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, 71 (2), 136-146

Biocompute Objects-A Step Towards Evaluation and Validation of Biomedical Scientific Computations

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Biocompute Objects-A Step Towards Evaluation and Validation of Biomedical Scientific Computations

Vahan Simonyan et al. PDA J Pharm Sci Technol.

Abstract

The unpredictability of actual physical, chemical, and biological experiments due to the multitude of environmental and procedural factors is well documented. What is systematically overlooked, however, is that computational biology algorithms are also affected by multiplicity of parameters and have no lesser volatility. The complexities of computation protocols and interpretation of outcomes is only a part of the challenge: There are also virtually no standardized and industry-accepted metadata schemas for reporting the computational objects that record the parameters used for computations together with the results of computations. Thus, it is often impossible to reproduce the results of a previously performed computation due to missing information on parameters, versions, arguments, conditions, and procedures of application launch. In this article we describe the concept of biocompute objects developed specifically to satisfy regulatory research needs for evaluation, validation, and verification of bioinformatics pipelines. We envision generalized versions of biocompute objects called biocompute templates that support a single class of analyses but can be adapted to meet unique needs. To make these templates widely usable, we outline a simple but powerful cross-platform implementation. We also discuss the reasoning and potential usability for such concept within the larger scientific community through the creation of a biocompute object database initially consisting of records relevant to the U.S. Food and Drug Administration. A biocompute object database record will be similar to a GenBank record in form; the difference being that instead of describing a sequence, the biocompute record will include information related to parameters, dependencies, usage, and other information related to specific computational instance. This mechanism will extend similar efforts and also serve as a collaborative ground to ensure interoperability between different platforms, industries, scientists, regulators, and other stakeholders interested in biocomputing.

Keywords: Biocompute object; Computation reproducibility; FDA; NGS standardization; Regulatory research.

Conflict of interest statement

Competing Interests: The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
An experiment can be viewed as a black box that takes specific inputs under an established set or range of conditions and has predetermined outputs that are generated. A sample program command line is shown with generic terms covering the input, parameters, and output for the computation to emphasize the analogy of generalized experiment concept. Note: The image has been adapted from Pixabay released under Creative Commons CC0. No attribution or permission is required (https://pixabay.com/en/chemistry-distillationexperiment-161575/).
Figure 2
Figure 2
Visualization of an experimental procedure. The results are dependent on input, parameters and experimental methods, protocol, and instance.
Figure 3
Figure 3
Illustration of an experimental protocol that will have a specific set of input and output domains.
Figure 4
Figure 4
Illustration of validity domains of a pipeline in three dimensions. The parametric space (3 axis) in this case is expansive, but only a small subset represented by the dark blue shapes are valid in the pipeline. Parameters that fall outside of these areas are not within the scope of the pipeline and not guaranteed to result in usable outputs.
Figure 5
Figure 5
A visual description of the biocompute object that a user would create and upload into the Biocompute Database. The figure provides a view of how a biocompute object encapsulates workflow, pipeline, parametric domain instance, input domain, and output domain.

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