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The sequences were analyzed using an automated mutation detection pipeline developed by the MSKCC Bioinformatics Core.
The dedicated infrastructure we have developed for fully automated mutation impact extraction from unstructured text has a respectable level of precision of 0.86, albeit with moderate recall.
Mutations were identified using an automated mutation caller and then verified manually with comparison made to the matched normal sequence in the case of all primary tumor samples.
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An automated mutation-calling algorithm was performed to identify candidate mutations and putative mutations were further filtered by a manual review.
The possibilities for ingenious new kinds of analyses, transformations, and maybe even automated mutations of workflows provoke the imagination.
Next, an automated mutation-calling algorithm was performed to identify candidate mutations.
Anbalagan and Xie [13] automated two pointcut-related mutation operators defined by Mortensen and Alexander [9].
Jho et al. [ 41] have developed a data deposition system integrated with automated bioinformatics tools for mutation detection and analysis starting from raw patient data.
To do so, researchers led by synthetic biologist George Church of Harvard University came up with a new, high-speed technique called multiplexed automated genome engineering for targeting mutations.
Our methodology can be automated to annotate and classify mutations in any protein family.
Genetic testing to identify deleterious BRCA1 and BRCA2 mutations included direct automated sequencing on the entire coding sequence.
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