Difference between revisions of "Template:Article of the week"

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(Updated article of the week text.)
(Updated article of the week text.)
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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Backman BMCBio2016 17.gif|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Irawan ResIdeasOut2018 4.png|240px]]</div>
'''"[[Journal:systemPipeR: NGS workflow and report generation environment|systemPipeR: NGS workflow and report generation environment]]"'''
'''"[[Journal:Promoting data sharing among Indonesian scientists: A proposal of a generic university-level research data management plan (RDMP)|Promoting data sharing among Indonesian scientists: A proposal of a generic university-level research data management plan (RDMP)]]"'''


Next-generation sequencing (NGS) has revolutionized how research is carried out in many areas of biology and medicine. However, the analysis of NGS data remains a major obstacle to the efficient utilization of the technology, as it requires complex multi-step processing of big data, demanding considerable computational expertise from users. While substantial effort has been invested on the development of software dedicated to the individual analysis steps of NGS experiments, insufficient resources are currently available for integrating the individual software components within the widely used R/Bioconductor environment into automated [[Workflow|workflows]] capable of running the analysis of most types of NGS applications from start-to-finish in a time-efficient and reproducible manner. ('''[[Journal:systemPipeR: NGS workflow and report generation environment|Full article...]]''')<br />
Every researcher needs data in their working ecosystem, but despite the resources (funding, time, and energy) they have spent to get the data, only a few are putting more real attention into [[Information management|data management]]. This paper mainly describes our recommendation of a research data management plan (RDMP) at the university level. This paper is an extension of our initiative, to be developed at the university or national level, while also in-line with current developments in scientific practices mandating data sharing and data re-use. Researchers can use this article as an assessment form to describe the setting of their research and data management. Researchers can also develop a more detailed RDMP to cater to a specific project's environment. ('''[[Journal:Promoting data sharing among Indonesian scientists: A proposal of a generic university-level research data management plan (RDMP)|Full article...]]''')<br />
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Revision as of 18:12, 1 November 2018

Fig1 Irawan ResIdeasOut2018 4.png

"Promoting data sharing among Indonesian scientists: A proposal of a generic university-level research data management plan (RDMP)"

Every researcher needs data in their working ecosystem, but despite the resources (funding, time, and energy) they have spent to get the data, only a few are putting more real attention into data management. This paper mainly describes our recommendation of a research data management plan (RDMP) at the university level. This paper is an extension of our initiative, to be developed at the university or national level, while also in-line with current developments in scientific practices mandating data sharing and data re-use. Researchers can use this article as an assessment form to describe the setting of their research and data management. Researchers can also develop a more detailed RDMP to cater to a specific project's environment. (Full article...)

Recently featured:

systemPipeR: NGS workflow and report generation environment
A data quality strategy to enable FAIR, programmatic access across large, diverse data collections for high performance data analysis
How big data, comparative effectiveness research, and rapid-learning health care systems can transform patient care in radiation oncology