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MEMBERSHIP

REVIEW OF MILESTONES FOR YEAR 1 AND UPCOMING MILESTONES FOR YEAR 2 – RESEARCH AND TOOL DEVELOPMENT WORKING GROUP (JULIE MAKANI AND EZEKIEL ADEBIYI). MEMBERSHIP. RTDWG members breakdown by Countries. Further Information. Number of meetings: 9 First meeting: 19 Feb.

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MEMBERSHIP

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  1. REVIEW OF MILESTONES FOR YEAR 1 AND UPCOMING MILESTONES FOR YEAR 2 – RESEARCH AND TOOL DEVELOPMENT WORKING GROUP (JULIE MAKANI AND EZEKIEL ADEBIYI)

  2. MEMBERSHIP

  3. RTDWG members breakdown by Countries

  4. Further Information • Number of meetings: 9 • First meeting: 19 Feb.

  5. Key to Milestone Tables E = Education & Training Working Group I = Infrastructure Working Group R = Research and Tool Development Working Group N = Node Accreditation Working Group SP = Specific Project partners C = Central ALL = All working groups

  6. FOUNDATIONCOLLABORATIVE PROJECTS MILESTONES H3ABioNet 2nd Annual Meeting 2013

  7. FOUNDATIONCOLLABORATIVE PROJECTS MILESTONES

  8. FOUNDATIONCOLLABORATIVE PROJECTS MILESTONES

  9. Summary of key Foundation Collaborative Projects

  10. FIRST YEAR COLLABORATIVE PROJECTS • Network Capacity Database (NetCapDB) an innovative tool to monitor H3ABioNet Capacity development • The SNP Analysis Platform (SNAP) • Design of Phenotype Database and Surveillance Programme for Epidemiology of Sickle Cell Disease (SCD) in Tanzania • Human metabolic network modelling: contextualization of H3Africa projects high throughput data from pathological and drug-treated states and simulation of these states • Visual Analytical Screening System for Disease Linked Gene Variants • A Knowledge Transfer Programme (KTP) for sustainable Bioinformatics capacity development in Africa • Determination of European Genome phenome Archive Data submission process • Investigation into current Cloud, High Performance and Grid Computing resources available. • Surveillance Programme of IN – patients and Epidemiology (SPINE) for Sickle Cell Disease (SCD) of East African Populations • Design and Implementation of a Sickle Cell Disease (SCD) database and Analysis modules • Molecular Mechanism of Action of the Anti-Sickling Potential of Solenostemon monostachyus in Sickle Cell Dieseased Mice

  11. ? • Collaborative Project Templates- available • Milestones (schedules of execution)

  12. NetCapBD: An innovative tool to monitor activities in the H3ABioNet networK • H3ABioNet launched an ambitious project by developing a Network Capacity Database (NetCapDB), a comprehensive database-oriented tool for monitoring capacity building activities taking place within H3ABioNet. Although NetCapDB has been primarily designed to monitor and assess capacity development within H3ABioNet, it would potentially suit other capacity building projects. Individual Nodes of H3ABioNet (scaling from small emerging research groups to larger institutes) are responsible for entering their own data within carefully planned categories .The entered data are stored in a complex MySQL database comprising of 126 tables with a cumulative total of 1,067 fields. Data will then be retrieved and processed through MySQL queries in order to generate accurate and rich reports made out of raw or synthetic figures, graphics and maps of Africa representing all the aspects of sustainable capacity building within the H3ABioNet initiative ranging from increased research output to strengthened education and training activities, as well as steady growth in terms of personnel and computing/educational infrastructure. The reports generated will be useful not only to the H3ABioNet Nodes themselves, but also to the H3ABioNet Scientific Advisory Body (SAB), the Management Committee (MC) and for each Nodes’ annual report to the NIH providing them with an objective and comprehensive activities assessment as an input to the decision-making process about where and for which projects should funding go.

  13. The SNP Analysis Platform (SNAP) • SNAP is a web-based workflow management system that is currently under development by the Rhodes University Bioinformatics (RUBi) research group. It will provide a range of bioinformatics tools that will initially target homology modeling and SNP analysis. Being a workflow management system, SNAP will provide users with the ability to string multiple tools together in complex, non-linear pipelines. Users can then save these pipelines (or workflows) for future use. With the initial goal being homology modeling and SNP analysis, the proposed initial categories are currently Template Selection, Sequence Alignment, Homology Modeling, Model Validation, Energy Analysis, SNP Analysis (which will include tools to fetch SNP data and map SNPs to three dimensional models of proteins), Visualization, and Data Manipulation. Amongst other things, these tools will allow proteins with unknown structures to be modeled, SNPs to be mapped to a location on the protein structure, stability and energy analysis to be carried out to determine whether an amino acid change caused by a SNP might destabilize the protein, and Genome Wide Association Studies.

  14. Development of a Grid-based tool for data storage and sharing. • This aims to develop a web service that allows the secure, auditable and reliable storage of such data using grid technology. This web service will be tailored for wet-lab scientists and will required limited technical knowhow whilst allowing collaboration and data sharing between project members across multiple sites to occur. The European Grid Initiative (EGI) has made Science Gateways (SG) a major part of its vision to increase usage of grid systems worldwide. A SG is a web interface that allows users access to the underlying grid resources and services, hiding the complexities of interacting with the grid from the end users. The implementation of a Science Gateway using the CSG engine will be useful for the H3Africa project.

  15. Design of Phenotype Database and Surveillance Programme for Epidemiology of Sickle Cell Disease (SCD) in Tanzania • Phenotypic information for a cohort of >6000 Sickle Cell disease (SCD) patients and non-SCD individuals is currently stored in the Muhimbili Sickle Cell (MSC) database. The data consist of demographic (age, geographical residence), clinical (symptoms, physical signs), laboratory and physiological data collected from multiple case report forms (CRF) and diagnostic devices. Genotype data on 1,300 SCD individuals, generated from GWAS and NGS, is stored at Wellcome Trust Sanger Institute. The MSC database needs to store and manage patients' data for healthcare as well as research, including genotype-phenotype association studies. The current structure of the database does not support functionality for healthcare, flexible querying capability and genetic research. The setting up of a well-structured SCD database will enable easy incorporation and flexible end-user queries. This will be the first platform developed through pan-African collaboration and will form the basis for existing and future SCD healthcare needs and research.

  16. Human metabolic network modelling: contextualization of H3Africa projects high throughput data from pathological and drug-treated states and simulation of these states • A computational method (Choke Point Analysis (CPA)) investigating the topology of biochemical metabolic networks was developed to mine new viable enzymatic drug targets in the most deadly malaria parasite, Plasmodium falciparum. Initial drug screening in in-vitro antiplasmodial assay experiments have been performed against the predicted drug targets. This work may produce novel antimalarial drugs, whose biological mode of action can be determined accurately and provides another antimalarial drug target site upon which a viable structural design pipeline is currently being constructed. One important database for P. falciparumthat has proved useful in the previous works above is its biochemical metabolic network. Based on this network, the computational analysis of Anopheles gambiaemetabolism to facilitate insecticidal target and resistance mechanism discovery is imperative. This will lead to the possibilty of constructing computational analysis using several human metabolic networks (HMNs) for affected human cells/tissues of the H3Africa diseases of consideration.

  17. Implementation of a Visual Analytical Screening System for Disease Linked Gene Variants • An identified challenge faced by African researchers is the limited availability of computational tools and curated datasets to enable visual discovery (exploration, mining and analysis via visual interfaces) of bioinformatics results from high-quality genomics research. This need was based on recommendations by participants in the H3Africa Bioinformatics Network sponsored Visual Analytics Training Workshop held in July 2013 in Abuja. The long-term goal of this project is to develop a web-based pipeline repository of curated datasets on molecular consequences of gene variants and gene-toxicant interactions for human gene families. Along with visual discovery tools, researchers will be able to make sense of large-scale molecular and clinical datasets to support decision-making on genetic and environmental determinants of cardiometabolic diseases in Africa. An example of visual analytical system developed for genes variants linked to blood lipids is available at: http://public.tableausoftware.com/views/bloodlipids/bloodlipids_dashboard/

  18. A Knowledge Transfer Programme for sustainable Bioinformatics capacity development in Africa • Typically, when scientists in Africa plan to acquire new skills, especially involving recently developed techniques at the forefront of their research domain, individuals are sent overseas to acquire these skills in a properly resourced environment. This project is a systematic yet customizable approach to building capacity in Africa in a more sustainable fashion, called the Knowledge Transfer Programme (KTP). This model is built on the premise that researchers with desirable skills are invited to join local research groups for 6 weeks to 6 months, instead of individual researchers travelling to overseas destinations for training. Visiting experts will pass on their skills and knowledge to multiple people simultaneously. This increases the efficiency of the concomitant knowledge transfer, within the context of a specific project. The long term benefits include acquisition of knowledge and the creation of a pool of local experts who can in turn amplify this knowledge in Africa.

  19. Determination of European Genome phenome Archive Data submission process • A lot of the H3Africa data will have to be ultimately deposited into public repositories with the European Genome-phenome Archive (EGA :https://www.ebi.ac.uk/ega/ )being the repository of choice by the H3A consortium.Determining what the submission process entails, the data types and file format requirements, the quality control annotation process and pre-processing of the submission data, what potential bottlenecks maybe encountered and attachment of tentative timelines to these steps is vital for any strategic planning in terms of resource allocation and experimental planning. The anticipated outcomes will be a working document that highlights the key EGA submission process steps, the data files and formats required for each step, the anticipated time line for each step to be completed and the processing steps required by H3ABioNet for submitting these data. This documentation can be used to help plan experimental data generation, management, quality control checking, transfer, pre and post processing, analysis and submission periods for H3Africa data generated.

  20. Investigation into current Cloud, High Performance and Grid Computing resources available. • The aim of the project is to conduct a pilot survey of what resources in terms of cloud, high performance computing and grid computing resources are available to Africa in general and South Africa specifically for biomedical research. The proposed project will identify such resources, document their location and availability, ease of access and use as well as their suitability for different purposes such as processing, storage and computing specifically aimed at bioinformatics and for use with H3Africa data.The anticipated outcomes will be a detailed report that can be shared with the rest of the H3Africa consortium and H3ABioNet as to what each type of computing architecture comprises of, their availability, location, ease of use / implementation and suitability for bioinformatics research.

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