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 .
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, 4-12, 15-18, 20, 22, 24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
create a first distribution of a first plurality of pairwise comparisons of vectors, of the first set of vectors, which were generated from image pairs with similar cell perturbations (creating a distribution from vector of data is a mathematical function);
create a second distribution of a second plurality of pairwise comparisons of vectors of the first set of vectors, which were generated from image pairs with dissimilar cell perturbations (creating a distribution from vector of data is a mathematical function);
determine a difference between the first distribution and the second distribution (determining a difference is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper); and
use the difference to make a determination of goodness of the first deep learning model, as applied to the biological assay, in maintaining both consistency and diversity between biology in different images, of the plurality of images, in the vectors of the first set of vectors (determining a difference and/or goodness is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper); and
create a third distribution of a third plurality of pairwise comparisons of vectors, of the second set of vectors, which were generated from the image pairs with similar cell perturbations (creating a distribution from vector of data is a mathematical function);
create a fourth distribution of a fourth plurality of pairwise comparisons of vectors, of the second set of vectors, which were generated from the image pairs with dissimilar cell perturbations (creating a distribution from vector of data is a mathematical function);
determine a second difference between the third distribution and the fourth distribution (determining a difference is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper);
compare the difference with the second difference to make a determination of goodness of the first deep learning model with respect to the second deep learning model (determining a difference and/or goodness is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper); and
select between using the first deep learning model and the second deep learning model based on the comparison of the difference to the second difference (model selection is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper),
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application. The claim recites the following additional elements:
A system for determining a goodness of a deep learning model, comprising: a memory; and at least one processor coupled with the memory and configured to (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f)):
following a biological assay involving perturbing cells in wells of at least one microplate, direct capture of a plurality of images of biology of the cells in the wells (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)); furthermore, capturing of data amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g));
access a first set of vectors representative of the images of the biological assay (accessing vectors amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g)), wherein vectors of the first set of vectors are outputs of a first deep learning model (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
wherein the processor is further configured to:
access a second set of vectors representative of the images of the biological assay (accessing vectors amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g)), wherein vectors of the second set of vectors are outputs of a second deep learning model, (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)); and
wherein the second deep learning model is different from the deep learning model (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
wherein the selected deep learning model is used for additional vectorization of the cell biology of images and the non-selected deep learning model sees diminished or ceased use in vectorization of the cell biology of images (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)).
Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Step 2B: the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
A system for determining a goodness of a deep learning model, comprising: a memory; and at least one processor coupled with the memory and configured to (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f)):
following a biological assay involving perturbing cells in wells of at least one microplate, direct capture of a plurality of images of biology of the cells in the wells (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)); furthermore, capturing of data amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g), and well understood, routine and convention as identified by the court in MPEP 2106.05(d));
access a first set of vectors representative of the images of the biological assay (accessing vectors amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g), and well understood, routine and convention as identified by the court in MPEP 2106.05(d)), wherein vectors of the first set of vectors are outputs of a first deep learning model (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
wherein the processor is further configured to:
access a second set of vectors representative of the images of the biological assay (accessing vectors amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g), and well understood, routine and convention as identified by the court in MPEP 2106.05(d)), wherein vectors of the second set of vectors are outputs of a second deep learning model, (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)); and
wherein the second deep learning model is different from the deep learning model (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
wherein the selected deep learning model is used for additional vectorization of the cell biology of images and the non-selected deep learning model sees diminished or ceased use in vectorization of the cell biology of images (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)).
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as they are mere insignificant extra solution activity in combination of generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above.
Claim 4: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
4. (Currently Amended) The system as recited in Claim 1, wherein the processor is further configured to: adjust an aspect of one of the first deep learning model and the second deep learning model based on the comparison of the difference to the second difference (adjust an aspect of a model is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper), wherein the processor analyzes both the selected deep learning model and the non-selected deep learning model for differences (analyzing for difference is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper).
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application. The claim recites the following additional elements:
removes an aspect of the non-selected model which is not present in the selected deep learning model (amounts to mere insignificant application, an insignificant extra-solution activity as discussed in MPEP 2106.05(g)).
Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Step 2B: the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
removes an aspect of the non-selected model which is not present in the selected deep learning model (amounts to mere insignificant application, an insignificant extra-solution activity as discussed in MPEP 2106.05(g), which is extra-solution activity of well, understood routine and conventional operation of applying it under MPEP 2106.05(d)).
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as they are mere insignificant extra solution activity in combination of generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above.
Claim 5: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
create a third fifth distribution of a third plurality of pairwise comparisons of vectors, of the second set of vectors, which were generated from image pairs with similar cell perturbations (creating a distribution from vector of data is a mathematical function);
create a fourth sixth distribution of a fourth plurality of pairwise comparisons of vectors, of the second set of vectors, which were generated from image pairs with similar dissimilar cell perturbations (creating a distribution from vector of data is a mathematical function);
determine a second third difference between the third fifth distribution and the fourth sixth distribution (determining a difference is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper); and
compare the difference with the second third difference to make a determination of goodness of the first deep learning model with respect to at least one of representing consistency of similar biological perturbations across time-separated biological assays and representing diversity in dissimilar biological perturbations across time-separated biological assays (determining a difference and/or goodness is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper).
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application. The claim recites the following additional elements:
following a second biological assay involving perturbing cells in wells of at least one additional microplate, direct capture of a second plurality of images of biology of the cells in the wells of at the least one additional microplate (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)); furthermore, capturing of data amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g));
access a second set of vectors representative of the images of the second biological assay (accessing vectors amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g)), wherein vectors of the second set of vectors are outputs of the first deep learning model, and wherein the second biological assay is conducted at a separate time from the biological assay (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Step 2B: the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
following a second biological assay involving perturbing cells in wells of at least one additional microplate, direct capture of a second plurality of images of biology of the cells in the wells of at the least one additional microplate (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)); furthermore, capturing of data amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g) and well understood, routine and convention as identified by the court in MPEP 2106.05(d)));
access a second set of vectors representative of the images of the second biological assay (accessing vectors amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g) and well understood, routine and convention as identified by the court in MPEP 2106.05(d))), wherein vectors of the second set of vectors are outputs of the first deep learning model, and wherein the second biological assay is conducted at a separate time from the biological assay (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as they are mere insignificant extra solution activity in combination of generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above.
Claim 6: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites an abstract idea of independent claim.
The system of Claim 1, wherein the processor configured to create a first distribution comprises the processor being configured to: create the first distribution to represent the first plurality of pairwise comparisons of vectors as one of distances and angle comparisons (vectors as angles is a mathematical function);
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application.
The claim recites no additional element:
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
The claim is not patent eligible.
Claim 7: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
7. (Original) The system of Claim 1, wherein the processor configured to create a first distribution comprises the processor being configured to: perform one of a parametric test and a non-parametric test (parametric test and a non-parametric in high level is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper);
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application.
The claim recites no additional element:
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
The claim is not patent eligible.
Claim 8: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
8. (Currently Amended) A method of determining a goodness of a deep learning model, comprising:
creating a first distribution of a first plurality of pairwise comparisons of vectors, of the first set of vectors, which were generated from image pairs with similar cell perturbations (creating a distribution from vector of data is a mathematical function); wherein the first plurality of pairwise comparisons comprise determining a cosine similarity from the cosine of the angle between each pair of evaluated vectors in the first plurality of pairwise comparisons (cosine similarity is a mathematical function);, and wherein the first distribution comprises a first cumulative distribution function created by cumulating similarities that are measured between vectors of pairs of the first plurality of pairwise comparisons (cumulating distribution is a mathematical function);
creating a second distribution of a second plurality of pairwise comparisons of vectors, of the first set of vectors, which were generated from image pairs with dissimilar cell perturbations (creating a distribution from vector of data is a mathematical function); wherein the second plurality of pairwise comparisons comprise determining a cosine similarity from the cosine of the angle between each pair of evaluated vectors in the second plurality of pairwise comparisons (cosine similarity is a mathematical function), and wherein the second distribution comprises a second cumulative distribution function created by cumulating similarities that are measured between vectors of pairs of the second plurality of pairwise comparisons (cumulating distribution is a mathematical function);
determining, by the computer system, a difference between the first distribution and the second distribution (determining a difference is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper);
using, by the computer system, the difference to make a determination of goodness of the first deep learning model, as applied to the biological assay, in maintaining both consistency and diversity between biology in different images, of the plurality of images, (determining a difference and/or goodness is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper).
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application. The claim recites the following additional elements:
by a/the computer system (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f));
performing a biological assay in which cells from the same cell line are placed in test wells of one or more microplates and those of the cells in each test well are perturbed in one of two different ways such that some of the test wells contain cells perturbed in a first of the two different ways and some of the test wells contain cells perturbed in a second of the two different ways (performing a biological assay, amounts to mere insignificant application, an insignificant extra-solution activity as discussed in MPEP 2106.05(g));
capturing a plurality of images of the biological assay, the images of biology of the cells in the test wells (amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g));
accessing by a computer system, a first set of vectors representative of the images of the biological assay (accessing vectors amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g)), wherein vectors of the first set of vectors are outputs of a first deep learning model (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
such that the some of the pairwise comparisons are performed on pairs of vectors associated with cells that have been similarly perturbed in the first of the two different ways and others of the pairwise comparisons are performed on pairs of vectors associated with cells which have been similarly perturbed in the second of the two different ways wells (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
such that the each of the pairwise comparisons is performed on pairs of vectors where one of the vector in each of the pairs is associated with cells that have been perturbed in the first of the two different ways and the other vector in each of the pairs is associated with cells which have been dissimilarly perturbed in the second of the two different ways (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)),
wherein the difference is a measure of the vertical separation between the first cumulative distribution function and the second cumulative distribution function (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)),
when transforming cell biology of the plurality of images into the vectors of the first set of vectors (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)).
Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Step 2B: the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
by a/the computer system (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f));
performing a biological assay in which cells from the same cell line are placed in test wells of one or more microplates and those of the cells in each test well are perturbed in one of two different ways such that some of the test wells contain cells perturbed in a first of the two different ways and some of the test wells contain cells perturbed in a second of the two different ways (amounts to mere insignificant application, an insignificant extra-solution activity as discussed in MPEP 2106.05(g), See spec [0001] that biological assay is well understood, routine and convention as identified by the court in MPEP 2106.05(d));
capturing a plurality of images of the biological assay, the images of biology of the cells in the test wells (amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g), and well understood, routine and convention as identified by the court in MPEP 2106.05(d));
accessing by a computer system, a first set of vectors representative of the images of the biological assay (accessing vectors amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g), and well understood, routine and convention as identified by the court in MPEP 2106.05(d)), wherein vectors of the first set of vectors are outputs of a first deep learning model (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
such that the some of the pairwise comparisons are performed on pairs of vectors associated with cells that have been similarly perturbed in the first of the two different ways and others of the pairwise comparisons are performed on pairs of vectors associated with cells which have been similarly perturbed in the second of the two different ways wells (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
such that the each of the pairwise comparisons is performed on pairs of vectors where one of the vector in each of the pairs is associated with cells that have been perturbed in the first of the two different ways and the other vector in each of the pairs is associated with cells which have been dissimilarly perturbed in the second of the two different ways (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)),
wherein the difference is a measure of the vertical separation between the first cumulative distribution function and the second cumulative distribution function (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)),
when transforming cell biology of the plurality of images into the vectors of the first set of vectors (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)).
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as they are mere insignificant extra solution activity in combination of generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above.
Claim 9: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
creating a third distribution of a third plurality of pairwise comparisons of vectors, of the second set of vectors, which were generated from image pairs with similar cell perturbations (creating a distribution from vector of data is a mathematical function);
creating a fourth distribution of a fourth plurality of pairwise comparisons of vectors, of the second set of vectors, which were generated from image pairs with dissimilar cell perturbations (creating a distribution from vector of data is a mathematical function);
determining a second difference between the third distribution and the fourth distribution (determining a difference is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper); and
comparing the difference with the second difference to make a determination of goodness of the first deep learning model with respect to the second deep learning model (determining a difference and/or goodness is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper).
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application. The claim recites the following additional elements:
by a/the computer system (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f));
accessing a second set of vectors representative of the images of the biological assay (accessing vectors amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g)), wherein vectors of the second set of vectors are outputs of a second deep learning model, and wherein the second deep learning model is different from the deep learning model (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Step 2B: the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
by a/the computer system (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f));
accessing a second set of vectors representative of the images of the biological assay (accessing vectors amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g), and well understood, routine and convention as identified by the court in MPEP 2106.05(d), wherein vectors of the second set of vectors are outputs of a second deep learning model, and wherein the second deep learning model is different from the deep learning model (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as they are mere insignificant extra solution activity in combination of generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above.
Claim 10: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
10. The method as recited in Claim 9, further comprising:
selecting between using the first deep learning model and the second deep learning model based on the comparison of the difference to the second difference (selecting model is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper);
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application.
The claim recites additional element:
by the computer system (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f));
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
The claim is not patent eligible.
Claim 11: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
adjusting an aspect of one of the first deep learning model and the second deep learning model based on the comparison of the difference to the second difference (model adjustment is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper);
analyzes both the selected deep learning model and the non-selected deep learning model for differences (model analysis is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper);
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application.
The claim recites additional element:
by the computer system and wherein the processor (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f));
and adds an aspect to the non-selected model which is present in the selected deep learning model but was not present in the non-selected deep learning model amounts to mere insignificant application, an insignificant extra-solution activity as discussed in MPEP 2106.05(g)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
by the computer system and wherein the processor (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f));
and adds an aspect to the non-selected model which is present in the selected deep learning model but was not present in the non-selected deep learning model amounts to mere insignificant application, an insignificant extra-solution activity as discussed in MPEP 2106.05(g), which is extra-solution activity of well, understood routine and conventional operation of applying it under MPEP 2106.05(d)).
The claim is not patent eligible.
Claim 12: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
12. The method as recited in Claim 8, further comprising:
creating a third distribution of a third plurality of pairwise comparisons of vectors, of the second set of vectors, which were generated from image pairs with similar cell perturbations (creating a distribution from vector of data is a mathematical function);
creating a fourth distribution of a fourth plurality of pairwise comparisons of vectors, of the second set of vectors, which were generated from image pairs with similar cell perturbations (creating a distribution from vector of data is a mathematical function);
determining a second difference between the third distribution and the fourth distribution (determining a difference is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper); and
comparing the difference with the second difference to make a determination of goodness of the first deep learning model with respect to at least one of representing consistency of similar biological perturbations across time-separated biological assays and representing diversity in dissimilar biological perturbations across time-separated biological assays (determining a difference and/or goodness is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper).
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application. The claim recites the following additional elements:
by the computer system (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f));
directing capture of a second plurality of images of a second biological assay involving perturbing cells in wells of at least one additional microplate, the images of biology of cells in the wells of the at least one additional microplate (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)); furthermore, capturing image amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g));
accessing a second set of vectors representative of the images of the second biological assay (accessing vectors amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g)), wherein vectors of the second set of vectors are outputs of the first deep learning model, and wherein the second biological assay is conducted at a separate time from the biological assay (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Step 2B: the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
directing capture of a second plurality of images of a second biological assay involving perturbing cells in wells of at least one additional microplate, the images of biology of cells in the wells of the at least one additional microplate (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h)); furthermore, capturing image amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g)), and well understood, routine and convention as identified by the court in MPEP 2106.05(d));
accessing a second set of vectors representative of the images of the second biological assay (accessing vectors amounts to mere data gathering, an insignificant extra-solution activity as discussed in MPEP 2106.05(g)), and well understood, routine and convention as identified by the court in MPEP 2106.05(d)), wherein vectors of the second set of vectors are outputs of the first deep learning model, and wherein the second biological assay is conducted at a separate time from the biological assay (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
The additional elements as disclosed above in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as they are mere insignificant extra solution activity in combination of generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above.
Claim 15: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
15. The method as recited in Claim 8, wherein the determining a difference between the first distribution and the second distribution comprises:
performing one of a parametric test and a non-parametric test (parametric test and a non-parametric in high level is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper);
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application.
The claim recites additional element:
by the computer system (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f));
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
The claim is not patent eligible.
Claim 16: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
16. The method as recited in Claim 8, wherein the determining a difference between the first distribution and the second distribution comprises: performing a Kolmogorov-Smirnov test (Kolmogorov-Smirnov test is a mathematical concept);
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application.
The claim recites additional element:
by the computer system (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f));
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
The claim is not patent eligible.
Claim 17: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
17. The method as recited in Claim 8, wherein the determining a difference between the first distribution and the second distribution comprises: performing a Wilcoxon Rank-Sum test (Wilcoxon Rank-Sum test is a mathematical concept);
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application.
The claim recites additional element:
by the computer system (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f));
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
The claim is not patent eligible.
Claim 18: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
18. The method as recited in Claim 8, wherein the determining a difference between the first distribution and the second distribution comprises: performing a Kolmogorov-Shapiro test (Kolmogorov-Shapiro test is a mathematical concept);
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application.
The claim recites additional element:
by the computer system (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f));
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The judicial exceptions are not integrated into a practical application.
The claim is not patent eligible.
Claim 20: Step 1: the claim is directed to statuary category.
Step 2A Prong 1: The claim recites the following limitations:
creating a first distribution of a first plurality of pairwise comparisons of vectors, of the first set of vectors, which were generated from image pairs with similar cell perturbations (creating a distribution from vector of data is a mathematical function) wherein the first plurality of pairwise comparisons comprise determining a cosine similarity from the cosine of the angle between each pair of evaluated vectors in the first plurality of pairwise comparisons (cosine similarity is a mathematical function), and wherein the first distribution comprises a first cumulative distribution function created by cumulating similarities that are measured between vectors of pairs of the first plurality of pairwise comparisons (cumulating distribution is a mathematical function);
creating a second distribution of a second plurality of pairwise comparisons of vectors, of the first set of vectors, which were generated from image pairs with dissimilar cell perturbations (creating a distribution from vector of data is a mathematical function); wherein the second plurality of pairwise comparisons comprise determining a cosine similarity from the cosine of the angle between each pair of evaluated vectors in the second plurality of pairwise comparisons (cosine similarity is a mathematical function), and wherein the second distribution comprises a second cumulative distribution function created by cumulating similarities that are measured between vectors of pairs of the second plurality of pairwise comparisons (cumulating distribution is a mathematical function);
determining a difference between the first distribution and the second distribution (determining a difference is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper),
using the difference to make a determination of goodness of the first deep learning model, as applied to the biological assay, in maintaining both consistency and diversity between biology in different images, of the plurality of images, when transforming cell biology of the images into the vectors of the first set of vectors (determining a difference and/or goodness is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper);
creating a third distribution of a third plurality of pairwise comparisons of vectors, of the second set of vectors, which were generated from image pairs with similar cell perturbations (creating a distribution from vector of data is a mathematical function);
creating a fourth distribution of a fourth plurality of pairwise comparisons of vectors, of the second set of vectors, which were generated from image pairs with similar dissimilar cell perturbations (creating a distribution from vector of data is a mathematical function);
determining a second difference between the third distribution and the fourth distribution (determining a difference is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper),
comparing the difference with the second difference to make a determination of goodness of the first deep learning model with respect to the second deep learning model (determining a difference and/or goodness is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper);
selecting between using the first deep learning model and the second deep learning model based on the comparison of the difference to the second difference (model selection is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper); and
adjusting an aspect of one of the first deep learning model and the second deep learning model based on the comparison of the difference to the second difference (adjust an aspect of a model is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper), wherein the processor analyzes both the selected deep learning model and the non-selected deep learning model for differences (difference analysis is an observation, evaluation mental process which can reasonably be performed in one’s mind with the aid of pencil and paper);
The claim recites an abstract idea.
Step 2A Prong 2: The judicial exceptions are not integrated into a practical application. The claim recites the following additional elements:
A non-transitory computer readable storage medium comprising instructions embodied thereon, which when executed, cause a processor to perform a method of determining a goodness of a deep learning model, comprising (amounts to generic computer components that are performing generic function of execution of stored instructions (MPEP 2106.05(f));
directing capture of a plurality of images of a biological assay involving perturbing cells in wells of at least one microplate, the images of biology of cells in the wells in which cells from the same cell line are placed in test wells of one or more microplates and cells in each test well are perturbed in one of two different ways such that some of the test wells contain cells perturbed in a first of the two different ways and some of the test wells contain cells perturbed in a second of the two different ways (amounts to mere insignificant application, an insignificant extra-solution activity as discussed in MPEP 2106.05(g));
such that the some of the pairwise comparisons are performed on pairs of vectors associated with cells that have been similarly perturbed in the first of the two different ways and others of the pairwise comparisons are performed on pairs of vectors associated with cells which have been similarly perturbed in the second of the two different ways (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
such that the each of the pairwise comparisons is performed on pairs of vectors where one of the vector in each of the pairs is associated with cells that have been perturbed in the first of the two different ways and the other vector in each of the pairs is associated with cells which have been dissimilarly perturbed in the second of the two different ways (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
wherein the difference is a measure of the vertical separation between the first cumulative distribution function and the second cumulative distribution function (amounts to generally linking the abstract ideas to the technological environment or field of use as discussed in in MPEP 2106.05(h));
accessing a second set of vectors representative of the images of the biological assay (acce