Life Technologies Corporation

Manjula Aliminati

David C Woo

Gordon A Janaway

David Fortescue

Ming Shen

Sylvia Chang

Ruoyun Wu

Stephanie Jo Schneider

David Denny

Siva Kumar Samsani

Yoke Peng Lim

Nivedita Sumi Majumdar

Harrison Leong

David Hoard

Thomas Wessel

Yong Chu

Levente Egry

Shakila Pothini

Kevin Papenfuss

Yongzhi Chen

Nivedita Majumbar

Salil Kumar

Pratik Simon Soares

Christopher Fong

A computer-implemented method of generating a digital polymerase chain reaction (dPCR) result is provided. The method includes detecting a first set of emission data from a plurality of samples, each included in a sample region of a plurality of sample regions, at a first time amplification during an amplification period. The method further includes determining a positive or negative amplification determination for each sample of the plurality of samples based in part on the first set of emission data. A dPCR result is generated based on the positive or negative amplification determinations for the plurality of samples.

Methods and systems for visualizing and evaluating data

A system and methods are provided for image driven quality control for array based PCR. The system comprises a PCR unit, a reaction array plate, a convolutional neural network (CNN) configured to receive a sequence of images of the reaction array plate in the PCR system, and an output of the CNN coupled to a control for the reaction array plate. The method comprises applying a sequence of images from a plurality of subarrays of the reaction array plate to a plurality of CNNs during operation of the PCR system on the reaction plate array, operating the CNNs to generate failure mode predictions for the reaction plate based on the sequence of images, and coupling an output of the CNNs to one or more of a setting for manufacture of the reaction array plate or to control the PCR system.

Image driven quality control for array-based PCR

A system for analyzing biological data, comprising: a storage configured to store a plurality of data files containing biological data obtained from a plurality of devices; a server configured to: host a plurality of applications, each configured to be implemented on the server and to provide analysis, manipulation, comparison, visualization, or a combination thereof, of the biological data included in the data files, wherein the plurality of applications allow a user to analyze different data files related to the same sample and compare the results of the analysis.

Methods and systems for knowledge discovery using biological data

In one exemplary embodiment, a method for detecting variants in electropherogram data is provided. The method includes receiving electropherogram data from an instrument and analyzing the electropherogram data to identify mixed bases in the electropherogram data. The method further includes validating the identified mixed bases. Then the method includes determining variants in the electropherogram data based on the validated mixed bases.

Methods and systems for variant detection

A computer-implemented method of generating a digital polymerase chain reaction (dPCR) result is provided. The method includes detecting a first set of emission data from a plurality of samples, each included in a sample region of a plurality of sample regions, at a first time during an amplification period. The method further includes determining a positive or negative amplification determination for each sample of the plurality of samples based in part on the first set of emission data. A dPCR result is generated based on the positive or negative amplification determinations for the plurality of samples.

In one exemplary embodiment, a method for detecting variants in electropherogram data is provided. The method includes receiving electropherogram data from an instrument and analyzing the electropherogram data to identify mixed bases in the electropherogram data. The method further includes identifying features within the electropherogram data indicative of errors and validating the identified mixed bases. Then the method includes determining variants in the electropherogram data based on the validated mixed bases.

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Santa Clara, CA, United States of America

Manjula Aliminati