Apex Peptide Elution Chain Selection: A New Strategy for Selecting Precursors in 2D-LC-MALDI-TOF/TOF Experiments on Complex Biological Samples

LC-MALDI provides an often overlooked opportunity to exploit the separation between LC-MS and MS/MS stages of a 2D-LC-MS-based proteomics experiment, that is, by making a smarter selection for precursor fragmentation. Apex Peptide Elution Chain Selection (APECS) is a simple and powerful method for intensity-based peptide selection in a complex sample separated by 2D-LC, using a MALDI-TOF/TOF instrument. It removes the peptide redundancy present in the adjacent first-dimension (typically strong cation exchange, SCX) fractions by constructing peptide elution profiles that link the precursor ions of the same peptide across SCX fractions. Subsequently, the precursor ion most likely to fragment successfully in a given profile is selected for fragmentation analysis, selecting on precursor intensity and absence of adjacent ions that may cofragment. To make the method independent of experiment-specific tolerance criteria, we introduce the concept of the branching factor, which measures the likelihood of false clustering of precursor ions based on past experiments. By validation with a complex proteome sample of Arabidopsis thaliana, APECS identified an equivalent number of peptides as a conventional data-dependent acquisition method but with a 35% smaller work load. Consequently, reduced sample depletion allowed further selection of lower signal-to-noise ratio precursor ions, leading to a larger number of identified unique peptides.

Git4Voc: Git-based Versioning for Collaborative Vocabulary Development

Collaborative vocabulary development in the context of data integration is the process of finding consensus between the experts of the different systems and domains. The complexity of this process is increased with the number of involved people, the variety of the systems to be integrated and the dynamics of their domain. In this paper we advocate that the realization of a powerful version control system is the heart of the problem. Driven by this idea and the success of Git in the context of software development, we investigate the applicability of Git for collaborative vocabulary development. Even though vocabulary development and software development have much more similarities than differences there are still important differences. These need to be considered within the development of a successful versioning and collaboration system for vocabulary development. Therefore, this paper starts by presenting the challenges we were faced with during the creation of vocabularies collaboratively and discusses its distinction to software development. Based on these insights we propose Git4Voc which comprises guidelines how Git can be adopted to vocabulary development. Finally, we demonstrate how Git hooks can be implemented to go beyond the plain functionality of Git by realizing vocabulary-specific features like syntactic validation and semantic diffs

Adaptive Parallel Iterative Deepening Search

Many of the artificial intelligence techniques developed to date rely on heuristic search through large spaces. Unfortunately, the size of these spaces and the corresponding computational effort reduce the applicability of otherwise novel and effective algorithms. A number of parallel and distributed approaches to search have considerably improved the performance of the search process. Our goal is to develop an architecture that automatically selects parallel search strategies for optimal performance on a variety of search problems. In this paper we describe one such architecture realized in the Eureka system, which combines the benefits of many different approaches to parallel heuristic search. Through empirical and theoretical analyses we observe that features of the problem space directly affect the choice of optimal parallel search strategy. We then employ machine learning techniques to select the optimal parallel search strategy for a given problem space. When a new search task is input to the system, Eureka uses features describing the search space and the chosen architecture to automatically select the appropriate search strategy. Eureka has been tested on a MIMD parallel processor, a distributed network of workstations, and a single workstation using multithreading. Results generated from fifteen puzzle problems, robot arm motion problems, artificial search spaces, and planning problems indicate that Eureka outperforms any of the tested strategies used exclusively for all problem instances and is able to greatly reduce the search time for these applications

A MANAGED APPROACH OF INTERACTION BETWEEN AGILE SCRUM AND SOFTWARE CONFIGURATION MANAGEMENT SYSTEM

In current age the agile software development is one of the most popular software development methodology but due the mismanagement and lack of efficient handling of agile scrum and software configuration management system our software industry is facing a high rate of failed product, keeping this as my motivation, I have designed a efficient checklist which will help the industry to organized the interaction between agile scrum process and software configuration management system in a efficient and managed way and definitely that will increase the successful project in the software industry. Index-term : Agile Scrums, Software development, Software configuration management system, Checklist, Successful project

Virtual patients design and its effect on clinical reasoning and student experience : a protocol for a randomised factorial multi-centre study

Background Virtual Patients (VPs) are web-based representations of realistic clinical cases. They are proposed as being an optimal method for teaching clinical reasoning skills. International standards exist which define precisely what constitutes a VP. There are multiple design possibilities for VPs, however there is little formal evidence to support individual design features. The purpose of this trial is to explore the effect of two different potentially important design features on clinical reasoning skills and the student experience. These are the branching case pathways (present or absent) and structured clinical reasoning feedback (present or absent). Methods/Design This is a multi-centre randomised 2x2 factorial design study evaluating two independent variables of VP design, branching (present or absent), and structured clinical reasoning feedback (present or absent).The study will be carried out in medical student volunteers in one year group from three university medical schools in the United Kingdom, Warwick, Keele and Birmingham. There are four core musculoskeletal topics. Each case can be designed in four different ways, equating to 16 VPs required for the research. Students will be randomised to four groups, completing the four VP topics in the same order, but with each group exposed to a different VP design sequentially. All students will be exposed to the four designs. Primary outcomes are performance for each case design in a standardized fifteen item clinical reasoning assessment, integrated into each VP, which is identical for each topic. Additionally a 15-item self-reported evaluation is completed for each VP, based on a widely used EViP tool. Student patterns of use of the VPs will be recorded. In one centre, formative clinical and examination performance will be recorded, along with a self reported pre and post-intervention reasoning score, the DTI. Our power calculations indicate a sample size of 112 is required for both primary outcomes

Virtual patient design : exploring what works and why : a grounded theory study

Objectives: Virtual patients (VPs) are online representations of clinical cases used in medical education. Widely adopted, they are well placed to teach clinical reasoning skills. International technology standards mean VPs can be created, shared and repurposed between institutions. A systematic review has highlighted the lack of evidence to support which of the numerous VP designs may be effective, and why. We set out to research the influence of VP design on medical undergraduates. Methods: This is a grounded theory study into the influence of VP design on undergraduate medical students. Following a review of the literature and publicly available VP cases, we identified important design properties. We integrated them into two substantial VPs produced for this research. Using purposeful iterative sampling, 46 medical undergraduates were recruited to participate in six focus groups. Participants completed both VPs, an evaluation and a 1-hour focus group discussion. These were digitally recorded, transcribed and analysed using grounded theory, supported by computer-assisted analysis. Following open, axial and selective coding, we produced a theoretical model describing how students learn from VPs. Results: We identified a central core phenomenon designated ‘learning from the VP’. This had four categories: VP Construction; External Preconditions; Student–VP Interaction, and Consequences. From these, we constructed a three-layer model describing the interactions of students with VPs. The inner layer consists of the student's cognitive and behavioural preconditions prior to sitting a case. The middle layer considers the VP as an ‘encoded object’, an e-learning artefact and as a ‘constructed activity’, with associated pedagogic and organisational elements. The outer layer describes cognitive and behavioural change. Conclusions: This is the first grounded theory study to explore VP design. This original research has produced a model which enhances understanding of how and why the delivery and design of VPs influence learning. The model may be of practical use to authors, institutions and researchers