David Kuo Woo, 743635 Brown Ave, Oakland, CA 94619

7398171, Jul 8, 2008

Jun 30, 2006

11/428048

David C. Woo - Foster City CA, US

Applera Corporation - Foster City CA

G06F 19/00
G06F 17/40

702 82, 382100, 382128, 382129, 382133, 702 19, 702 20, 702 81, 702189

Aspects of the present invention describe a method and apparatus for automating quality control for gene expression data. A computer based device receives gene expression data associated with a spectral species and genetic sample in each well of a plate. Gene expression data may be received from a sequence detection instrument performing one or more gene expression related operations for each of the wells of the plate. The computer based device identifies gene expression data determined to have anomalous characteristics according to a set of one or more quality control metrics and may conditionally flag one or more wells of the plate affected by the anomalous characteristics. Filters can then be selectively applied to temporarily or permanently remove the flagged data from subsequent gene expression studies.

7839507, Nov 23, 2010

Jun 28, 2007

11/770443

Stephen J. Gunstream - San Francisco CA, US
David C. Woo - Foster City CA, US
John P. Bodeau - San Mateo CA, US
Mark A. McCoy - Foster City CA, US

Applied Biosystems, LLC - Carlsbad CA

G01N 21/25

356417

Methods and systems for processing signals to minimize the effects of dye crosstalk. Deconvolution of multiplexed dye signals can include corrections for residual error determined from experimental measurements. Residual error corrections can account for reaction or assay specific factors and modify the subsequent filtering of signals. Correction values can be determined for specific dye-probe conjugates to minimize dye crosstalk and may be combined with residual error correction to further minimize errors in spectral deconvolution. Apparatus, systems, and computer-readable media can process signals and modify filters based on values obtained using the methods.

8621251, Dec 31, 2013

Feb 24, 2011

13/034661

Kevin E. Keller - Sunnyvale CA, US
Steven D. McKenney - Seattle WA, US
Paul E. Misener - Great Falls VA, US
David Y. Woo - Seattle WA, US
Gregg Elliott Zehr - Seattle WA, US

Amazon Technologies, Inc. - Reno NV

G06F 1/26

713310, 713300, 713320

A computing device may operate in various modes, which may include a full operational mode and a reduced operational mode. When operating in the reduced operational mode, the computing device may reduce power, reduce radiation output, and/or power off various components to achieve operation in accordance with an operational policy. While operating in the reduced operational mode, the computing device may restrict user access to or adjustment of the impacted components thereby preventing the user from restoring the computing device to the full operational mode, at least temporarily. In some aspects, the device may initiate or terminate the reduced operational mode in response to a signal from a beacon, parameters from a monitored environment, or in response to user commands. In various aspects, the device may provide messaging to inform the user about the modes of operation.

8649982, Feb 11, 2014

Sep 13, 2011

13/231618

David Woo - Foster City CA, US
Clinton Lewis - Palo Alto CA, US
Nasser Abbasi - San Mateo CA, US

Applied Biosystems, LLC - Carlsbad CA

G01N 33/48

702 19

The invention discloses a system and methods for quantitating the presence of nucleic acid sequences by evaluation of amplification data generated using real-time PCR. In one aspect, the methods may be adapted to identify a threshold and threshold cycle for one or more reactions based upon evaluation of exponential and baseline regions for each amplification reaction. The methodology used in the analysis may be readily automated such that subjective user interpretation of the data is substantially reduced or eliminated.

2007001, Jan 11, 2007

Jun 30, 2006

11/428293

Madhu Augustine - Foster City CA, US
David Woo - Foster City CA, US
Jacob Burghardt - Seattle WA, US

G06F 17/00

707104100

Aspects of the present invention describe a method and apparatus for viewing and interfacing with gene expression on a computer device. A computer based device interfaces with gene the expression data by representing a plate having one or more wells and their contents with a matrix of elements addressable along at least two-dimensions. Each of the elements in the matrix are processed and then distinguished based upon their passing and failing one or more metrics for gene expression data. The interface displays those values associated with the distinguished elements in the matrix using colors, shapes and symbols. Depending on the results, some of the elements in the matrix may be flagged and then filtered from the data set. Remaining gene expression values not filtered from the matrix of elements are displayed and processed further.

2008020, Aug 21, 2008

Jan 28, 2008

12/021032

Chengyong Yang - Foster City CA, US
David C. Woo - Foster City CA, US

Applera Corporation - Foster City CA

G06F 17/18
G01N 33/48
G01D 18/00

702179, 702 19, 702 85

The present teachings comprise systems and methods for calibrating the background or baseline signal in a PCR or other reaction. The background signal derived from detected emissions of sample wells can be subjected to a normalized statistical metric, and be compared to a threshold or other standard to discard outlier cycles or other extraneous data. According to various embodiments, a relative standard deviation (relativeSTD) for the background component can be generated by dividing the standard deviation by the median of differences across all wells, where the difference is defined as the difference between maximum and minimum pixel values of a well. The relativeSTD as a metric is not sensitive to machine-dependent variations in absolute signal output that can be caused by different gain settings, different LED draw currents, different optical paths, or other instrumental variations. More accurate background characterization can be achieved.

2021039, Dec 23, 2021

Jun 11, 2020

16/899545

- Carlsbad CA, US
Stephanie Jo Schneider - Mountain View CA, US
Rylan Schaeffer - Mountain View CA, US
David Woo - Foster City CA, US

Life Technologies Corporation - Carlsbad CA

G16B 30/00
G16B 25/00
G16B 40/00
G06N 3/08
G06N 5/04
G06K 9/62
C12Q 1/6869

A method of automatically sequencing or basecalling one or more DNA (deoxyribonucleic acid) molecules of a biological sample is described. The method comprises using a capillary electrophoresis genetic analyzer to measure the biological sample to obtain at least one input trace comprising digital data corresponding to fluorescence values for a plurality of scans. Scan labelling probabilities for the plurality of scans are generated using a trained artificial neural network comprising a plurality of layers including convolutional layers. A basecall sequence comprising a plurality of basecalls for the one or more DNA molecules based on the scan labelling probabilities for the plurality of scans is determined.

2021031, Oct 7, 2021

Mar 19, 2021

17/207488

- Carlsbad CA, US
Thomas Wessel - Pleasanton CA, US
David C. Woo - Foster City CA, US
Marcin Sikora - Burlingame CA, US
Gordon A. Janaway - Castro Valley CA, US
Shweta Raizada - Southfield MI, US
Joanna Lankester - San Carlos CA, US
Jeffrey A. Marks - Mountain View CA, US
Daniel Wessel - Pleasanton CA, US

G16B 25/20
G16B 25/00
G16B 40/00
C12Q 1/686

A computer-implemented method for designing a digital PCR (dPCR) experiment is provided. The method includes receiving, from a user, a selection of optimization type. The optimization type may be maximizing the dynamic range, minimizing the number of substrates including reaction sites needed for the experiment, determining a dilution factor, or determining the lower limit of detection, for example. The method further includes receiving, from the user, a precision measure for an experiment, and a minimum concentration of a target in a reaction site for the experiment. The method also includes determining a set of dPCR experiment design factors for the experiment based on the optimization type. The set of dPCR experiment design factors is then displayed to the user.