Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Comment Regarding Specification
The examiner note that this application has incorporated many US patent applications by reference ( see pages 1-6). The examiner notes that may of the claimed features are related to features that appear to be incorporated by reference by one of these documents. In particular 16/825,991 corresponding to US 20200302223 A1; 16/826168 corresponding to US 20200302224 A1, and/or 16/825987 corresponding to US 20200302225 A1 appear to disclose essential material to the claims.
Information Disclosure Statement
The information disclosure statement filed 10/31/2025 fails to comply with 37 CFR 1.98(a)(2), which requires a legible copy of each cited foreign patent document; each non-patent literature publication or that portion which caused it to be listed; and all other information or that portion which caused it to be listed. It has been placed in the application file, but the information referred to therein has not been considered where lined through because the examiner was not able to find a copy of these document in the case file or in the parent applications.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 1-14 and 21-24 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Re claim 1
The limitation of “receive, for a sequencing cycle, one or more images comprising pixels depicting cluster signals from clusters of nucleic acids”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “receiving” in the context of this claim encompasses the user simply looking at the image.
The limitation of determine a set of preliminary cluster centers in the one or more images, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, determining in the context of this claim encompasses the user mentally determining a cluster center.
The limitation of analyze pixel intensities of preliminary cluster centers and respective regions adjacent to preliminary cluster centers; based on analyzing pixel intensity of preliminary cluster centers and respective regions adjacent to preliminary cluster centers, determine one or more cluster center locations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, analyzing pixel intensities in the context of this claim encompasses the user mentally looking at the image to analyze the pixel intensities.
The limitation of generate a template for images from sequencing cycles based on cluster metadata comprising the one or more cluster center locations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, generating a template in the context of this claim encompasses the user mentally imagining a templet
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – A system comprising: at least one processor; and a non-transitory computer-readable medium storing instructions that, when executed by the at least one processor, cause the system to perform the function. The processor and non-transitory computer readable medium are recited at a high-level of generality (i.e., as a generic processor an medium performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor and non-transitory computer readable medium to perform the function amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible.
Re claim 2 The limitation of wherein the cluster metadata further comprises cluster spatial distribution, cluster shapes, cluster sizes, cluster background, or cluster boundaries., as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, the cluster data in the context of this claim encompasses the user mentally determining a template based on the cluster data.
The analysis with respect to integration into an abstract idea and significantly more is not significantly changed from the claim from which this claim depends.
Re claim 3 The limitation of based on the set of preliminary cluster centers, analyze pixel intensity in the one or more images to identify one or more additional cluster centers; and determine one or more cluster center locations based on analyzing pixel intensity of preliminary cluster centers, additional cluster centers, and respective regions adjacent to preliminary cluster centers or additional cluster centers, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, analyzing and determining in the context of this claim encompasses the user mentally analyzing the clusters and determining additional clusters.
The analysis with respect to integration into an abstract idea and significantly more is not significantly changed from the claim from which this claim depends.
Re claim 4 The limitation of determine one or more preliminary cluster centers by identifying one or more center pixels that include a preliminary cluster center, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, determining in the context of this claim encompasses the user mentally determining the location of the cluster.
The analysis with respect to integration into an abstract idea and significantly more is not significantly changed from the claim from which this claim depends.
Re claim 5 he limitation of determine one or more preliminary cluster centers by identifying one or more subpixels that contain one or more preliminary cluster centers., as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, determining in the context of this claim encompasses the user mentally determining the location of the cluster.
The analysis with respect to integration into an abstract idea and significantly more is not significantly changed from the claim from which this claim depends.
Re claim 6 The limitation of determine a revised set of cluster centers based on analyzing pixel intensity of preliminary cluster centers and respective regions adjacent to preliminary cluster centers., as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, determining and analyzing in the context of this claim encompasses the user mentally performing determination and analyzing pixel intensities to determine the cluster.
The analysis with respect to integration into an abstract idea and significantly more is not significantly changed from the claim from which this claim depends.
Re claim 7
The limitation of determine the set of preliminary cluster centers in the one or more images, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, determining in the context of this claim encompasses the user mentally determining preliminary cluster centers.
The limitation of analyze pixel intensities of preliminary cluster centers and respective regions adjacent to preliminary cluster centers, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, analyzing in the context of this claim encompasses the user mentally determining preliminary cluster centers.
The limitation of based on analyzing pixel intensity of preliminary cluster centers and respective regions adjacent to preliminary cluster centers, determine one or more cluster center locations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, analyzing in the context of this claim encompasses the user mentally analyzing the regions.
The limitation of generate a template for images from sequencing cycles based on cluster metadata comprising the one or more cluster center locations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, generating a template in the context of this claim encompasses the user mentally imagining the template.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – A system comprising: at least one processor; a non-transitory computer-readable medium storing instructions that, when executed by the at least one processor, cause the system to perform the function; and a neural network performing the function. The processor and non-transitory computer readable medium are recited at a high-level of generality (i.e., as a generic processor an medium performing a generic computer function ) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Further simply stating that some of the function is performed by a generic neural network does no more that merely limit the claim to the field of artificial intelligence. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor and non-transitory computer readable medium to perform the function amounts to no more than mere instructions to apply the exception using a generic computer component. Further simply stating that some of the function is performed by a generic neural network does no more than merely limit the claim to the field of artificial intelligence. Mere instructions to apply an exception using generic computer components combined with a generic neural network cannot provide an inventive concept. The claim is not patent eligible.
Re claim 8 The limitation of wherein at least one of the clusters of nucleic acids comprises a concatemer created using a rolling circle amplification procedure. Merely describes the clusters depicted in the image. This does not materially change the analysis from claim 1 because one could still receive the image by looking at it.
The analysis with respect to integration into an abstract idea and significantly more is not significantly changed from the claim from which this claim depends.
Re claim 9
The limitation of “receive, for a sequencing cycle, one or more images comprising pixels depicting cluster signals from clusters of nucleic acids”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “receiving” in the context of this claim encompasses the user simply looking at the image.
The limitation of determine a set of preliminary cluster centers in the one or more images, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, determining in the context of this claim encompasses the user mentally determining a cluster center.
The limitation of analyzing pixel intensities in the one or more images and the set of preliminary cluster center coordinates to generate a set of cluster center locations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, analyzing in the context of this claim encompasses the user mentally looking at the pixels and analyzing them to determine cluster center locations.
The limitation of generating a template for images from sequencing cycles based on cluster metadata comprising the set of cluster center locations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, generating a template in the context of this claim encompasses the user mentally generating a template in the mind of the user.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – a computer to perform the function. The computer is recited at a high-level of generality (i.e., as generic computer performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer to perform the function amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible.
Re claim 10 The limitation of wherein generating the template comprises encoding the cluster metadata in a template image, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, generating the template in the context of this claim encompasses the user mentally imagining a template image or simply drawing a template of a couple clusters.
The analysis with respect to integration into an abstract idea and significantly more is not significantly changed from the claim from which this claim depends.
Re claim 11 The limitation of herein determining the set of preliminary cluster center coordinates comprises processing a set of images comprising pixels depicting cluster signals, wherein the set of images comprises images from a plurality of imaging channels, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, determining and processing in the context of this claim encompasses the user mentally looking at images of a plurality of imaging channels.
The analysis with respect to integration into an abstract idea and significantly more is not significantly changed from the claim from which this claim depends.
Re claim 12 The limitation of The limitation of wherein the template comprises data indicative of locations of clusters, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, storing data in the context of this claim encompasses the user mentally determining data indication the location of the clusters.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – a computer to perform the function and storing the output in a file. The computer is recited at a high-level of generality (i.e., as generic computer performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Furthermore storing output in a computer file is insignificant extra solution activity of outputting data. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer to perform the function amounts to no more than mere instructions to apply the exception using a generic computer component. Furthermore storing output in a computer file is insignificant extra solution activity of outputting data Mere instructions to apply an exception using generic computer components and insignificant extra solution activity cannot provide an inventive concept. The claim is not patent eligible.
Re claim 13 The limitation of comprising base calling a target cluster based on the template, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, base calling in the context of this claim encompasses the user mentally determining the base of a target cluster.
The analysis with respect to integration into an abstract idea and significantly more is not significantly changed from the claim from which this claim depends.
Re claim 14 The limitation of wherein at least one of the clusters of nucleic acids comprises a concatemer created using a rolling circle amplification procedure. Merely describes the clusters depicted in the image. This does not materially change the analysis from claim 1 because one could still receive the image by looking at it.
The analysis with respect to integration into an abstract idea and significantly more is not significantly changed from the claim from which this claim depends.
Re claim 21
The limitation of receive, for a sequencing cycle, one or more images comprising pixels depicting cluster signals from clusters of nucleic acids, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, receive in the context of this claim encompasses the user mentally looking at the image to receive it.
The limitation of determine one or more pixels or sub-pixels of an image from the one or more images comprising a cluster center, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, determine in the context of this claim encompasses the user mentally determining the location of the subpixels.
The limitation of generate a template for images from sequencing cycles based on cluster metadata comprising locations corresponding to the one or more pixels or sub-pixels of the image comprising the cluster center, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, generating a template in the context of this claim encompasses the user mentally imagining a templet.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – A system comprising: at least one processor; and a non-transitory computer-readable medium storing instructions that, when executed by the at least one processor, cause the system to perform the function. The processor and non-transitory computer readable medium are recited at a high-level of generality (i.e., as a generic processor an medium performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor and non-transitory computer readable medium to perform the function amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible.
Re claim 22 The limitation of determine the one or more pixels or sub-pixels of the image comprising the cluster center without using a neural network; and generate the template for images from sequencing cycles without using a neural network., as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, further modifying the determining and generating steps to not use a neural network does not change their ability to be performed mentally.
The analysis with respect to integration into an abstract idea and significantly more is not significantly changed from the claim from which this claim depends.
Re claim 23 The limitation of receive, from a template generator, the template for images from sequencing cycles; and generate, using base caller, base calls for each base calling location based on the template, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, reviving and base calling in the context of this claim encompasses the user mentally receiving a mental template and mentally identifying a nucleotide base.
The analysis with respect to integration into an abstract idea and significantly more is not significantly changed from the claim from which this claim depends.
Re claim 24 The limitation of analyze pixel intensity of the one or more pixels or sub-pixels of the image comprising the cluster center and respective regions adjacent to the one or more pixels or sub-pixels of the image comprising the cluster center., as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, analyzing in the context of this claim encompasses the user mentally analyzing the image.
The analysis with respect to integration into an abstract idea and significantly more is not significantly changed from the claim from which this claim depends.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-4, 6, 9, 10, 12, 14, 21, 22, and 24 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Tyrunia US 2007/0177799.
Re claim 1 Tyrunia US 2007/0177799 discloses
A system comprising: at least one processor; and a non-transitory computer-readable medium storing instructions that, when executed by the at least one processor, cause the system to: (see paragraph 54 “Data from the image capture boards 622 are sent to a computer 624 for further processing (e.g., deblending) by one or more software programs running on the computer 624. The program(s) perform the processing operations describe herein, and all or some portions of the program(s) can be stored in the computer 624 on its hard drive and/or in its permanent and/or temporary memory. All or some portions of the program(s) can be stored on any program storage medium that is readable by a computer such as, for example, one or more of RAM, ROM, removable memory/storage devices, hard drives, CDs, etc. The computer 624 is depicted in FIG. 6 as a desktop personal computer, but it can be any other type of computer and in fact any type of computing device now known or later developed (e.g., handheld, laptop, server, workstation, supercomputer, networked device, etc.) running any operating system as long as it is capable of performing the processing operations described herein such as the deblending described herein”)
receive, for a sequencing cycle, one or more images comprising pixels depicting cluster signals from clusters of nucleic acids (see paragraph 28 and 53 figure 2 and figure 1 note that a template image is input see also paragraph 33 and figure 2 note that the image repetition includes intensity data and centroids of objects see abstract and paragraph 36 note that the objects are fluorescing nucleotides and the object in the images correspond to “clusters”);
determine a set of preliminary cluster centers in the one or more images (see paragraph 34-36 and figure 2 element 202 204 and 306 note that centroids and intensity data are determined for the image);
analyze pixel intensities of preliminary cluster centers and respective regions adjacent to preliminary cluster centers (see paragraph 37 and 38 note that intensity data of object corresponding to a centroid analyzed to determine if the intensity fits a point spread function see paragraph 39 note that “area of integration” is 6 pixel corresponding to the surrounding area);
based on analyzing pixel intensity of preliminary cluster centers and respective regions adjacent to preliminary cluster centers, determine one or more cluster center locations (see figure 2 and paragraph 47 note that a coordinates of a final centroid for each object are generated);
and generate a template for images from sequencing cycles based on cluster metadata comprising the one or more cluster center locations (see figure 1 deblended rep. template image this corresponds to the generation of the template see paragraph 35 note that the deburred template image is generated by the processed of figure 2 and includes the corrected centroids. See paragraph 48 and figure 2 element 230 note that the final representation of the image corresponds to the template)
Re claim 2 Tyrunia discloses meta data further comprises cluster spatial distribution (see figure 7 element 106 note that the template image displays a spatial distribution of intensity peaks), cluster shapes, cluster sizes, cluster background, or cluster boundaries.
Re claim 3 Tyruina discloses based on the set of preliminary cluster centers, analyze pixel intensity in the one or more images to identify one or more additional cluster centers (see paragraph 34-35 note that closely spaced objects may be initially represented by one object deblurring is used to reveal the location of additional objects that previously unresolvable corresponding to the corrected centroids see paragraphs 36-49 for the deblurring process); and determine one or more cluster center locations based on analyzing pixel intensity of preliminary cluster centers, additional cluster centers, and respective regions adjacent to preliminary cluster centers or additional cluster centers (see paragraph 34-35 note that closely spaced objects may be initially represented by one object deblurring is used to reveal the location of additional objects that previously unresolvable corresponding to the corrected centroids see paragraphs 36-49 for the deblurring process note that in paragraph 47 note that final centroids will be found for each object by analyzing the intensity data and fitting it to a curve for example in paragraph 37).
Re claim 4 Tyrunia discloses when executed by the at least one processor, cause the system to determine one or more preliminary cluster centers by identifying one or more center pixels that include a preliminary cluster center (see paragraph 33 The intensity data 108 generally follow a Gaussian distribution, and the centroids 110 are typically the coordinates of the centers of the identified objects 104. See paragraph 37 .mu..sub.1 and .mu..sub.2 are the x- and y-coordinates (i.e., centroid) of the fluorescing object i.e. the pixel location of the centroid ).
Re claim 6 Tyrunia discloses determine a revised set of cluster centers based on analyzing pixel intensity of preliminary cluster centers and respective regions adjacent to preliminary cluster centers ((see figure 2 and paragraph 47 note that a coordinates of a final centroid for each object are generated ) (see paragraph 37 and 38 note that intensity data of object corresponding to a centroid analyzed to determine if the intensity fits a point spread function see paragraph 39 note that “area of integration” is 6 pixels ).
Re claim 9 Tyrunia discloses A computer-implemented method comprising:
receiving, for a sequencing cycle, one or more images comprising pixels depicting cluster signals from clusters of nucleic acids (see paragraph 28 and 53 figure 2 and figure 1 note that a template image is input see also paragraph 33 and figure 2 note that the image repetition includes intensity data and centroids of objects see abstract and paragraph 36 note that the objects are fluorescing nucleotides and the object in the images correspond to “clusters” see also paragraph 50);
determining a set of preliminary cluster center coordinates in the one or more images (see paragraph 34-36 and figure 2 element 202 204 and 306 note that centroids and intensity data are determined for the image objects);
analyzing pixel intensities in the one or more images and the set of preliminary cluster center coordinates to generate a set of cluster center locations((see figure 2 and paragraph 47 note that a coordinates of a final centroid for each object are generated) (see paragraph 37 and 38 note that intensity data of object corresponding to a centroid analyzed to determine if the intensity fits a point spread function see paragraph 39 note that “area of integration” is 6 pixels corresponding to the surrounding area).; and
generating a template for images from sequencing cycles based on cluster metadata comprising the set of cluster center locations (see figure 1 deblended rep. template image this corresponds to the generation of the template see paragraph 35 note that the deburred template image is generated by the processed of figure 2 and includes the corrected centroids. See paragraph 47-48 and figure 2 element 230 note that the final representation of the image corresponds to the template).
Re claim 10 Tyurina discloses wherein generating the template comprises encoding the cluster metadata in a template image (see paragraph 47-48 note that the final representation of the image (corresponding to the deblended template of figure 112) includes the centroid information of objects with noise removed).
Re claim 12 Tyruina discloses wherein the template comprises a computer file indicative of locations of clusters (see paragraph 35 A result is a series of equations that are solved simultaneously to yield a template parameter 116 that, in some embodiments, includes corrected values for the centroids 110 see paragraph 50 and 54 note that the template information comprises centroids is generated by computer as such the generated template could be considered a computer file).
Re claim 14 Tyrunia discloses wherein the cluster signals comprise intensity emissions (see paragraph 34-36 and figure 2 element 202 204 and 306 note that centroids and intensity data are determined for the image objects.
Re Claim 21 Tyruina discloses A system comprising: at least one processor; and a non-transitory computer-readable medium storing instructions that, when executed by the at least one processor, cause the system to:
( see paragraph 54 “Data from the image capture boards 622 are sent to a computer 624 for further processing (e.g., deblending) by one or more software programs running on the computer 624. The program(s) perform the processing operations describe herein, and all or some portions of the program(s) can be stored in the computer 624 on its hard drive and/or in its permanent and/or temporary memory. All or some portions of the program(s) can be stored on any program storage medium that is readable by a computer such as, for example, one or more of RAM, ROM, removable memory/storage devices, hard drives, CDs, etc. The computer 624 is depicted in FIG. 6 as a desktop personal computer, but it can be any other type of computer and in fact any type of computing device now known or later developed (e.g., handheld, laptop, server, workstation, supercomputer, networked device, etc.) running any operating system as long as it is capable of performing the processing operations described herein such as the deblending described herein”)
receive, for a sequencing cycle, one or more images comprising pixels depicting cluster signals from clusters of nucleic acids; (see paragraph 28 and 53 figure 2 and figure 1 note that a template image is input see also paragraph 33 and figure 2 note that the image repetition includes intensity data and centroids of objects see abstract and paragraph 36 note that the objects are fluorescing nucleotides and the object in the images correspond to “clusters” see also paragraph 50);
determine one or more pixels or sub-pixels of an image from the one or more images comprising a cluster center (see paragraph 33 The intensity data 108 generally follow a Gaussian distribution, and the centroids 110 are typically the coordinates of the centers of the identified objects 104. See paragraph 37 .mu..sub.1 and .mu..sub.2 are the x- and y-coordinates (i.e., centroid) of the fluorescing object i.e the pixel location of the centroid ).;
and generate a template for images from sequencing cycles based on cluster metadata comprising locations corresponding to the one or more pixels or sub-pixels of the image comprising the cluster center (see figure 1 deblended rep. template image this corresponds to the generation of the template see paragraph 35 note that the deburred template image is generated by the process of figure 2 and includes the corrected centroids. See paragraph 48 and figure 2 element 230 note that the final representation of the image corresponds to the template).
Re claim 22 Tyurina discloses determine the one or more pixels or sub-pixels of the image comprising the cluster center without using a neural network; and generate the template for images from sequencing cycles without using a neural network (see paragraphs 31 -48 and figure 1 note that the process for determining the cluster centers and generating the template are disclose without the use of a neural network. There are no neural networks described in the specification).
Re claim 24 Tyurina discloses when executed by the at least one processor, cause the system to analyze pixel intensity of the one or more pixels or sub-pixels of the image comprising the cluster center and respective regions adjacent to the one or more pixels or sub-pixels of the image comprising the cluster center. (see paragraph 37 and 38 note that intensity data of object corresponding to a centroid analyzed to determine if the intensity fits a point spread function see paragraph 39 note that “area of integration” is 6 pixel corresponding to the surrounding area);
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 5, 15, 16 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tyurina US 20070177799 A1 in view of Xu et al US 2018/0101951.
Re claim 5 Tyurina discloses all the features of claim 1 and determined preliminary clusters (see rejection to claim 1). Tyurina does not expressly disclose determine cluster centers by identifying one or more subpixels that contain one or more preliminary cluster centers. Xu et al discloses determine cluster centers by identifying one or more subpixels that contain one or more preliminary cluster centers (see paragraph 175- 177 the examiner notes that sub pixel centers are determined for candidate spots are determined). The motivation to combine is “the center coordinate of the spot and/or the intensity value of the center coordinate may be represented by the sub-pixel, such that the accuracy of the method for processing an image may be further improved.” (see paragraph 120) The examiner notes that the accuracy of the centroids of Tyurina can be improved by using sub pixel accuracy. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Tyurina and Xu to reach the aforementioned advantage.
Re claim 15 Tyurina discloses determining the set of preliminary cluster center coordinates in the one or more images (see rejection to claim 1). Tyurina does not expressly disclose determining one or more sub-pixel cluster centers in the one or more images based on interpolating sub-pixel intensities using a Gaussian-based intensity extraction
Xu discloses comprises determining one or more sub-pixel cluster centers (see paragraph 175 note that sub pixel centers are determined) in the one or more images based on interpolating sub-pixel intensities (see paragraph 177 note that interpolation is performed to determine sub pixel centers) using a Gaussian-based intensity extraction (see paragraph 176 note that spots are extracted using a gaussian distribution on the intensity). The motivation to combine is “the center coordinate of the spot and/or the intensity value of the center coordinate may be represented by the sub-pixel, such that the accuracy of the method for processing an image may be further improved.” (see paragraph 120) The examiner notes that the accuracy of the centroids of Tyurina can be improved by using sub pixel accuracy. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Tyurina and Xu to reach the aforementioned advantage.
Re claim 16 Tyurina A system comprising: at least one processor; and a non-transitory computer-readable medium storing instructions that, when executed by the at least one processor, cause the system to:
( see paragraph 54 “Data from the image capture boards 622 are sent to a computer 624 for further processing (e.g., deblending) by one or more software programs running on the computer 624. The program(s) perform the processing operations describe herein, and all or some portions of the program(s) can be stored in the computer 624 on its hard drive and/or in its permanent and/or temporary memory. All or some portions of the program(s) can be stored on any program storage medium that is readable by a computer such as, for example, one or more of RAM, ROM, removable memory/storage devices, hard drives, CDs, etc. The computer 624 is depicted in FIG. 6 as a desktop personal computer, but it can be any other type of computer and in fact any type of computing device now known or later developed (e.g., handheld, laptop, server, workstation, supercomputer, networked device, etc.) running any operating system as long as it is capable of performing the processing operations described herein such as the deblending described herein”)
receive, for a sequencing cycle, one or more images comprising pixels depicting cluster signals from clusters of nucleic acids; (see paragraph 28 and 53 figure 2 and figure 1 note that a template image is input see also paragraph 33 and figure 2 note that the image repetition includes intensity data and centroids of objects see abstract and paragraph 36 note that the objects are fluorescing nucleotides and the object in the images correspond to “clusters” see also paragraph 50);
determine one or more cluster centers in the one or more images; ( see paragraph 33 note that centroids are determined see paragraph see figure 2 and paragraph 35 and 36 note that a coordinates of corrected centroids are generated )
and generate a template for images from sequencing cycles based on cluster metadata comprising locations corresponding to the one or more sub-pixel cluster centers. (see figure 1 deblended rep. template image this corresponds to the generation of the template see paragraph 35 note that the deburred template image is generated by the process of figure 2 and includes the corrected centroids. See paragraph 48 and figure 2 element 230 note that the final representation of the image corresponds to the template)
Tyurina does not disclose determine one or more sub-pixel cluster centers in the one or more images based on interpolating sub-pixel intensities using a Gaussian based intensity extraction. Xu discloses comprises determining one or more sub-pixel cluster centers (see paragraph 175 note that sub pixel centers are determined) in the one or more images based on interpolating sub-pixel intensities (see paragraph 177 note that interpolation is performed to determine sub pixel centers) using a Gaussian-based intensity extraction (see paragraph 176 note that spots are extracted using a gaussian distribution on the intensity). The motivation to combine is “the center coordinate of the spot and/or the intensity value of the center coordinate may be represented by the sub-pixel, such that the accuracy of the method for processing an image may be further improved.” (see paragraph 120) The examiner notes that the accuracy of the centroids of Tyurina can be improved by using sub pixel accuracy. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Tyurina and Xu to reach the aforementioned advantage.
Re claim 20 Tyurina discloses determine store the one or more cluster centers as one or more preliminary cluster centers (see paragraph 33 31 and note that preliminary cluster centers (centroids of the objects element 110) are determined using photometry program to detected objects 104 then determine the centroids 110) note the clusters centers are preliminary because they are subjected to further processing (see paragraph 35 and 36 and figure 1 and figure 2). Xu further disclose the subpixel centers (see paragraph 175 note that sub pixel centers are determined).
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tyurina US 20070177799 A1 in view of Chukka US 20200097701 A1.
Re claim 7 Tyurina discloses all the element of claim 1 and determine the set of preliminary cluster centers in the one or more images (see paragraph 33 31 and note that preliminary cluster centers (centroids of the objects element 110) are determined using photometry program to detected objects 104 then determine the centroids 110). Note that Tyurina detects objects as part of the centroid determination. Tyurina does not discloses detecting objects in the one or more images using a neural network. Chucka discloses detecting objects in the one or more images using a neural network (see paragraph 1). One of ordinary skill in the art could have used the neural network object detection in Chukka perform the object detection in Tyrunia as part of the process for determining the centroids thus meeting the limitation of “determine the set of preliminary cluster centers in the one or more images using a neural network”. The motivation to combine is “for accurate detection of objects of interest” and “however, it will be evident to a person having ordinary skill in the art that the disclosed network can be trained and used for detecting any type of objects of interest within any type of sample images” (see paragraph 36). Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Tyurin and Chukka to reach the aforementioned advantage.
The examine notes that the additional features” analyze pixel intensities of preliminary cluster centers and respective regions adjacent to preliminary cluster centers using the neural network; based on analyzing pixel intensity of preliminary cluster centers and respective regions adjacent to preliminary cluster centers, determine one or more cluster center locations using the neural network; or generate a template for images from sequencing cycles based on cluster metadata comprising the one or more cluster center locations using the neural network.“ are presented in the alternative and only and need not be shown to read on the claim.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tyurina US 20070177799 A1 in view of Desai US 20200224243 A1.
Re claim 8 Tyurina discloses wherein at least one of the clusters of nucleic acids comprises a concatemer created using a rolling circle amplification procedure. Desai discloses wherein at least one of the clusters of nucleic acids comprises a concatemer created using a rolling circle amplification (see paragraph 8 performing rolling circle amplification, wherein each circular DNA molecule formed serves as a template to produce a concatemer comprising multiple copies of the circular DNA nucleotide sequence; g) contacting each concatemer with one or more imager oligonucleotides, wherein each imager oligonucleotide comprises a detectable label and a nucleotide sequence complementary to one or more sites in the circular DNA sequence, wherein the imager oligonucleotide binds to said sites in the multiple copies of the circular DNA sequence of the concatemer; and h) detecting the bound imager oligonucleotides.), The motivation to combine is “rolling circle amplification (RCA) to increase the signal for detection”. One of ordinary skill in the art could have easily used rolling circle amplification in the DNA sequencing process or Tyurina to generate the images for DNA sequencing. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Tyurina and Desai to reach the aforementioned advantage.
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tyurina US 20070177799 A1 in view of Garcia US 2012/0020537.
Re claim 11 Tyurina discloses determining the set of preliminary cluster center coordinates comprises processing a set of images comprising pixels depicting cluster signals, (see figure 1 note that the template image and the sample image both have centroids determined see paragraph 33 and paragraph 7). Tyurina does not expressly disclose wherein the set of images comprises images from a plurality of imaging channels (see paragraph 90). The motivation to combine is “Four images can then be obtained, each using a detection channel that is selective for one of the four different label” see paragraph 96 and “improved speed and accuracy.” See paragraph 8. One of ordinary skill in the art could have modified Tyurina to use it in a process with multiple channels. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Tyurina and Garcia to reach the aforementioned advantage.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tyurina US 20070177799 A1 in view of Emhoff US 20100034444 A1.
Tyruina discloses the features of claim 1 and sequencing DNA a target cluster based on the template (see abstract and paragraph 31). To the extent Tyrunia does not expressly disclose base calling. Emhoff discloses base calling a target cluster based on the template. (See paragraph 38 note that a template is used for base calling). The motivation to combine is “at the end of the process the nucleotides are known.” Therefore it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine Tyrunia and Emhoff to reach the aforementioned advantage.
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tyurina US 20070177799 A1 in view of Xu et al US 2018/0101951 in further view of Desai US 20200224243 A1.
Tyruina and Xu disclose all the elements of claim 16 they do not expressly disclose wherein at least one of the clusters of nucleic acids comprises a concatemer. Desai discloses herein at least one of the clusters of nucleic acids comprises a concatemer (see paragraph 8 performing rolling circle amplification, wherein each circular DNA molecule formed serves as a template to produce a concatemer comprising multiple copies of the circular DNA nucleotide sequence; g) contacting each concatemer with one or more imager oligonucleotides, wherein each imager oligonucleotide comprises a detectable label and a nucleotide sequence complementary to one or more sites in the circular DNA sequence, wherein the imager oligonucleotide binds to said sites in the multiple copies of the circular DNA sequence of the concatemer; and h) detecting the bound imager oligonucleotides.), The motivation to combine is “rolling circle amplification (RCA) to increase the signal for detection” (see paragraph 7). One of ordinary skill in the art could have easily used rolling circle amplification in the DNA sequencing process or Tyurina to generate the images for DNAsequencing. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Tyurina Xu and Desai to reach the aforementioned advantage.
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tyurina US 20070177799 A1 in view of Xu et al US 2018/0101951 in further view of Chukka US 20200097701 A1.
Re claim 18 Tyurina and Xu discloses all the element of claim 16 and determine one or more cluster centers in the one or more images (see paragraph 33 31 and note that preliminary cluster centers (centroids of the objects element 110) are determined using photometry program to detected objects 104 then determine the centroids 110). Xu discloses subpixels (see paragraph 175- 177 the examiner notes that sub pixel centers are determined for candidate spots are determined). Note that Tyurina detects objects as part of the centroid determination. Tyurina does not discloses detecting objects in the one or more images using a neural network. Chukka discloses detecting objects in the one or more images using a neural network, (see paragraph 1 and 36 note that objectrs are detected via a neural network). One of ordinary skill in the art could have used the neural network object detection in Chukka perform the object detection in Tyrunia as part of the process for determining the centroids thus meeting the limitation of “determine the set of preliminary cluster centers in the one or more images using a neural network”. The motivation to combine is “for accurate detection of objects of interest” and “however, it will be evident to a person having ordinary skill in the art that the disclosed network can be trained and used for detecting any type of objects of interest within any type of sample images” (see paragraph 36). Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Tyurin and Chukka to reach the aforementioned advantage.
The examiner notes that the additional element or “generate a template for images from sequencing cycles based on cluster metadata through the neural network” is presented in the alternative and only one of these elements need be shown.
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tyurina US 20070177799 A1 in view of Xu et al US 2018/0101951 in further view of Emhoff US 20100034444 A1.
Re claim 19 Tyurnia and Xu discloses all the features of claim 16 and expressly disclose generate a template by encoding the cluster metadata in a single template image (see paragraph 47-48 note that the final representation of the image (corresponding to the deblended template of figure 112) includes the centroid information of objects with noise removed). They do not expressly disclose and base call a target cluster using a plurality of imaging channels based on the single template image. Emhoff discloses and base call a target cluster using a plurality of imaging channels (see paragraph 28 note that four separate nucleotides are recognized and uniquely registered these correspond to the different “imaging channels”) based on the single template image (see paragraph 38 note that the first image in the stack may be used to generate the template). The motivation to combine to perform “faster and has fewer errors than previous apparatuses” see paragraph 36. One of ordinary skill in the art could have adapted the template of Tyurnia modified by Xu to sequence the multiple channels of Emhoff Therefore it would have been obvious before the effective filing date of the claimed invention to combine Emhoff Xu and Tyurina to reach the aforementioned advantage.
Claim(s) 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tyurina US 20070177799 A1 in view of Xu et al US 2018/0101951 in further view of Wick et al Performance of neural network basecalling tools for Oxford Nanopore sequencing Volume 20, article number 129, (2019).
Re claim 23 Tyurina discloses receive, from a template generator, the template for images from sequencing cycles; (see paragraph 30 and 33), Generate Sequencing with using centroid locations for each sequencing location based on the template (see abstract and paragraph 50 and 55 note that nucleotides are sequenced using the template).
Tyurina and Xu do not expressly disclose a neural network-based base caller. Wick discloses a neural network-based base caller, (see background and results section). The motivation to combine is A larger neural network is able to improve both read and consensus accuracy (see background section). One of ordinary skill in the art could have easily trained a neural network to perform to perform base calling using the template of Tyruina. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Wick, Tyurina and Xu to reach the aforementioned advantage.
Allowable Subject Matter
Claim 25-30 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Re claim 25 the prior art of record does not expressly disclose the combination of select, from a bank of lookup tables, a lookup table that contains pixel coefficients that are configured to increase a signal-to-noise ratio; apply the pixel coefficients to intensity values of the pixels in an image of the one or more images to produce an output; and base call a target cluster based on the output.
Claim 26 depends from claim 25.
Re claim 27 the prior art of record does not expressly disclose the combination of access a set of images of a tile captured during a sequencing run and preliminary center coordinates of the clusters determined by a base caller; for each image set, obtain a base call classifying, as one of four bases, origin subpixels that contain the preliminary center coordinates and a predetermined neighborhood of contiguous subpixels that are successively contiguous to respective ones of the origin subpixels, thereby producing a base call sequence for each of the origin subpixels and for each of the predetermined neighborhood of contiguous subpixels; generate a cluster map that identifies the clusters as disjointed regions of contiguous subpixels that are successively contiguous to at least some of the respective ones of the origin subpixels and share a substantially matching base call sequence of the one of four bases with the at least some of the respective ones of the origin subpixels; and store the cluster map in memory and determine cluster metadata comprising shapes and sizes of the clusters based on the disjointed regions in the cluster map.
Re claim 28 the prior art of record does not expressly disclose the combination of receive input image data, the input image data derived from a sequence of images, wherein each image in the sequence of images represents an imaged region and depicts intensity emissions of one or more clusters and surrounding background at a respective one of a plurality of sequencing cycles of a sequencing run, and wherein the input image data comprises image patches extracted from each image in the sequence of images; process the input image data through a neural network to generate an alternative representation of the input image data, wherein the neural network is trained for cluster metadata determination task, including determining cluster background, cluster centers, and cluster shapes; process the alternative representation through an output layer to generate an output indicating properties of respective portions of the imaged region; threshold output values of the output and classify a first subset of the respective portions of the imaged region as background portions depicting the surrounding background; locate peaks in the output values of the output and classify a second subset of the respective portions of the imaged region as center portions containing centers of the one or more clusters; and apply a segmenter to the output values of the output and determine shapes of the one or more clusters as non-overlapping regions of contiguous portions of the imaged region.
Re claim 29 the prior art of record does not expressly disclose the combination of convolve input data through a convolutional neural network to generate a convolved representation of the input data, wherein the input data includes image patches extracted from one or more images in each of a current image set generated at a current sequencing cycle of a sequencing run, of one or more preceding image sets respectively generated at one or more sequencing cycles of the sequencing run preceding the current sequencing cycle, and of one or more succeeding image sets respectively generated at one or more sequencing cycles of the sequencing run succeeding the current sequencing cycle, wherein each of the image patches depicts intensity emissions of a target cluster being base called, and wherein the input data further includes distance information indicating respective distances of pixels of the image patch from a center pixel of the image patch; process the convolved representation through an output layer to produce an output; and base call the target cluster at the current sequencing cycle based on the output.
Re claim 30 the prior art of record does not expressly disclose the combination of process input data for one or more clusters through a neural network-based base caller and produce an alternative representation of the input data; process the alternative representation through an output layer to produce an output, wherein the output identifies likelihoods of a base incorporated in a particular one of the clusters being A, C, T, and G; call bases for one or more of the clusters based on the output; and determine quality scores for the bases based on the likelihoods identified by the output based on a quantization scheme calibrated against training of the neural network-based base caller, wherein the quantization scheme includes: quantizing classification scores of called bases produced by the neural network-based base caller during the training in response to processing training data; selecting a set of quantized classification scores; for each quantized classification score in the set of quantized classification scores, determining a base calling error rate by comparing its predicted base calls to corresponding ground truth base calls; determining a fit between each of the set of quantized classification scores and their base calling error rates; and correlating the quality scores to the set of quantized classification scores based on the fit.
Cited Art
The following is a listing of cited art which is considered relevant but not used in a rejection above.
Li et al US 20210217171 A1 discloses A method for constructing a sequencing template based on an image, a device, and a system. The image includes first, second, third and fourth images of one same field of view corresponding to base extensions of A, T/U, G, and C respectively; the first, second, third and fourth images respectively include images M1 and M2, images N1 and N2, images P1 and P2, and images Q1 and Q2; the method includes combining any two of the images M1, M2, N1, N2, P1, P2, Q1, and Q2 to perform bright spot matching, and enabling such images to participate in the combination for at least one time to obtain a plurality of combined images including first coincident bright spots, and merging the first coincident bright spots on the plurality of combined images to obtain a bright spot set corresponding to the sequencing template. (See abstract)
Gordon US 20130137091 A1 discloses The invention provides methods and compositions, including, without limitation, algorithms, computer readable media, computer programs, apparatus, and systems for determining the identity of nucleic acids in nucleotide sequences using, for example, data obtained from sequencing by synthesis methods. The methods of the invention include correcting one or more phenomena that are encountered during nucleotide sequencing, such as using sequencing by synthesis methods. These phenomena include, without limitation, sequence lead, sequence lag, spectral crosstalk, and noise resulting from variations in illumination and/or filter responses. (see abstract)
Conclusion
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/SEAN T MOTSINGER/Primary Examiner, Art Unit 2673