6 results on '"Mamana Mbiyavanga"'
Search Results
2. The H3ABioNet helpdesk: an online bioinformatics resource, enhancing Africa’s capacity for genomics research
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Judit Kumuthini, Lyndon Zass, Sumir Panji, Samson P. Salifu, Jonathan K. Kayondo, Victoria Nembaware, Mamana Mbiyavanga, Ajayi Olabode, Ali Kishk, Gordon Wells, Nicola J. Mulder, and as members of the Sustainability and Outreach Work Package of the H3ABioNet Consortium
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Bioinformatics support ,Genomics support ,H3Africa ,H3ABioNet ,Helpdesk ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Biology (General) ,QH301-705.5 - Abstract
Abstract Background Currently, formal mechanisms for bioinformatics support are limited. The H3Africa Bioinformatics Network has implemented a public and freely available Helpdesk (HD), which provides generic bioinformatics support to researchers through an online ticketing platform. The following article reports on the H3ABioNet HD (H3A-HD)‘s development, outlining its design, management, usage and evaluation framework, as well as the lessons learned through implementation. Results The H3A-HD evaluated using automatically generated usage logs, user feedback and qualitative ticket evaluation. Evaluation revealed that communication methods, ticketing strategies and the technical platforms used are some of the primary factors which may influence the effectivity of HD. Conclusion To continuously improve the H3A-HD services, the resource should be regularly monitored and evaluated. The H3A-HD design, implementation and evaluation framework could be easily adapted for use by interested stakeholders within the Bioinformatics community and beyond.
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- 2019
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3. Developing reproducible bioinformatics analysis workflows for heterogeneous computing environments to support African genomics
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Shakuntala Baichoo, Yassine Souilmi, Sumir Panji, Gerrit Botha, Ayton Meintjes, Scott Hazelhurst, Hocine Bendou, Eugene de Beste, Phelelani T. Mpangase, Oussema Souiai, Mustafa Alghali, Long Yi, Brian D. O’Connor, Michael Crusoe, Don Armstrong, Shaun Aron, Fourie Joubert, Azza E. Ahmed, Mamana Mbiyavanga, Peter van Heusden, Lerato E. Magosi, Jennie Zermeno, Liudmila Sergeevna Mainzer, Faisal M. Fadlelmola, C. Victor Jongeneel, and Nicola Mulder
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Workflows ,Pipeline ,Bioinformatics ,Africa ,Genomics ,Docker ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Biology (General) ,QH301-705.5 - Abstract
Abstract Background The Pan-African bioinformatics network, H3ABioNet, comprises 27 research institutions in 17 African countries. H3ABioNet is part of the Human Health and Heredity in Africa program (H3Africa), an African-led research consortium funded by the US National Institutes of Health and the UK Wellcome Trust, aimed at using genomics to study and improve the health of Africans. A key role of H3ABioNet is to support H3Africa projects by building bioinformatics infrastructure such as portable and reproducible bioinformatics workflows for use on heterogeneous African computing environments. Processing and analysis of genomic data is an example of a big data application requiring complex interdependent data analysis workflows. Such bioinformatics workflows take the primary and secondary input data through several computationally-intensive processing steps using different software packages, where some of the outputs form inputs for other steps. Implementing scalable, reproducible, portable and easy-to-use workflows is particularly challenging. Results H3ABioNet has built four workflows to support (1) the calling of variants from high-throughput sequencing data; (2) the analysis of microbial populations from 16S rDNA sequence data; (3) genotyping and genome-wide association studies; and (4) single nucleotide polymorphism imputation. A week-long hackathon was organized in August 2016 with participants from six African bioinformatics groups, and US and European collaborators. Two of the workflows are built using the Common Workflow Language framework (CWL) and two using Nextflow. All the workflows are containerized for improved portability and reproducibility using Docker, and are publicly available for use by members of the H3Africa consortium and the international research community. Conclusion The H3ABioNet workflows have been implemented in view of offering ease of use for the end user and high levels of reproducibility and portability, all while following modern state of the art bioinformatics data processing protocols. The H3ABioNet workflows will service the H3Africa consortium projects and are currently in use. All four workflows are also publicly available for research scientists worldwide to use and adapt for their respective needs. The H3ABioNet workflows will help develop bioinformatics capacity and assist genomics research within Africa and serve to increase the scientific output of H3Africa and its Pan-African Bioinformatics Network.
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- 2018
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4. Assessing computational genomics skills: Our experience in the H3ABioNet African bioinformatics network.
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C Victor Jongeneel, Ovokeraye Achinike-Oduaran, Ezekiel Adebiyi, Marion Adebiyi, Seun Adeyemi, Bola Akanle, Shaun Aron, Efejiro Ashano, Hocine Bendou, Gerrit Botha, Emile Chimusa, Ananyo Choudhury, Ravikiran Donthu, Jenny Drnevich, Oluwadamila Falola, Christopher J Fields, Scott Hazelhurst, Liesl Hendry, Itunuoluwa Isewon, Radhika S Khetani, Judit Kumuthini, Magambo Phillip Kimuda, Lerato Magosi, Liudmila Sergeevna Mainzer, Suresh Maslamoney, Mamana Mbiyavanga, Ayton Meintjes, Danny Mugutso, Phelelani Mpangase, Richard Munthali, Victoria Nembaware, Andrew Ndhlovu, Trust Odia, Adaobi Okafor, Olaleye Oladipo, Sumir Panji, Venesa Pillay, Gloria Rendon, Dhriti Sengupta, and Nicola Mulder
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Biology (General) ,QH301-705.5 - Abstract
The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so.
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- 2017
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5. 'Broadband' Bioinformatics Skills Transfer with the Knowledge Transfer Programme (KTP): Educational Model for Upliftment and Sustainable Development.
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Emile R Chimusa, Mamana Mbiyavanga, Velaphi Masilela, and Judit Kumuthini
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Biology (General) ,QH301-705.5 - Abstract
A shortage of practical skills and relevant expertise is possibly the primary obstacle to social upliftment and sustainable development in Africa. The "omics" fields, especially genomics, are increasingly dependent on the effective interpretation of large and complex sets of data. Despite abundant natural resources and population sizes comparable with many first-world countries from which talent could be drawn, countries in Africa still lag far behind the rest of the world in terms of specialized skills development. Moreover, there are serious concerns about disparities between countries within the continent. The multidisciplinary nature of the bioinformatics field, coupled with rare and depleting expertise, is a critical problem for the advancement of bioinformatics in Africa. We propose a formalized matchmaking system, which is aimed at reversing this trend, by introducing the Knowledge Transfer Programme (KTP). Instead of individual researchers travelling to other labs to learn, researchers with desirable skills are invited to join African research groups for six weeks to six months. Visiting researchers or trainers will pass on their expertise to multiple people simultaneously in their local environments, thus increasing the efficiency of knowledge transference. In return, visiting researchers have the opportunity to develop professional contacts, gain industry work experience, work with novel datasets, and strengthen and support their ongoing research. The KTP develops a network with a centralized hub through which groups and individuals are put into contact with one another and exchanges are facilitated by connecting both parties with potential funding sources. This is part of the PLOS Computational Biology Education collection.
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- 2015
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6. Assessing computational genomics skills: Our experience in the H3ABioNet African bioinformatics network
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Shaun Aron, Mamana Mbiyavanga, Lerato E Magosi, Efejiro Ashano, Christopher J. Fields, C. Victor Jongeneel, Danny Mugutso, Phelelani T. Mpangase, Sumir Panji, Venesa Pillay, Seun Adeyemi, Adaobi Okafor, Oluwadamila Falola, Hocine Bendou, Ananyo Choudhury, Olaleye Oladipo, Ezekiel Adebiyi, Radhika S. Khetani, Ovokeraye Achinike-Oduaran, Bola Akanle, Richard J. Munthali, Suresh Maslamoney, Ayton Meintjes, Gloria Rendon, Nicola Mulder, Trust Odia, Andrew Ndhlovu, Ravikiran Donthu, Itunuoluwa Isewon, Liesl M. Hendry, Emile R. Chimusa, Jenny Drnevich, Judit Kumuthini, Magambo Phillip Kimuda, Scott Hazelhurst, Liudmila Sergeevna Mainzer, Marion O. Adebiyi, Victoria Nembaware, Dhriti Sengupta, and Gerrit Botha
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0301 basic medicine ,Service (systems architecture) ,Computer science ,Data management ,Social Sciences ,Bioinformatics ,Database and Informatics Methods ,South Africa ,Sociology ,Databases, Genetic ,Medicine and Health Sciences ,Public and Occupational Health ,Biology (General) ,Ecology ,Health services research ,Genomics ,Research Assessment ,Sports Science ,3. Good health ,Test (assessment) ,Professions ,Computational Theory and Mathematics ,Modeling and Simulation ,Workshops ,Health Services Research ,QH301-705.5 ,Process (engineering) ,Developing country ,Black People ,Nigeria ,Research and Analysis Methods ,Education ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Genome-Wide Association Studies ,Genetics ,Humans ,Sports and Exercise Medicine ,Molecular Biology ,Exercise ,Developing Countries ,Ecology, Evolution, Behavior and Systematics ,business.industry ,Computational genomics ,Biology and Life Sciences ,Computational Biology ,Human Genetics ,Physical Activity ,Genome Analysis ,Data science ,Health Care ,030104 developmental biology ,Physical Fitness ,People and Places ,Scientists ,Database Management Systems ,Population Groupings ,business - Abstract
The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so., Author summary Many programs have been developed to boost the technical and computational skills of scientists working in low to medium income countries (LMIC), who often struggle to remain competitive with their peers in more developed parts of the world. Typically, these programs rely on intensive workshops where students acquire and exercise these skills under the supervision of experienced trainers. However, when trainees return to their home institutions, even after extensive exposure to state of the art techniques, they often find it difficult to put the skills they have acquired into practice and to establish themselves as fully independent practitioners. We have attempted to build a framework through which teams of scientists in African research groups can demonstrate that they have acquired the necessary skills to analyze different types of genomic datasets. Three teams of scientists who have successfully submitted to this assessment exercise report their positive experiences. Many potential participants have so far declined the opportunity, and we discuss the reasons for their reluctance as well as possible ways to facilitate their engagement and provide them with incentives. We argue that assessments such as this could be part of any program aiming to develop technical skills in scientists wishing to support genomic research programs.
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- 2017
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