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1.
BMC Bioinformatics ; 22(1): 543, 2021 Nov 08.
Artigo em Inglês | MEDLINE | ID: mdl-34749640

RESUMO

BACKGROUND: Clinical diagnostics of whole-exome and whole-genome sequencing data requires geneticists to consider thousands of genetic variants for each patient. Various variant prioritization methods have been developed over the last years to aid clinicians in identifying variants that are likely disease-causing. Each time a new method is developed, its effectiveness must be evaluated and compared to other approaches based on the most recently available evaluation data. Doing so in an unbiased, systematic, and replicable manner requires significant effort. RESULTS: The open-source test bench "VPMBench" automates the evaluation of variant prioritization methods. VPMBench introduces a standardized interface for prioritization methods and provides a plugin system that makes it easy to evaluate new methods. It supports different input data formats and custom output data preparation. VPMBench exploits declaratively specified information about the methods, e.g., the variants supported by the methods. Plugins may also be provided in a technology-agnostic manner via containerization. CONCLUSIONS: VPMBench significantly simplifies the evaluation of both custom and published variant prioritization methods. As we expect variant prioritization methods to become ever more critical with the advent of whole-genome sequencing in clinical diagnostics, such tool support is crucial to facilitate methodological research.


Assuntos
Variação Genética , Software , Exoma , Humanos , Sequenciamento do Exoma
2.
Annu Int Conf IEEE Eng Med Biol Soc ; 2019: 3377-3382, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31946605

RESUMO

The reproducibility of scientific results gains increasing attention. In the context of biomedical engineering, this applies to experimental studies of three different kinds: in-vivo, in-vitro, and in-silico. Numerical modelling and finite element simulation of bio-electric systems are intricate processes involving manifold steps. A typical example of this process is the electrical stimulation at alloplastic reconstruction plates of the mandible. During the bio-electric modelling and simulation process, diverse methods realised in various software tools are exploited. To comprehensibly render how the final model has been developed requires a thorough documentation. We exploit the W3C provenance model PROV to structure this process and to make it accessible for modellers and for automatic analyses. Different entity types, such as data, model, software, literature, assumptions, and mathematical equations are distinguished; roles of entities within an activity are revealed as well as the involved researchers. In addition, we identify five process patterns: 1) information extraction from the literature; 2) generation of a geometrical model which uses data as input; 3) composition of several geometrical or mathematical models into a combined model; 4) parameterisation, which augments the input model by additional properties; and, finally, 5) refinement, which uses a model in addition to an assumption and generates an enhanced model. By modelling provenance information of a typical bio-electric modelling and simulation process as well as identifying provenance patterns, we provide a first step towards a better documentation of academic investigations in that scientific field.


Assuntos
Simulação por Computador , Eletricidade , Análise de Elementos Finitos , Software , Estimulação Elétrica , Humanos , Mandíbula , Modelos Teóricos , Reprodutibilidade dos Testes
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