34 research outputs found

    Rh alleles and phenotypes among Saudi women in Hail Region, Saudi Arabia

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    Background: The Rh system is considered as the most complex among the human blood group systems, with 61 antigens identified to date. This study aimed to provide preliminary data on the distribution of Rh alleles and phenotypes among Saudi women and compare them with other ethnic groups.Methods: This retrospective cross-sectional study was conducted among Saudi women who visited the Maternity and Children Hospital of Hail from November 2019 to March 2020. A fully automated blood bank analyzer was used in determining the Rh subgroups (D, C, c, E, e) and phenotypes. Inferential statistics and chi-square tests were used appropriately for comparisons.Results: The study included a total of 500 Saudi female patients. The most prevalent antigen found was the “e” antigen, while phenotype CcDee has shown to have the highest frequency. A significant difference exists in comparison with the other studies from various ethnic groups.Conclusions: The prevalence and distributions of Rh alleles and phenotypes among Saudi women were revealed in this study. The findings showed that Rh alleles and phenotypes are diverse across various races and regions globally.Keywords: Rh allele; Rh phenotype; Rh system; Saudi Arabi

    Galaxy Integrated Omics:Web-based standards-compliant workflows for proteomics informed by transcriptomics

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    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

    The mzTab data exchange format: communicating mass-spectrometry-based proteomics and metabolomics experimental results to a wider audience.

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    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

    Social personalized e-learning framework

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    This thesis discusses the topic of how to improve adaptive and personalized e-learning in order to provide novel learning experiences. A recent literature review revealed that adaptive and personalized e-learning systems are not widely used. There is a lack of interoperability between adaptive systems and learning management systems, in addition to limited collaborative and social features. First of all, this thesis investigates the interoperability issue via two case studies. The first case study focuses on how to achieve interoperability between adaptive systems and learning management systems using e-learning standards and the second case study focuses on how to augment e-learning standards with adaptive features. Secondly, this thesis proposes a new social framework for personalized e-learning, in order to provide adaptive and personalized e-learning platforms with new social features. This is not just about creating learning content, but also about developing new ways of learning. For instance, in the presented vision, adaptive learning does not refer to individuals only, but also to groups. Furthermore, the boundaries between authors and learners become less distinct in the Web 2.0 context. Finally, a new social personalized prototype is introduced based on the new social framework for personalized e-learning in order to test and evaluate this framework. The implementation and evaluation of the new system were carried out through a number of case studies

    Interoperability between MOT and learning management systems : converting CAF to IMS QTI and IMS CP

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    The chain of applying adaptivity to Learning Management Systems (LMS) is still deficient; there is a gap between authoring adaptive materials and delivering them in LMS. In this paper, we extend My Online Teacher (MOT), an adaptive authoring system, by adding compatibility with IMS Question & Test Interoperability (QTI) and IMS Content Packaging (CP). Thus, the authors can utilize the authored materials for learning process adaptation on any standards-compatible LMS. From a technical perspective, we initialize the creation of adaptive LMS by converting Common Adaptation Format (CAF), XML representation of MOT database, into IMS QTI and IMS CP, to ensure a wider uptake and use of adaptive learning systems. Finally, this work represents a significant step towards the little explored avenue of adaptive collaborative systems based on extant learning standards and popular LMS
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