A machine learning model to determine the accuracy of variant calls in capture-based next generation sequencing

Overview of attention for article published in BMC Genomics, April 2018

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In the top 25% of all research outputs scored by Altmetric
High Attention Score compared to outputs of the same age (87th percentile)
High Attention Score compared to outputs of the same age and source (96th percentile)

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twitter: 21 X users

patent: 3 patents

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So far, Altmetric has seen 3 patents that reference this research output.

PISEQ DEVICE AND ALGORITHM FOR DISTINGUISHING TRUE POSITIVE VARIATION AND FALSE POSITIVE…

Application WO-2023214620-A1

World Intellectual Property Organisation (WIPO)

GENETIC INFORMATION PROCESSING SYSTEM WITH UNBOUNDED-SAMPLE ANALYSIS MECHANISM AND METHOD…

Application WO-2023154937-A1

World Intellectual Property Organisation (WIPO)

MACHINE-LEARNING MODEL FOR GENERATING CONFIDENCE CLASSIFICATIONS FOR GENOMIC COORDINATES

Application WO-2023278966-A1

World Intellectual Property Organisation (WIPO)

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