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Methodology capture: discriminating between the "best" and the rest of community practice.

Eales JM, Pinney JW, Stevens RD, Robertson DL - BMC Bioinformatics (2008)

Bottom Line: We have identified a structured community of phylogenetic researchers performing analyses that are customary in their own local community and significantly different from those in other areas.We propose that the practice of expert authors from the field of evolutionary biology is the closest to contemporary best practice in phylogenetic experimental design.Capturing best practice is, however, a complex task and should also acknowledge the differences between fields such as the specific context of the analysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Faculty of Life Sciences, University of Manchester, Manchester, UK. james.eales@postgrad.manchester.ac.uk

ABSTRACT

Background: The methodologies we use both enable and help define our research. However, as experimental complexity has increased the choice of appropriate methodologies has become an increasingly difficult task. This makes it difficult to keep track of available bioinformatics software, let alone the most suitable protocols in a specific research area. To remedy this we present an approach for capturing methodology from literature in order to identify and, thus, define best practice within a field.

Results: Our approach is to implement data extraction techniques on the full-text of scientific articles to obtain the set of experimental protocols used by an entire scientific discipline, molecular phylogenetics. Our methodology for identifying methodologies could in principle be applied to any scientific discipline, whether or not computer-based. We find a number of issues related to the nature of best practice, as opposed to community practice. We find that there is much heterogeneity in the use of molecular phylogenetic methods and software, some of which is related to poor specification of protocols. We also find that phylogenetic practice exhibits field-specific tendencies that have increased through time, despite the generic nature of the available software. We used the practice of highly published and widely collaborative researchers ("expert" researchers) to analyse the influence of authority on community practice. We find expert authors exhibit patterns of practice common to their field and therefore act as useful field-specific practice indicators.

Conclusion: We have identified a structured community of phylogenetic researchers performing analyses that are customary in their own local community and significantly different from those in other areas. Best practice information can help to bridge such subtle differences by increasing communication of protocols to a wider audience. We propose that the practice of expert authors from the field of evolutionary biology is the closest to contemporary best practice in phylogenetic experimental design. Capturing best practice is, however, a complex task and should also acknowledge the differences between fields such as the specific context of the analysis.

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Model of archetypal phylogenetic experiment. A model of the archetypal phylogenetic experiment with an example representation of a protocol in text form. Protocol elements are coloured according to their stage (1 to 4) in the model.
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Figure 1: Model of archetypal phylogenetic experiment. A model of the archetypal phylogenetic experiment with an example representation of a protocol in text form. Protocol elements are coloured according to their stage (1 to 4) in the model.

Mentions: The single largest source of phylogenetic and indeed scientific practice is journal literature. Because of the adherence to the scientific method and therefore the need to declare the methods used, each article describing original research should contain text relating to the methods employed. Our approach makes use of this practice resource by operating on the full-text of journal articles. We then search this text for terms that are significant in the description of phylogenetic experiments (see Figure 1 for example).


Methodology capture: discriminating between the "best" and the rest of community practice.

Eales JM, Pinney JW, Stevens RD, Robertson DL - BMC Bioinformatics (2008)

Model of archetypal phylogenetic experiment. A model of the archetypal phylogenetic experiment with an example representation of a protocol in text form. Protocol elements are coloured according to their stage (1 to 4) in the model.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2553348&req=5

Figure 1: Model of archetypal phylogenetic experiment. A model of the archetypal phylogenetic experiment with an example representation of a protocol in text form. Protocol elements are coloured according to their stage (1 to 4) in the model.
Mentions: The single largest source of phylogenetic and indeed scientific practice is journal literature. Because of the adherence to the scientific method and therefore the need to declare the methods used, each article describing original research should contain text relating to the methods employed. Our approach makes use of this practice resource by operating on the full-text of journal articles. We then search this text for terms that are significant in the description of phylogenetic experiments (see Figure 1 for example).

Bottom Line: We have identified a structured community of phylogenetic researchers performing analyses that are customary in their own local community and significantly different from those in other areas.We propose that the practice of expert authors from the field of evolutionary biology is the closest to contemporary best practice in phylogenetic experimental design.Capturing best practice is, however, a complex task and should also acknowledge the differences between fields such as the specific context of the analysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Faculty of Life Sciences, University of Manchester, Manchester, UK. james.eales@postgrad.manchester.ac.uk

ABSTRACT

Background: The methodologies we use both enable and help define our research. However, as experimental complexity has increased the choice of appropriate methodologies has become an increasingly difficult task. This makes it difficult to keep track of available bioinformatics software, let alone the most suitable protocols in a specific research area. To remedy this we present an approach for capturing methodology from literature in order to identify and, thus, define best practice within a field.

Results: Our approach is to implement data extraction techniques on the full-text of scientific articles to obtain the set of experimental protocols used by an entire scientific discipline, molecular phylogenetics. Our methodology for identifying methodologies could in principle be applied to any scientific discipline, whether or not computer-based. We find a number of issues related to the nature of best practice, as opposed to community practice. We find that there is much heterogeneity in the use of molecular phylogenetic methods and software, some of which is related to poor specification of protocols. We also find that phylogenetic practice exhibits field-specific tendencies that have increased through time, despite the generic nature of the available software. We used the practice of highly published and widely collaborative researchers ("expert" researchers) to analyse the influence of authority on community practice. We find expert authors exhibit patterns of practice common to their field and therefore act as useful field-specific practice indicators.

Conclusion: We have identified a structured community of phylogenetic researchers performing analyses that are customary in their own local community and significantly different from those in other areas. Best practice information can help to bridge such subtle differences by increasing communication of protocols to a wider audience. We propose that the practice of expert authors from the field of evolutionary biology is the closest to contemporary best practice in phylogenetic experimental design. Capturing best practice is, however, a complex task and should also acknowledge the differences between fields such as the specific context of the analysis.

Show MeSH