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Elucidating the role and use of bioinformatics software in life science research

Published: 13 July 2015 Publication History

Abstract

Life science research requires critical evaluation of data handling and analytical software usability. We present the results of semi-structured interviews which provide insight into the effects of bioinformatics software usability on life science research. Results from our study confirm much of the prior anecdotal evidence of standalone bioinformatics software usability. More importantly, we show that usability issues and life scientists' lack of expertise in applying computational methods to biological research is limiting their research objectives and contributing to researchers' reliance on computational experts to conduct their research.

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Andrew Brooks

Genome-based research involves large teams of specialists and the use of complex software tools to perform analysis. To better understand the problems associated with using bioinformatics software, ten life science researchers were interviewed. Questions were asked about the goals of their research, the workflows they used, and the tools they used. Participants were also asked to walk through specific examples of how they conducted recent research. Interview materials and photographs of work artifacts were analyzed using the affinity diagram approach. The life science researchers were found to treat their tools almost as black boxes. Without adequate knowledge of the underlying algorithms being used, they resorted to a variety of strategies to select the values of input parameters. For example, one strategy was to begin with default settings and then use a trial-and-error approach. Several of them were found to use both digital and physical notes to keep records of the command-line sequences required when working with Linux-based tools. Other researchers chose to purchase commercial genomics workbenches to reduce the need for command-line skills. A priority for any project was access to bioinformatics experts. If this could not be obtained, some of the life science researchers indicated that this restricted their inquiries to those that they themselves were comfortable answering using their existing tools. A major limitation of this study, as recognized by the authors, was the small sample size. Nevertheless, several important issues have been exposed. This paper is recommended to genomics researchers and developers of bioinformatics software. Online Computing Reviews Service

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Published In

cover image ACM Other conferences
British HCI '15: Proceedings of the 2015 British HCI Conference
July 2015
334 pages
ISBN:9781450336437
DOI:10.1145/2783446
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 13 July 2015

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Author Tags

  1. bioinformatics software
  2. data-driven research
  3. qualitative study

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  • Research-article

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British HCI 2015
British HCI 2015: 2015 British Human Computer Interaction Conference
July 13 - 17, 2015
Lincolnshire, Lincoln, United Kingdom

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British HCI '15 Paper Acceptance Rate 28 of 62 submissions, 45%;
Overall Acceptance Rate 28 of 62 submissions, 45%

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  • (2023)Protecting Autonomous Cars from Phantom AttacksCommunications of the ACM10.1145/355230866:4(56-69)Online publication date: 23-Mar-2023
  • (2023)Cyber Efficiency and Cyber ResilienceCommunications of the ACM10.1145/354907366:4(33-37)Online publication date: 23-Mar-2023
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