DETAILED ACTION
Status of Claims
This action is in reply to the application filed on 25 March 2025.
Claims 1 – 17 are currently pending and have been examined.
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 Objections
Claims 4 – 16 are objected to under 37 CFR 1.75(c) as being in improper form because a multiple dependent claim should refer to other claims in the alternative only, and/or, cannot depend from any other multiple dependent claim. See MPEP § 608.01(n). Accordingly, claims 4 – 16 have not been further treated on the merits.
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.
Claims 1 – 3 and 17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. a law of nature, a natural phenomenon, or an abstract idea), and does not include additional elements that either: 1) integrate the abstract idea into a practical application, or 2) that provide an inventive concept – i.e. element that amount to significantly more than the abstract idea. The Claims are directed to an abstract idea because, when considered as a whole, the plain focus of the claims is on an abstract idea.
Claim 1 is representative. Claim 1 recites:
A method of detecting cell types and their associated markers, the method comprising:
a. running a plurality of instances of an algorithm in a distributed system wherein each instance is configured according to the following steps:
i. receiving a two-dimensional input matrix M wherein each vertical vector of the input matrix represents a single cell and each value in the vector represents a feature expression corresponding to that single cell;
ii. initializing a parent solution set Si, S2,....,Sn from the matrix, where n is a predefined finite number, wherein the solution set comprises a plurality of solutions Si, S2,....,Sn derived from the matrix, wherein each solution S, has a set of randomly assigned cluster sets C,, C2, ... Ck of single cells, where k is the total number of clusters in a given solution;
iii. computing the fitness of each solution S, in the solution set using a fitness function, wherein the fitness function is derived from a plurality of objectives;
iv. applying genetic operators to the solution set to produce an offspring solution set;
v. computing the fitness of each solution in the offspring set using the fitness function;
vi. comparing the fitness of each solution in the solution set and the offspring set, wherein each solution with the highest fitness is retained in a new solution set for the next generation;
vii. repeating steps iii, iv, v and vi for a predetermined number of generations;
b. selecting the solution set with the highest fitness of the plurality of instances;
c. extracting the single cell clusters and features from the selected solution set.
Claim 17 recites a system that executes the steps of the method recited in Claim 1.
STEP 1
The claims are directed to a device, a method and non-transitory computer readable medium which are included in the statutory categories of invention.
STEP 2A PRONG ONE
The claims, as illustrated by Claim 1, recite limitations that encompass an abstract idea including:
The claims, as illustrated by Claim 1, recite limitations that encompass an abstract idea within the mathematical formula or relationship grouping including:
iii. computing the fitness of each solution S, in the solution set using a fitness function, wherein the fitness function is derived from a plurality of objectives;
v. computing the fitness of each solution in the offspring set using the fitness function;
vii. repeating steps iii and v for a predetermined number of generations;
The claims compute the “fitness” of each solution S in both a “parent solution set” and an offspring solution set, wherein each solution S, has a set of randomly assigned cluster sets C,, C2, ... Ck of single cells. The specification expressly discloses that the fitness function is a mathematic formula or relationship (P. 13-14). Calculating fitness is a mathematical relationship. As such, the claims recite a mathematical formula or relationship.
The claims, as illustrated by Claim 1, recite limitations that encompass an abstract idea within the “mental processes” grouping – concepts performed in the human mind including observation, evaluation, judgment and opinion including:
ii. initializing a parent solution set Si, S2,....,Sn from the matrix, where n is a predefined finite number, wherein the solution set comprises a plurality of solutions Si, S2,....,Sn derived from the matrix, wherein each solution S, has a set of randomly assigned cluster sets C,, C2, ... Ck of single cells, where k is the total number of clusters in a given solution;
vi. comparing the fitness of each solution in the solution set and the offspring set, wherein each solution with the highest fitness is retained in a new solution set for the next generation;
b. selecting the solution set with the highest fitness of the plurality of instances;
The claims compare a fitness value for each solution and selects the solution with the highest fitness score. The specification discloses this feature as comparing values. Comparing fitness values, and recognizing the highest value, is a process that, except for generic computer implementation steps, can be performed in the human mind. Initializing a parent solution involves randomly selecting clusters of cells. Selecting information by content or source for collection, analysis or display is an abstract mental process. (Electric Power Group) As such, the claims recite an abstract idea within the mental process grouping.
STEP 2A PRONG TWO
The claims recite limitations that include additional elements beyond those that encompass the abstract idea above including:
a. running a plurality of instances of an algorithm in a distributed system wherein each instance is configured according to the following steps:
i. receiving a two-dimensional input matrix M wherein each vertical vector of the input matrix represents a single cell and each value in the vector represents a feature expression corresponding to that single cell;
iv. applying genetic operators to the solution set to produce an offspring solution set; vii. repeating step iv for a predetermined number of generations;
c. extracting the single cell clusters and features from the selected solution set.
However, these additional elements do not integrate the abstract idea into a practical application of that idea in accordance with the MPEP. (see MPEP 2106.05)
The distributed system is recited at a high level of generality such that it amounts to no more than instructions to apply the abstract idea using a generic computer component. These elements merely add instructions to implement the abstract idea on a computer, and generally link the abstract idea to a particular technological environment.
Receiving an input matrix of vectors representing feature values for single cells, and initializing a random set of solutions for analysis is an insignificant extra-solution activity – i.e. a data gathering step. Similarly, applying genetic operators is disclosed in the specification as shuffling or adding cell vectors to a solution set, and is an insignificant extra-solution data gathering step. Extracting single cell clusters and features involves retrieving the cells included in the solution set having the highest fitness value.
Nothing in the claim recites specific limitations directed to an improved technology or technological process. A general purpose computer that applies a judicial exception by use of conventional computer functions, as is the case here, does not qualify as a particular machine, nor does the recitation of a generic computer impose meaningful limits in the claimed process. (see Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716-17 (Fed. Cir. 2014)). As such, the additional elements recited in the claim do not integrate the abstract solution set selection process into a practical application of that process.
STEP 2B
The additional elements identified above do not amount to significantly more than the abstract solution set selection process. The input matrix of vectors representing feature values for single cells is derived from “RNA or proteomics experiments following laboratory protocols” – i.e. “counts obtained from mRNA sequencing or protein expression”. In particular, the specification discloses obtaining this data from known, external data sources (@ Page 17) - indicating that obtaining such data is routine and conventional. Receiving information is a well-understood, routine and conventional computer function – i.e. receiving or transmitting data over a network as in Symantec, TLI, OIP and buySAFE.
Similarly, applying genetic operators to shuffle or add cell vectors to a solution set is a conventional technique in feature selection. For example, the claims compute and compare the “fitness” of a plurality of sets of single cell clusters, i.e. a solution set, each represented by a vector for each cell. The genetic operators modify the set of clusters by adding, or shuffling the vectors. This feature comprises a feature selection technique that is well-known and purely conventional; a fact for which Examiner takes Official Notice.
Extracting cell clusters from the selected solution involves obtaining the set of cell feature expression vectors assigned to the selected solution, and is ancillary to the abstract idea. Retrieving information is a routine and conventional computer function as in Versata and OIP Tech.
The additional structural elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than a recitation of generic computer structure (i.e. a distributed computing system). Each of the above components are disclosed in the specification as being purely conventional and/or known in the industry. Because the specification describes these additional elements in general terms, without describing particulars, Examiner concludes that the claim limitations may be broadly, but reasonably construed, as reciting well-understood, routine and conventional computer components and techniques. The specification describes the elements in a manner that indicates that they are sufficiently well-known that the specification does not need to describe the particulars in order to satisfy U.S.C. 112. Considered as an ordered combination the limitations recited in the claims add nothing that is not already present when the steps are considered individually. As such, the additional elements recited in the claim do not provide significantly more than the abstract solution set selection process, or an inventive concept.
The dependent claims add additional features including:
those that merely serve to further narrow the abstract idea above such as:
further limiting the number of objectives (Claim 2);
further limiting the type of data in the matrix (Claim 3);
The limitations recited in the dependent claims, in combination with those recited in the independent claims add nothing that integrates the abstract idea into a practical application, or that amounts to significantly more. As such, the additional element do not integrate the abstract idea into a practical application, or provide an inventive concept that transforms the claims into a patent eligible invention.
The apparatus claims are no different from the method claims in substance. “The equivalence of the method, system and media claims is readily apparent.” “The only difference between the claims is the form in which they were drafted.” (Bancorp). The method claims recite the abstract idea implemented on a generic computer, while the apparatus claims recite generic computer components configured to implement the same idea. Specifically, Claim 17 merely adds the generic hardware noted above that nearly every computer will include. The apparatus claim’s requirement that the same method be performed with a programmed computer does not alter the method’s patentability under U.S.C. 101 (In re Grams). Therefore, the claims are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 – 3 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Minshull et al.: (US PGPUB 2020/0283798 A1) in view of Malmgren et al.: (US 9,509,617 B1)
CLAIMS 1 and 17
Minshull discloses a system and method for identifying gene expression vectors that includes the following limitations:
A method of detecting cell types and their associated markers, the method comprising:
a. running an instance of an algorithm; (Minshull 0104); wherein each instance is configured according to the following steps:
i. receiving a two-dimensional input matrix M wherein each vertical vector of the input matrix represents a single cell and each value in the vector represents a feature expression corresponding to that single cell; ii. initializing a parent solution set Si, S2,....,Sn from the matrix, where n is a predefined finite number, wherein the solution set comprises a plurality of solutions Si, S2,....,Sn derived from the matrix, wherein each solution S, has a set of randomly assigned cluster sets C,, C2, ... Ck of single cells, where k is the total number of clusters in a given solution; (Minshull 0015, 0046, 0049, 0063, 0066, 0089, 0092, 0097, 0099, 0104, 0105).
Minshull discloses a system and method for relating genetic sequences of cells to functional activity that includes a genetic algorithm for receiving a two-dimensional input matrix of expression vectors for cells (i.e. a descriptor and a value), and constructing (i.e. initializing) a plurality of sequence element groups corresponding to functional categories comprising subsets of the expression vectors, (i.e. a parent solution set). The method applies initial weights to each of the subsets and modifies the initial weights in each successive iteration. In unsupervised learning, in particular for genetic algorithms, stochastic searches are known in the art, and are further disclosed in Minshull. Minshull further discloses the following limitations:
iii. computing the fitness of each solution S, in the solution set using a fitness function, wherein the fitness function is derived from a plurality of objectives; (Minshull 0018, 0019, 0098, 0099, 0100, 0104);
iv. applying genetic operators to the solution set to produce an offspring solution set; (Minshull 0020, 0106, 0107);
v. computing the fitness of each solution in the offspring set using the fitness function; (Minshull 0018, 0019, 0099, 0100);
vi. comparing the fitness of each solution in the solution set and the offspring set, wherein each solution with the highest fitness is retained in a new solution set for the next generation; (Minshull 0099, 0100, 0104, 0105, 0107);
vii. repeating steps iii, iv, v and vi for a predetermined number of generations; (Minshull 0020, 0105, 0107);
b. selecting the solution set with the highest fitness of the plurality of instances; (Minshull 0107);
c. extracting the single cell clusters and features from the selected solution set; (Minshull 0108).
Minshull discloses optimizing, using stochastic search techniques that are known in the art, by modifying the weights of the descriptors, describing the relative or absolute contribution of the respective element, in order to minimize a loss function (i.e. fitness). Stochastic searching involves scoring randomly generated subsets of candidate solutions. Minshull generates subsets by repeating the optimization step a plurality of times including adding new vector elements to subsets, (i.e. applying genetic operators), and repeating the process. Minshull finds the data set that best fits the function, and ranks the sequence elements that have the most effect on the output. The most advantageous combination of elements is identified (i.e. extracted) based on the elements assigned to the combination.
With respect to the following limitation:
a. running a plurality of an instances of an algorithm in a distributed system; (Malmgren col. 1 line 7 – 15, col. 3 line 8 – 15, col. 5 line 50 to col. 6 line 8)
Minshull discloses executing the method on a programmed computer “that can be operated in one or more locations” (@ 0109); but does not expressly disclose a distributed computing system. Here, Examiner asserts that distributed computer systems are notoriously old and well-known. Nonetheless, Examiner relies on Malmgren to teach executing (i.e. running) a plurality of instances of an algorithm in a distributed system. Distributed systems include a plurality of computing nodes representing computational resources such as servers, etc. Malmgren teaches that an algorithm is executed independently at each node. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the solution set selection method of Minshull so as to have included executing the algorithm in a distributed computer system, in accordance with the teaching of Malmgren, in order to allow for load distribution.
CLAIMS 2 and 3
The combination of Minshull/Malmgren discloses the limitations above relative to Claim 1. Additionally, Minshull discloses the following limitations:
wherein the fitness function is derived from two objectives; (Minshull 0097 – 0099).
Minshull discloses a fitness function that is derived from the type of element and the location on the vector, (i.e. two objectives).
wherein the matrix comprises raw count or log2 transcriptome or proteome data; (Minshull 0016, 0092 - 0094).
Minshull discloses a quantitative measure of gene expression.
CONCLUSION
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 5,897,629 A to Shinagawa et al. discloses a problem solver apparatus using a genetic algorithm and a stochastic search strategy to find the fittest candidate solution.
US PGPUB 2003/0191728 A1 to Kulkarni et al. discloses using a stochastic search technique foe genetic algorithms.
“A Unified Framework for Stochastic Optimization”; Powell, Warren B.; 26 July, 2018 discloses stochastic optimization techniques.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to John A. Pauls whose telephone number is (571) 270-5557. The Examiner can normally be reached on Mon. - Fri. 8:00 - 5:00 Eastern. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Robert Morgan can be reached at (571) 272-6773.
Official replies to this Office action may now be submitted electronically by registered users of the EFS-Web system. Information on EFS-Web tools is available on the Internet at: http://www.uspto.gov/patents/process/file/efs/guidance/index.jsp. An EFS-Web Quick-Start Guide is available at: http://www.uspto.gov/ebc/portal/efs/quick-start.pdf.
Alternatively, official replies to this Office action may still be submitted by any one of fax, mail, or hand delivery. Faxed replies should be directed to the central fax at (571) 273-8300. Mailed replies should be addressed to “Commissioner for Patents, PO Box 1450, Alexandria, VA 22313-1450.” Hand delivered replies should be delivered to the “Customer Service Window, Randolph Building, 401 Dulany Street, Alexandria, VA 22314.”
/JOHN A PAULS/Primary Examiner, Art Unit 3683
Date: 26 August, 2026
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