA-B: Bw4/Bw6; HLA-A: KIR3DL2; HLA-G: KIR2DL4), among others. Conclusions The diversity of KIR and HLA has led to a search for their role in human diseases. We expect KIR-HLA DB to be a useful repository for the histocompatibility and immunogenetics research community to better understand the role of these ligands.

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online.

The recent massive increase in capability for sequencing genomes is producing enormous advances in our understanding of biological systems. However, there is a bottleneck in genome annotation--determining the structure of all transcribed genes. Experimental data from MS studies can play a major role in confirming and correcting gene structure--proteogenomics. However, there are some technical and practical challenges to overcome, since proteogenomics requires pipelines comprising a complex set of interconnected modules as well as bespoke routines, for example in protein inference and statistics. We are introducing a complete, open source pipeline for proteogenomics, called ProteoAnnotator, which incorporates a graphical user interface and implements the Proteomics Standards Initiative mzIdentML standard for each analysis stage. All steps are included as standalone modules with the mzIdentML library, allowing other groups to re-use the whole pipeline or constituent parts within other tools. We have developed new modules for pre-processing and combining multiple search databases, for performing peptide-level statistics on mzIdentML files, for scoring grouped protein identifications matched to a given genomic locus to validate that updates to the official gene models are statistically sound and for mapping end results back onto the genome. ProteoAnnotator is available from http://www.proteoannotator.org/. All MS data have been deposited in the ProteomeXchange with identifiers PXD001042 and PXD001390 (http://proteomecentral.proteomexchange.org/dataset/PXD001042; http://proteomecentral.proteomexchange.org/dataset/PXD001390).

Liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) is an important technique for detecting peptides in proteomics studies. Here, we present an open source software tool, termed IPeak, a peptide identification pipeline that is designed to combine the Percolator post-processing algorithm and multi-search strategy to enhance the sensitivity of peptide identifications without compromising accuracy. IPeak provides a graphical user interface (GUI) as well as a command-line interface, which is implemented in JAVA and can work on all three major operating system platforms: Windows, Linux/Unix and OS X. IPeak has been designed to work with the mzIdentML standard from the Proteomics Standards Initiative (PSI) as an input and output, and also been fully integrated into the associated mzidLibrary project, providing access to the overall pipeline, as well as modules for calling Percolator on individual search engine result files. The integration thus enables IPeak (and Percolator) to be used in conjunction with any software packages implementing the mzIdentML data standard. IPeak is freely available and can be downloaded under an Apache 2.0 license at https://code.google.com/p/mzidentml-lib/.

The open XML format mzML, used for representation of mass spectrometry (MS) data, is pivotal for the development of platform-independent MS analysis software. Although conversion from vendor formats to mzML must take place on a platform on which the vendor libraries are available (i.e. Windows), once mzML files have been generated, they can be used on any platform. However, the mzML format has turned out to be less efficient than vendor formats. In many cases, the naive mzML representation is 4-fold or even up to 18-fold larger compared to the original vendor file. In disk I/O limited setups, a larger data file also leads to longer processing times, which is a problem given the data production rates of modern mass spectrometers. In an attempt to reduce this problem, we here present a family of numerical compression algorithms called MS-Numpress, intended for efficient compression of MS data. To facilitate ease of adoption, the algorithms target the binary data in the mzML standard, and support in main proteomics tools is already available. Using a test set of 10 representative MS data files we demonstrate typical file size decreases of 90% when combined with traditional compression, as well as read time decreases of up to 50%. It is envisaged that these improvements will be beneficial for data handling within the MS community.

The first paper in this series established that the projective analogue of the Young symmetrizer recently introduced by Nazarov has a naturalPxQ-structure comparable with thepq-form of the classical symmetrizer. This second paper develops the theory on this decomposition further. A more efficient construction of the projective symmetrizer is presented for certain classes of partitions; this approach yields a “compact” expression for the intermediate factorxλin the projective decomposition.

Evidence from the literature has been considered for factors controlling the occlusion and retention of gas in powders, particularly those produced by mechanical alloying (MA). A series of experiments has been performed on oxide dispersion strengthened Fe3Al and PM 2000 powders to determine recovery, recrystallisation and vacuum degassing behaviour. As-MA ODS Fe3Al powders begin to recover and recrystallise at lower temperatures than PM 2000 (550°C c.f. 750°C, respectively) and recrystallise to a finer grain size (∼10μm maximum mean linear intercept c.f. ∼50μm in PM 2000). Both powders outgassed hydrogen, as well as smaller quantities of nitrogen and water vapour. However, PM 2000 released more hydrogen than Fe3Al. Both powders contained small pores which are likely to have entrained molecular hydrogen. Defects contained in consolidated secondary recrystallised Fe3Al included porosity, residual stringers of fine grains and intrusions. The latter were larger, more numerous and slightly elongated wi...

Motivation: The Functional Genomics Experiment Object Model (FuGE) supports modelling of experimental processes either directly or through extensions that specialize FuGE for use in specific contexts. FuGE applications commonly include components that capture, store and search experiment descriptions, where the requirements of different applications have much in common. Results: We describe a toolkit that supports data capture, storage and web-based search of FuGE experiment models; the toolkit can be used directly on FuGE compliant models or configured for use with FuGE extensions. The toolkit is illustrated using a FuGE extension standardized by the proteomics standards initiative, namely GelML. Availability: The toolkit and a demonstration are available at http://code.google.com/p/fugetoolkit Contact: khalid.belhajjame@manchester.ac.uk

The plenary session of the Proteomics Standards Initiative of the Human Proteome Organisation provided an opportunity to update delegates on the progress of the work of the Human Proteome Organisation's Proteomics Standards Initiative (HUPO-PSI) to develop and implement standards in the field of proteomics. Significant advances have been made since the previous congress, with several of the interchange standards and minimal requirements documents being submitted for publication in the literature and being more widely adopted by both manufacturers and data repositories. An exciting development over the interim twelve months is the ongoing merger of the two existing mass spectrometry standards, the PSI mzData and Institute for Systems Biology mzXML, into a single product. This should be achieved by early in 2007.

Since its conception in April 2002, the Human Proteome Organisation Proteomics Standards Initiative has contributed to the development of community standards for proteomics in a collaborative and very dynamic manner, resulting in the publication and increasing adoption of a number of interchange formats and controlled vocabularies. Repositories supporting these formats are being established or are already operational. In parallel with this, minimum reporting requirement have been developed and are now maturing to the point where they have been submitted for journal publication after prolonged exposure to community-input via the PSI website.

This paper is the first in a series of three papers on the Young symmetrizers for the spin representations of the symmetric group. In this opening paper, it is shown that the projective analogue of the Young symmetrizer recently introduced by Nazarov has a structure resembling thepλqλ-form exhibited by the classical symmetrizer. In contrast to the classical case, our decomposition of the projective symmetrizer requires an additional intermediate factorxλ. This factor will be studied in greater detail in the later papers.

The killer cell immunoglobulin-like receptors (KIR) play a fundamental role in the innate immune system, through their interactions with human leucocyte antigen (HLA) molecules, leading to the modulation of activity in natural killer (NK) cells, mainly related to killing pathogen-infected cells. KIR genes are hugely polymorphic both in the number of genes an individual carries and in the number of alleles identified. We have previously developed the Allele Frequency Net Database (AFND, http://www.allelefrequencies.net), which captures worldwide frequencies of alleles, genes and haplotypes for several immune genes, including KIR genes, in healthy populations, covering >4 million individuals. Here, we report the creation of a new database within AFND, named KIR and Diseases Database (KDDB), capturing a large quantity of data derived from publications in which KIR genes, alleles, genotypes and/or haplotypes have been associated with infectious diseases (e.g. hepatitis C, HIV, malaria), autoimmune disorders (e.g. type I diabetes, rheumatoid arthritis), cancer and pregnancy-related complications. KDDB has been created through an extensive manual curation effort, extracting data on more than a thousand KIR-disease records, comprising >50 000 individuals. KDDB thus provides a new community resource for understanding not only how KIR genes are associated with disease, but also, by working in tandem with the large data sets already present in AFND, where particular genes, genotypes or haplotypes are present in worldwide populations or different ethnic groups. We anticipate that KDDB will be an important resource for researchers working in immunogenetics. Database URL: http://www.allelefrequencies.net/diseases/

The Library of Apicomplexan Metabolic Pathways (LAMP, http://www.llamp.net) is a web database that provides near complete mapping from genes to the central metabolic functions for some of the prominent intracellular parasites of the phylum Apicomplexa. This phylum includes the causative agents of malaria, toxoplasmosis and theileriosis—diseases with a huge economic and social impact. A number of apicomplexan genomes have been sequenced, but the accurate annotation of gene function remains challenging. We have adopted an approach called metabolic reconstruction, in which genes are systematically assigned to functions within pathways/networks for Toxoplasma gondii, Neospora caninum, Cryptosporidium and Theileria species, and Babesia bovis. Several functions missing from pathways have been identified, where the corresponding gene for an essential process appears to be absent from the current genome annotation. For each species, LAMP contains interactive diagrams of each pathway, hyperlinked to external resources and annotated with detailed information, including the sources of evidence used. We have also developed a section to highlight the overall metabolic capabilities of each species, such as the ability to synthesize or the dependence on the host for a particular metabolite. We expect this new database will become a valuable resource for fundamental and applied research on the Apicomplexa.

The scientific objective of the VIRGO experiment (Variability of solar IRradiance and Gravity Oscillations) is to determine the characteristics of pressure and internal gravity oscillations by observing irradiance and radiance variations, to measure the solar total and spectral irradiance and to quantify their variability over periods of days to the duration of the mission. With these data helioseismological methods can be used to probe the solar interior. Certain characteristics of convection and its interaction with magnetic fields, related to, for example, activity, will be studied from the results of the irradiance monitoring and from the comparison of amplitudes and phases of the oscillations as manifest in brightness from VIRGO, in velocity from GOLF, and in both velocity and continuum intensity from SOI/MDI. The VIRGO experiment contains two different active-cavity radiometers for monitoring the solar ‘constant’, two three-channel sunphotometers (SPM) for the measurement of the spectral irradiance at 402, 500 and 862 nm, and a low-resolution imager (LOI) with 12 pixels, for the measurement of the radiance distribution over the solar disk at 500 um. In this paper the scientific objectives of VIRGO are presented, the instruments and the data acquisition and control system are described in detail, and their measured performance is given.

Numerous software packages exist to provide support for quantifying peptides and proteins from mass spectrometry (MS) data. However, many support only a subset of experimental methods or instrument types, meaning that laboratories often have to use multiple software packages. The Progenesis LC-MS software package from Nonlinear Dynamics is a software solution for label-free quantitation. However, many laboratories using Progenesis also wish to employ stable isotope-based methods that are not natively supported in Progenesis. We have developed a Java programming interface that can use the output files produced by Progenesis, allowing the basic MS features quantified across replicates to be used in a range of different experimental methods. We have developed post-processing software (the Progenesis Post-Processor) to embed Progenesis in the analysis of stable isotope labeling data and top3 pseudo-absolute quantitation. We have also created export ability to the new data standard, mzQuantML, produced by the Proteomics Standards Initiative to facilitate the development and standardization process. The software is provided to users with a simple graphical user interface for accessing the different features. The underlying programming interface may also be used by Java developers to develop other routines for analyzing data produced by Progenesis.

This special issue examines cutting-edge approaches for quantitative proteomics, focusing on bioinformatics challenges and solutions in this complex field. Throughout the history of mass spectrometry (MS)-based proteomic research, the interpretation of data has been challenging. As MS techniques have increasingly become high-throughput, the design and implementation of bespoke software packages and algorithms for statistical analysis have become important areas of research. The field has generally moved towards techniques based on liquid chromatography (LC) directly coupled to a tandem mass spectrometer (LC-MS/MS), used to analyze peptides resulting from digestion of proteins. Approaches can generally be classified as “discovery,” in which more proteins are assessed at lower accuracy, or “targeted,” often performed by selected reaction monitoring (SRM), in which a smaller number of proteins are more accurately assessed. In all approaches, the ion intensity signal observed is difficult to predict based on a peptide sequence alone, although analysis of an individual peptide is highly reproducible. As such, a variety of experimental approaches have been designed to calculate the relative abundance of peptides by LC-MS, using differential labels applied prior to sample mixing, or label-free methods on samples run in parallel. These relative signals for peptides can be converted into relative protein abundance values, taking into account ambiguities in the assignment of peptides to proteins, or conflicting evidence from different peptides. Absolute protein abundance can usually only be calculated by incorporating differentially-labeled internal standards (peptides or proteins) in known abundances and converting the unit-less intensities from a relative technique into an absolute value. This special issue covers a range of important challenges facing the proteome bioinformatics community. It is hugely challenging for software developers to cope with the heterogeneity in proteomics; there are many different experimental methods, different instrument file formats, and different intermediate formats. Many software packages handle only a subset of approaches and they are difficult to connect. A collection of U.K.-based proteome bioinformatics groups have collaborated to construct a detailed review of the state-of-the-art in the software provision for quantitative proteomics, and describe a web-based resource that helps researchers to select the appropriate software tools for their local pipeline (Gonzalez-Galarza et al., 2012). The article also briefly describes community data standards under development by the Proteomics Standards Initiative, which will help solve some of the problems of heterogeneity and interconnectivity between software. The issue of software heterogeneity is also tackled in an original study from the group of Lennart Martens, in which the interplay between label-free approaches for quantitation and search engines for peptide/protein identification is analyzed (Degroeve et al., 2012). They demonstrate a significant difference in the results of quantitative analysis through the differential selection of a search engine to use for identification, and they provide recommendations for optimizing these analyses. Two new software packages are also presented in this issue: Eisenacher and colleagues describe the FindPairs module of the PeakQuant software, targeted towards approaches using 15N labeling, which is not well covered in the most popular open source tools (Eisenacher et al., 2012); Qi and colleagues describe an open source post-processing tool for using the commercial package Progenesis LC-MS (designed solely for label-free analysis), as a tool for the analysis of stable isotope labeling data and Top3 pseudo absolute quantitation (Qi et al., 2012). One of the major missing aspects of quantitative proteomics approaches is any detailed understanding of the importance of the efficiency of digestion. It is widely acknowledged that enzymatic digestion of proteins, say with trypsin, is rarely 100% efficient. For approaches in which proteins are digested into peptides in parallel samples, any variability in peptide digestion will have marked effects on estimates of peptide abundance, and thus these “missed cleavage” peptides are problematic for quantitation. Lawless and Hubbard present a software tool, incorporating support vector machines, capable of accurate prediction of candidate peptide bonds that will be poorly cleaved, leading to missed cleavage peptides (Lawless and Hubbard, 2012). In targeted approaches based on SRM, particular peptides are selected for analysis based on transitions (triplets of chromatographic retention time, peptide mass/charge, and peptide fragmentation product mass/charge). These transitions are difficult to predict computationally, and so require experimental data to be collected in advance for peptides of interest. Fan and colleagues describe a web-based tool that can help in the design of transitions, called MRMAid 2.0 (Fan et al., 2012). MRMAid 2.0 demonstrates the utility of public data deposition integrated into the new version, in which the authors have included a module for extracting large volumes of data from the PRIDE database at the EBI (http://www.ebi.ac.uk/pride/). Lastly, the development of advanced statistical approaches is a growing area of importance, since the complexity of proteomic data means standard statistical frameworks are insufficient and bespoke approaches are required. Richardson and colleagues present a bayesian statistical framework for calculating accurate relative peptide and protein abundance values from data that contain a considerable noise component, as is the case for most if not all MS-based approaches (Richardson et al., 2012). This special issue presents solutions to some of the challenges in quantitative proteomics, but there is still an enormous amount of work to do in this exciting field. Software tools are needed that can evolve in tandem with technical innovation and function robustly even after developers have moved on. Interconnectivity between different pipelines is still challenging, and will remain so until universal file format standards become more widely adopted. Proteomics data are complex and multi-layered, with noise introduced at several different stages at the bench and in silico, for which bespoke statistical tests and normalization methods are currently lacking. Finally, proteomics will benefit from improved benchmarking and comparison of tools, and the release of more gold-standard data sets is undoubtedly needed. This dynamic research field is continuing to grow, and it is likely to present many new and exciting challenges in bioinformatics for many years to come.

The development of ion mobility (IM) MS instruments has the capability to provide an added dimension to peptide analysis pipelines in proteomics, but, as yet, there are few software tools available for analysing such data. IM can be used to provide additional separation of parent ions or product ions following fragmentation. In this work, we have created a set of software tools that are capable of converting three dimensional IM data generated from analysis of fragment ions into a variety of formats used in proteomics. We demonstrate that IM can be used to calculate the charge state of a fragment ion, demonstrating the potential to improve peptide identification by excluding non-informative ions from a database search. We also provide preliminary evidence of structural differences between b and y ions for certain peptide sequences but not others. All software tools and data sets are made available in the public domain at http://code.google.com/p/ion-mobility-ms-tools/.

We report the release of mzIdentML, an exchange standard for peptide and protein identification data, designed by the Proteomics Standards Initiative. The format was developed by the Proteomics Standards Initiative in collaboration with instrument and software vendors, and the developers of the major open-source projects in proteomics. Software implementations have been developed to enable conversion from most popular proprietary and open-source formats, and mzIdentML will soon be supported by the major public repositories. These developments enable proteomics scientists to start working with the standard for exchanging and publishing data sets in support of publications and they provide a stable platform for bioinformatics groups and commercial software vendors to work with a single file format for identification data.

Background/Question/Methods: Ecological theory has begun to incorporate humans as part of coupled socio-ecological systems. Modern urban development provides an excellent laboratory to examine the interplay among socio-ecological relationships. Urban land and water management decisions result from dynamic interactions between institutional, individual and ecological factors. Landscaping and irrigation at any particular residence, for example, is a product of geography, hydrology, soil, and other local environmental conditions, the homeowners’ cultural preferences, socioeconomic status, identity construction, neighborhood dynamics, as well as zoning laws, market conditions, city policies, and county/state/federal government regulations. Since land and water management are key determinants of habitat for other species, urban biodiversity is strongly driven by the outcome of interactions between these variables. This study addresses the significance of water as a key variable in the Fresno-Clovis Metropolitan Area (FCMA), shaping current patterns of landscape and water use, at a time when the city of Fresno is installing meters as a regulatory tool to conserve water. We combine data from a citizen science bird monitoring project, field surveys of trees, and mail surveys of residents to address interactions among key components of the urban socioecological system. Results/Conclusions: We present results of multivariate analyses of bird and tree surveys to show that neighborhood income and irrigation levels interact to influence species diversity of both taxa. Data from the Fresno Bird Count found that bird species richness and functional group diversity are both strongly correlated with residential irrigation and neighborhood income levels. Tree species diversity shows a similar pattern. We examine these results to test and develop several theoretical models explaining outdoor water use behaviors, with the aim of assessing the resilience of such behaviors with the introduction of water metering in Fresno, and the resilience of urban plant and bird communities to resulting changes in water use in the landscape. We argue that socioeconomic status results from a complex interplay of cultural, economic, structural, and social-psychological factors, influencing institutional policies regarding the governance of water resources, and in turn impacts biodiversity within the urban landscape through spatial and temporal variations in water usage. This study is part of a long-term research project that examines the impacts of human water usage and water use policies on biodiversity within an urban environment.

*Background/Question/Methods:* Ecological theory has begun to incorporate humans as part of coupled socio-ecological systems. Modern urban development provides an excellent laboratory to examine the interplay among socio-ecological relationships. Urban land and water management decisions result from dynamic interactions between institutional, individual and ecological factors. Landscaping and irrigation at any particular residence, for example, is a product of geography, hydrology, soil, and other local environmental conditions, the homeowners’ cultural preferences, socioeconomic status, identity construction, neighborhood dynamics, as well as zoning laws, market conditions, city policies, and county/state/federal government regulations. Since land and water management are key determinants of habitat for other species, urban biodiversity is strongly driven by the outcome of interactions between these variables. This study addresses the significance of water as a key variable in the Fresno-Clovis Metropolitan Area (FCMA), shaping current patterns of landscape and water use, at a time when the city of Fresno is installing meters as a regulatory tool to conserve water. We combine data from a citizen science bird monitoring project, field surveys of trees, and mail surveys of residents to address interactions among key components of the urban socioecological system. *Results/Conclusions:* We present results of multivariate analyses of bird and tree surveys to show that neighborhood income and irrigation levels interact to influence species diversity of both taxa. Data from the Fresno Bird Count found that bird species richness and functional group diversity are both strongly correlated with residential irrigation and neighborhood income levels. Tree species diversity shows a similar pattern. We examine these results to test and develop several theoretical models explaining outdoor water use behaviors, with the aim of assessing the resilience of such behaviors with the introduction of water metering in Fresno, and the resilience of urban plant and bird communities to resulting changes in water use in the landscape. We argue that socioeconomic status results from a complex interplay of cultural, economic, structural, and social-psychological factors, influencing institutional policies regarding the governance of water resources, and in turn impacts biodiversity within the urban landscape through spatial and temporal variations in water usage. This study is part of a long-term research project that examines the impacts of human water usage and water use policies on biodiversity within an urban environment.

[1] Methane (CH4) and nitrous oxide (N2O) have strong radiative properties in the Earth's atmosphere and both are regulated through the United Nations Framework Convention on Climate Change. Through this convention the United Kingdom is obliged to report an inventory of annual emission estimates from 1990. This paper describes a methodology that estimates emissions of CH4 and N2O completely independent of the inventory values. Emissions have been estimated for each year 1990–2007 for the United Kingdom and for NW Europe. The methodology combines high-frequency observations from Mace Head, a monitoring site on the west coast of Ireland, with an atmospheric dispersion model and an inversion system. The sensitivities of the inversion method to the modeling assumptions are reported. The 20 year Northern Hemisphere midlatitude baseline mixing ratios, growth rates, and seasonal cycles of both gases are also presented. The results indicate reasonable agreement between the inventory and inversion results for the United Kingdom for N2O over the entire period. For CH4 the agreement is poor in the 1990s but good in the 2000s. The UK CH4 inventory reported reduction from 1990–1992 to 2005–2007 (over 50%) is dominated by changes to landfill and coal mine emissions and is more than double the corresponding drop in the inversion estimated emissions (24%). The inversion results suggest that the United Kingdom has met its Kyoto commitment (−12.5%) but by a smaller margin (−14.3%) than reported (−17.3%). The results for NW Europe with the United Kingdom removed show reasonable agreement in trend, on average the inversion results for N2O are 25% lower and for CH4 21% higher.

Background Proteomic techniques allow researchers to perform detailed analyses of cellular states and many studies are published each year, which highlight large numbers of proteins quantified in different samples. However, currently few data sets make it into public databases with sufficient metadata to allow other groups to verify findings, perform data mining or integrate different data sets. The Proteomics Standards Initiative has released a series of "Minimum Information About a Proteomics Experiment" guideline documents (MIAPE modules) and accompanying data exchange formats. This article focuses on proteomic studies based on gel electrophoresis and demonstrates how the corresponding MIAPE modules can be fulfilled and data deposited in public databases, using a new experimental data set as an example. Findings We have performed a study of the effects of an anabolic agent (salbutamol) at two different time points on the protein complement of rat skeletal muscle cells, quantified by difference gel electrophoresis. In the DIGE study, a total of 31 non-redundant proteins were identified as being potentially modulated at 24 h post treatment and 110 non redundant proteins at 96 h post-treatment. Several categories of function have been highlighted as strongly enriched, providing candidate proteins for further study. We also use the study as an example of best practice for data deposition. Conclusions We have deposited all data sets from this study in public databases for further analysis by the community. We also describe more generally how gel-based protein identification data sets can now be deposited in the PRoteomics IDEntifications database (PRIDE), using a new software tool, the PRIDESpotMapper, which we developed to work in conjunction with the PRIDE Converter application. We also demonstrate how the ProteoRed MIAPE generator tool can be used to create and share a complete and compliant set of MIAPE reports for this experiment and others.

The allele frequency net database (http://www.allelefrequencies.net) is an online repository that contains information on the frequencies of immune genes and their corresponding alleles in different populations. The extensive variability observed in genes and alleles related to the immune system response and its significance in transplantation, disease association studies and diversity in populations led to the development of this electronic resource. At present, the system contains data from 1133 populations in 608 813 individuals on the frequency of genes from different polymorphic regions such as human leukocyte antigens, killer-cell immunoglobulin-like receptors, major histocompatibility complex Class I chain-related genes and a number of cytokine gene polymorphisms. The project was designed to create a central source for the storage of frequency data and provide individuals with a set of bioinformatics tools to analyze the occurrence of these variants in worldwide populations. The resource has been used in a wide variety of contexts, including clinical applications (histocompatibility, immunology, epidemiology and pharmacogenetics) and population genetics. Demographic information, frequency data and searching tools can be freely accessed through the website.

We report the results of Single Event Effect (SEE) and Total Integrated Dose (TID) testing of a very-low-noise six-channel electrometer Application Specific Integrated Circuit (ASIC) constructed through the MOSIS service using the ON Semiconductor C5N process. The ASICs were designed using Radiation Hard By Design (RHBD) layout rules, and TID mitigation strategies. This testing provides a verification that the device does not show latch-up behavior, and that performance is not unduly compromised by TID. The SEE testing, using heavy ions, took place at the Single Event Effects Facility at Texas A&M University using the 24.8~MeV/u beam with ions Ar, Kr, and Xe giving a range of Linear Energy Transfer (LET) at the device of 7.5-63.5 MeV cm2/mg. No latch-ups were seen even at an elevated temperature (30C). TID testing using protons was conducted at the Indiana University Cyclotron Facility on the Radiation Effects Research Program RERS2 beamline. Parts were tested to a total dose of 300 krad(Si). As these ASICs are constructed using CMOS technology there will be no Enhanced Low Dose Rate Sensitivity (ELDRS)