Scientific workflows for bibliometrics

Scientific workflows organize the assembly of specialized software into an overall data flow and are particularly well suited for multi-step analyses using different types of software tools. They are also favorable in terms of reusability, as previously designed workflows could be made publicly available through the myExperiment community and then used in other workflows. We here illustrate how scientific workflows and the Taverna workbench in particular can be used in bibliometrics. We discuss the specific capabilities of Taverna that makes this software a powerful tool in this field, such as automated data import via Web services, data extraction from XML by XPaths, and statistical analysis and visualization with R. The support of the latter is particularly relevant, as it allows integration of a number of recently developed R packages specifically for bibliometrics. Examples are used to illustrate the possibilities of Taverna in the fields of bibliometrics and scientometrics.Proteomic

In Conversation with Mubin Shaikh: From Salafi Jihadist to Undercover Agent inside the "Toronto 18" Terrorist Group

This interview with former undercover agent Mubin Shaikh can help academics and security practitioners understand the key role played and the challenges faced by covert human intelligence sources within domestic terrorist groups. The interview highlights the identity crisis, the personal factors, and the allure of jihadi militancy that initially drove Shaikh to join a Salafi jihadist group. It investigates Shaikh’s process of disengagement from the Salafi jihadist belief system and his rediscovery of a moderate, inclusive, and benevolent form of Islam. It explores his work as an undercover agent for the Canadian Security Intelligence Service, the Royal Canadian Mounted Police, and the Integrated National Security Enforcement Team responsible for disrupting domestic terrorist groups. The “Toronto 18” terrorist cell, the key role played by undercover agents in preventing terrorist action, and the challenges posed by entrapment are also discussed

Renal expression and serum levels of high mobility group box 1 protein in lupus nephritis

INTRODUCTION: High mobility group box 1 protein (HMGB1) is a nuclear DNA binding protein acting as a pro-inflammatory mediator following extracellular release. HMGB1 has been increasingly recognized as a pathogenic mediator in several inflammatory diseases. Elevated serum levels of HMGB1 have been detected in autoimmune diseases including Systemic lupus erythematosus (SLE). However, the local expression of HMGB1 in active lupus nephritis (LN) is not known. Here we aimed to study both tissue expression and serum levels of HMGB1 in LN patients with active disease and after induction therapy. METHODS: Thirty-five patients with active LN were included. Renal biopsies were performed at baseline and after standard induction therapy; corticosteroids combined with immunosuppressive drugs. The biopsies were evaluated according to the World Health Organization (WHO) classification and renal disease activity was estimated using the British Isles lupus assessment group (BILAG) index. Serum levels of HMGB1 were analysed by western blot. HMGB1 expression in renal tissue was assessed by immunohistochemistry at baseline and follow-up biopsies in 25 patients. RESULTS: Baseline biopsies showed WHO class III, IV or V and all patients had high renal disease activity (BILAG A/B). Follow-up biopsies showed WHO I to II (n = 14), III (n = 6), IV (n = 3) or V (n = 12), and 15/35 patients were regarded as renal responders (BILAG C/D). At baseline HMGB1 was significantly elevated in serum compared to healthy controls (P < 0.0001). In all patients, serum levels decreased only slightly; however, in patients with baseline WHO class IV a significant decrease was observed (P = 0.03). Immunostaining revealed a pronounced extranuclear HMGB1 expression predominantly outlining the glomerular endothelium and in the mesangium. There was no clear difference in HMGB1 expression comparing baseline and follow-up biopsies or any apparent association to histopathological classification or clinical outcome. CONCLUSIONS: Renal tissue expression and serum levels of HMGB1 were increased in LN. The lack of decrease of HMGB1 in serum and tissue after immunosuppressive therapy in the current study may reflect persistent inflammatory activity. This study clearly indicates a role for HMGB1 in LN

Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset

Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics

Sample preparation: a crucial factor for the analytical performance of rationally designed MALDI matrices

Evidence is presented that the performance of the rationally designed MALDI matrix 4-chloro-α-cyanocinnamic acid (ClCCA) in comparison to its well-established predecessor α-cyano-4-hydroxycinnamic acid (CHCA) is significantly dependent on the sample preparation, such as the choice of the target plate. In this context, it becomes clear that any rational designs of MALDI matrices and their successful employment have to consider a larger set of physicochemical parameters, including sample crystallization and morphology/topology, in addition to parameters of basic (solution and/or gas-phase) chemistry

Autopiquer - a robust and reliable peak detection algorithm for mass spectrometry

We present a simple algorithm for robust and unsupervised peak detection by determining a noise threshold in isotopically resolved mass spectrometry data. Solving this problem will greatly reduce the subjective and time consuming manual picking of mass spectral peaks and so will prove beneficial in many research applications. The Autopiquer approach uses autocorrelation to test for the presence of (isotopic) structure in overlapping windows across the spectrum. Within each window, a noise threshold is optimized to remove the most unstructured data whilst keeping as much of the (isotopic) structure as possible. This algorithm has been successfully demonstrated for both peak detection and spectral compression on data from many different classes of mass spectrometer and for different sample types and this approach should also be extendible to other types of data that contain regularly spaced discrete peaks

CompareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry Datasets

It has long been known that biological species can be identified from mass spectrometry data alone. Ten years ago, we described a method and software tool, compareMS2, for calculating a distance between sets of tandem mass spectra, as routinely collected in proteomics. This method has seen use in species identification and mixture characterization in food and feed products, as well as other applications. Here, we present the first major update of this software, including a new metric, a graphical user interface and additional functionality. The data have been deposited to ProteomeXchange with dataset identifier PXD034932.publishedVersio

Text mining and computational chemistry reveal trends in applications of laser desorption/ionization techniques to small molecules

Continued development of laser desorption/ionization (LDI) since its inception in the 1960s has produced an explosion of soft ionization techniques, where ionization is assisted by the physical or chemical properties of a structure or matrix. While many of these techniques have primarily been used to ionize large biomolecules, including proteins, some have recently seen increasing applications to small molecules such as pharmaceuticals. Small molecules pose particular challenges for LDI techniques, including interference from the matrix or support in the low mass range. To investigate trends in the application of soft LDI techniques to small molecules, we combined text mining and computational chemistry, looking specifically at matrix substances, analyte properties, and the research domain. In addition to making visible the history of LDI techniques, the results may inform the choice of method and suggest new avenues of method development. All software and collected data are freely available on GitHub (https://github.com/ReinV/SCOPE), VOSviewer (https://www.vosviewer.com), and OSF (https://osf.io/zkmua/).Proteomic

APE in the wild: automated exploration of proteomics workflows in the bio.tools registry

The bio.tools registry is a main catalogue of computational tools in the life sciences. More than 17 000 tools have been registered by the international bioinformatics community. The bio.tools metadata schema includes semantic annotations of tool functions, that is, formal descriptions of tools' data types, formats, and operations with terms from the EDAM bioinformatics ontology. Such annotations enable the automated composition of tools into multistep pipelines or workflows. In this Technical Note, we revisit a previous case study on the automated composition of proteomics workflows. We use the same four workflow scenarios but instead of using a small set of tools with carefully handcrafted annotations, we explore workflows directly on bio.tools. We use the Automated Pipeline Explorer (APE), a reimplementation and extension of the workflow composition method previously used. Moving "into the wild" opens up an unprecedented wealth of tools and a huge number of alternative workflows. Automated composition tools can be used to explore this space of possibilities systematically. Inevitably, the mixed quality of semantic annotations in bio.tools leads to unintended or erroneous tool combinations. However, our results also show that additional control mechanisms (tool filters, configuration options, and workflow constraints) can effectively guide the exploration toward smaller sets of more meaningful workflows.Proteomic