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. Status of the Claims Claim s 1-20 are currently pending and under exam herein. Claim s 1-20 are rejected. Priority The instant application claims priority from Provisional application #63/263,138 filed on 10/27/2021 . Thus, the effective filing date of the instant application is 10/27/2021. Drawings The Drawings filed on 10/26/2022 were considered. Information Disclosure Statement The information disclosure statement s (IDS) submitted on 03/27/2023 and 01/26/2026 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement has been considered by the examiner. 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite: (a) mathematical concepts, (e.g., mathematical relationships, formulas or equations, mathematical calculations); and (b) mental processes, i.e., concepts performed in the human mind, (e.g., observation, evaluation, judgement, opinion). Subject matter eligibility evaluation in accordance with MPEP 2106: Eligibility Step 1: Claims 1-20 are directed to a method and system to determine a pets kinship relation . [Step 1: YES] Eligibility Step 2A : First it is determined in Prong One whether a claim recites a judicial exception, and if so, then it is determined in Prong Two whether the recited judicial exception is integrated into a practical application of that exception. Eligibility Step 2A Prong One : In determining whether a claim is directed to a judicial exception, examination is performed that analyzes whether the claim recites a judicial exception, i.e., whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. Independent claim 1 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: training the machine-learning model to predict at least one familial relationship from the at least one DNA sequence, the training further comprising: for each of the at least one DNA sequence, extracting at least one local DNA fragment pattern from a database, the at least one local DNA fragment pattern corresponding to the at least one matching companion pet ( mental process ) analyzing the at least one local DNA fragment pattern to determine at least one predicted familial relationship between the companion pet and the at least one matching companion pet (mental process) based on the analyzing, determining at least one predicted familial relationship and at least one corresponding confidence level. (mental process) D ependent claim 2 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: wherein the at least one local DNA fragment pattern includes a plurality of IBD (identical-by-descent) fragments. ( mental process , mathematics ) D ependent claim 3 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: determining a proportion of the at least one DNA sequence that contains the plurality of IBD fragments in only one of two sets of chromosomes ( mental process , mathematics) D ependent claim 4 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: the analyzing further comprising: determining a proportion of the at least one DNA sequence that contains the plurality of IBD fragments in both of two sets of chromosomes (mental process , mathematics) D ependent claim 5 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: the analyzing further comprising: determining a proportion of the at least one DNA sequence that does not contain any of the plurality of IBD fragments. (mental process , mathematics) D ependent claim 6 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: the analyzing further comprising: analyzing the plurality of IBD fragments to determine a total number of IBD fragments within the at least one local DNA fragment pattern (mental process , mathematics) D ependent claim 7 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: the analyzing further comprising: analyzing the plurality of IBD fragments to determine a total length of the plurality of IBD fragments within the at least one local DNA fragment pattern (mental process , mathematics) D ependent claim 8 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: wherein the total length of the plurality of IBD fragments is measured in centimorgans (mental process , mathematics) D ependent claim 9 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: the training further comprising: determining that the at least one local DNA fragment pattern indicates an overlap of at least one trait; and (mental process , mathematics) D ependent claim 11 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: wherein the at least one predicted familial relationship includes at least one of a mom, a dad, a sister, a brother, an uncle, an aunt, a niece, a nephew, a cousin, a grandfather, a grandmother, a grandson, a granddaughter, a great-grandfather, a great-grandmother, a great-grandson, a great- granddaughter, a half mom, a half dad, a half sister , a half brother , a half uncle, a half aunt, a half niece, a half nephew, a half cousin, a half grandfather, a half grandmother, a half grandson, a half granddaughter, a half great-grandfather, a half great- grandmother, a half great-grandson, or a half great-granddaughter. (mental process , mathematics) D ependent claim 13 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: determining further comprising: outputting a list of matching DNA companion pet samples, wherein each of the matching DNA companion pet samples meet or surpass a matching threshold (mental process , mathematics) D ependent claim 14 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: the training further comprising: determining a homozygosity-by-descent level for the companion pet and for the at least one matching companion pet, the homozygosity-by-descent level indicating a level of inbreeding. (mental process , mathematics) D ependent claim 15 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: the analyzing further comprising: analyzing the at least one local DNA fragment pattern to determine whether the at least one local DNA fragment pattern occurs on one set of chromosomes or both sets of chromosomes of the companion pet (mental process ) D ependent claim 16 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: upon the receiving, training the machine-learning model to predict at least one familial relationship from the at least one DNA sequence, the training further comprising: for each of the at least one DNA sequence, extracting at least one local DNA fragment pattern from a database, the at least one local DNA fragment pattern corresponding to the at least one matching companion pet; (mental process ) a nalyzing the at least one local DNA fragment pattern to determine at least one predicted familial relationship between the companion pet and the at least one matching companion pet (mental process ) based on the analyzing, determining at least one predicted familial relationship and at least one corresponding confidence level (mental process ) D ependent claim 17 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: a nalyzing the at least one local DNA fragment pattern to determine whether the at least one local DNA fragment pattern occurs on one set of chromosomes or both sets of chromosomes of the companion pet (mental process ) D ependent claim 18 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: wherein the at least one predicted familial relationship includes at least one of a mom, a dad, a sister, a brother, an uncle, an aunt, a niece, a nephew, a cousin, a grandfather, a grandmother, a grandson, a granddaughter, a great-grandfather, a great-grandmother, a great-grandson, a great- granddaughter, a half mom, a half dad, a half sister , a half brother , a half uncle, a half aunt, a half niece, a half nephew, a half cousin, a half grandfather, a half grandmother, a half grandson, a half granddaughter, a half great-grandfather, a half great- grandmother, a half great-grandson, or a half great-granddaughter (mental process ) Ind ependent claim 19 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: upon the receiving, training the machine-learning model to predict at least one familial relationship from the at least one DNA sequence, the training further comprising: for each of the at least one DNA sequence, extracting at least one local DNA fragment pattern from a database, the at least one local DNA fragment pattern corresponding to the at least one matching companion pet (mental process ) analyzing the at least one local DNA fragment pattern to determine at least one predicted familial relationship between the companion pet and the at least one matching companion pet (mental process ) based on the analyzing, determining at least one predicted familial relationship and at least one corresponding confidence level (mental process ) D ependent claim 20 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas: wherein the at least one predicted familial relationship includes at least one of a mom, a dad, a sister, a brother, an uncle, an aunt, a niece, a nephew, a cousin, a grandfather, a grandmother, a grandson, a granddaughter, a great-grandfather, a great-grandmother, a great- grandson, a great-granddaughter, a half mom, a half dad, a half sister , a half brother , a half uncle, a half aunt, a half niece, a half nephew, a half cousin, a half grandfather, a half grandmother, a half grandson, a half granddaughter, a half great-grandfather, a half great-grandmother, a half great-grandson, or a half great-granddaughter. (mental process ) The abstract ideas recited in the claims are evaluated under the broadest reasonable interpretation (BRI) of the claim limitations when read in light of and consistent with the specification. As noted in the foregoing section, the claims are determined to contain limitations that can practically be performed in the human mind with the aid of a pencil and paper, and therefore recite judicial exceptions from the mental process grouping of abstract ideas. Additionally, the recited limitations that are identified as judicial exceptions from the mathematical concepts grouping of abstract ideas are abstract ideas irrespective of whether or not the limitations are practical to perform in the human mind. Therefore, claims 1-20 recite an abstract idea as the dependent claims will inherit the abstract ideas from the independent claims. [Step 2A Prong One: YES] Eligibility Step 2A Prong Two : In determining whether a claim is directed to a judicial exception, further examination is performed that analyzes if the claim recites additional elements that when examined as a whole integrates the judicial exception(s) into a practical application (MPEP 2106.04(d)). A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The claimed additional elements are analyzed to determine if the abstract idea is integrated into a practical application (MPEP 2106.04(d)(I); MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the abstract idea, the claim fails to integrate the abstract idea into a practical application (MPEP 2106.04(d)(III)). The judicial exceptions identified in Eligibility Step 2A Prong One are not integrated into a practical application because of the reasons noted below. The additional element in independent claim 1 includes: a computer-implemented method for using companion pet DNA information to train a machine-learning model to predict a familial relationship of a companion pet receiving companion pet DNA information, the companion pet DNA information including at least one DNA sequence, at least one matching companion pet, and at least one familial label corresponding to the familial relationship between the companion pet and the at least one matching companion pet The additional element in dependent claim 9 includes: outputting a notification indicating that the at least one trait was shared with the at least one matching companion pet The additional element in dependent claim 10 includes: wherein the at least one trait is breed-specific. The additional element in dependent claim 12 includes: wherein the companion pet DNA information further includes whether one or both sets of chromosomes match and a number of DNA fragments that match the at least one matching companion pet. The additional element in in dependent claim 16 includes: A computer system for using companion pet DNA information to train a machine- learning model to predict a familial relationship of a companion pet, the computer system comprising: at least one memory storing instructions; and at least one processor configured to execute the instructions to perform operations comprising: r eceiving companion pet DNA information, the companion pet DNA information including at least one DNA sequence, at least one matching companion pet, and at least one familial label corresponding to a relationship between the companion pet and the at least one matching companion pet The additional element in ind ependent claim 19 includes: A non-transitory computer-readable medium containing instructions that, when executed by a processor, cause the processor to perform operations for using companion pet DNA information to train a machine-learning model to predict a familial relationship of a companion pet, receiving companion pet DNA information, the companion pet DNA information including at least one DNA sequence, at least one matching companion pet, and at least one familial label corresponding to a relationship between the companion pet and the at least one matching companion pet; The additional elements of receiving companion pet DNA information, the companion pet DNA information including at least one DNA sequence, at least one matching companion pet, and at least one familial label corresponding to a relationship between the companion pet and the at least one matching companion pet (Claim 19) receiving companion pet DNA information, the companion pet DNA information including at least one DNA sequence, at least one matching companion pet, and at least one familial label corresponding to a relationship between the companion pet and the at least one matching companion pet (Claim 16) wherein the companion pet DNA information further includes whether one or both sets of chromosomes match and a number of DNA fragments that match the at least one matching companion pet. (Claim 12) receiving companion pet DNA information, the companion pet DNA information including at least one DNA sequence, at least one matching companion pet, and at least one familial label corresponding to the familial relationship between the companion pet and the at least one matching companion pet (Claim 1) are insignificant extra-solution activity that are art of the data gathering process used in the recited judicial exceptions (see MPEP 2106.05(g)). The additional elements of a non-transitory computer-readable medium containing instructions that, when executed by a processor, cause the processor to perform operations for using companion pet DNA information to train a machine-learning model to predict a familial relationship of a companion pet, (Claim 19) a computer system for using companion pet DNA information to train a machine- learning model to predict a familial relationship of a companion pet, the computer system comprising: at least one memory storing instructions; and at least one processor configured to execute the instructions (Claim 16) a computer-implemented method for using companion pet DNA information to train a machine-learning model to predict a familial relationship of a companion pet (Claim 1) are just mere use of a computer (2106.06 (f)) and are mere instructions to apply an exception 2106.05(f) ( 2) ( Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks ( e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea a s well as just applying an abstract idea to a particular field See MPEP 2106.05(h) – vi. Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016) ) The additional elements of outputting a notification indicating that the at least one trait was shared with the at least one matching companion pet (Claim 9) wherein the at least one trait is breed-specific. (Claim 10) are just mere use of a computer (2106.06 (f)) and are mere instructions to apply an exception 2106.05(f) ( 2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks ( e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea as well as just applying an abstract idea to a particular field See MPEP 2106.05(h) – vi. Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016); Claims 2-9, 11, 13-15, 17-18, 19 do not recite any elements in addition to the judicial exception, and thus are part of the judicial exception. Thus, the additionally recited elements merely invoke a computer as a tool, and/or amount to insignificant extra-solution data gathering activity, and as such, when all limitations in claims 1-20 have been considered as a whole , the claims are deemed to not recite any additional elements that would integrate a judicial exception into a practical application, and therefore claims 1-20 are directed to an abstract idea (MPEP 2106.04(d)). [Step 2A Prong Two: NO] Eligibility Step 2B : Because the claims recite an abstract idea, and do not integrate that abstract idea into a practical application, the claims are probed for a specific inventive concept. The judicial exception alone cannot provide that inventive concept or practical application (MPEP 2106.05). Identifying whether the additional elements beyond the abstract idea amount to such an inventive concept requires considering the additional elements individually and in combination to determine if they amount to significantly more than the judicial exception (MPEP 2106.05A i -vi). The claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception(s) because of the reasons noted below. The additional elements recited in claims 1-20 are identified above, and carried over from Step 2A : Prong Two along with their conclusions for analysis at Step 2B . Any additional element or combination of elements that was considered to be insignificant extra-solution activity at Step 2A : Prong Two was re-evaluated at Step 2B , because if such re-evaluation finds that the element is unconventional or otherwise more than what is well-understood, routine, conventional activity in the field, this finding may indicate that the additional element is no longer considered to be insignificant; and all additional elements and combination of elements were evaluated to determine whether any additional elements or combination of elements are other than what is well-understood, routine, conventional activity in the field, or simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, per MPEP 2106.05(d). The additional elements of receiving companion pet DNA information, the companion pet DNA information including at least one DNA sequence, at least one matching companion pet, and at least one familial label corresponding to a relationship between the companion pet and the at least one matching companion pet (Claim 19) receiving companion pet DNA information, the companion pet DNA information including at least one DNA sequence, at least one matching companion pet, and at least one familial label corresponding to a relationship between the companion pet and the at least one matching companion pet (Claim 16) wherein the companion pet DNA information further includes whether one or both sets of chromosomes match and a number of DNA fragments that match the at least one matching companion pet. (Claim 12) receiving companion pet DNA information, the companion pet DNA information including at least one DNA sequence, at least one matching companion pet, and at least one familial label corresponding to the familial relationship between the companion pet and the at least one matching companion pet (Claim 1) are conventional and part of the data gathering process used in the recited judicial exceptions (see MPEP 2106.05(g)). Evidence for conventionality is shown by 2106.05(d) . The courts have found receiving and storing data to be conventional ( i . Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); v. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93 as well as v. Analyzing DNA to provide sequence information or detect allelic variants, Genetic Techs. Ltd., 818 F.3d at 1377; 118 USPQ2d at 1546; ) The additional elements of a non-transitory computer-readable medium containing instructions that, when executed by a processor, cause the processor to perform operations for using companion pet DNA information to train a machine-learning model to predict a familial relationship of a companion pet, (Claim 19) a computer system for using companion pet DNA information to train a machine- learning model to predict a familial relationship of a companion pet, the computer system comprising: at least one memory storing instructions; and at least one processor configured to execute the instructions (Claim 16) a computer-implemented method for using companion pet DNA information to train a machine-learning model to predict a familial relationship of a companion pet (Claim 1) are conventional. Evidence for conventionality is shown by MPEP 2106.05(d) . v. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93 as well as v. Analyzing DNA to provide sequence information or detect allelic variants, Genetic Techs. Ltd., 818 F.3d at 1377; 118 USPQ2d at 1546; ) additional evidence for conventionality is shown by 2106.06 (f)) and as the claims are mere instructions to apply an exception 2106.05(f) ( 2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks ( e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea as well as just applying an abstract idea to a particular field See MPEP 2106.05(h) – vi. Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016); The additional elements of outputting a notification indicating that the at least one trait was shared with the at least one matching companion pet (Claim 9) wherein the at least one trait is breed-specific. (Claim 10) are conventional. Evidence for conventionality is shown by MPEP 2106.05(d) . v. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93 as well as v. Analyzing DNA to provide sequence information or detect allelic variants, Genetic Techs. Ltd., 818 F.3d at 1377; 118 USPQ2d at 1546; ) additional evidence for conventionality is shown by 2106.06 (f)) and as the claims are mere instructions to apply an exception 2106.05(f) ( 2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks ( e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea as well as just applying an abstract idea to a particular field See MPEP 2106.05(h) – vi. Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016); Claims 2-9, 11, 13-15, 17- 20 do not recite any elements in addition to the judicial exception . Therefore, when taken alone, all additional elements in claims 1-20 do not amount to significantly more than the above-identified judicial exception(s). Even when evaluated as a combination, the additional elements fail to transform the exception(s) into a patent-eligible application of that exception. Thus, claims 1-20 are deemed to not contribute an inventive concept, i.e., amount to significantly more than the judicial exception(s) (MPEP 2106.05(II)). [Step 2B : NO] Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 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 . This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention. Claims 1-2 , 7- 11 , 13 , 16 , 18 -20 are rejected under 35 U.S.C. 103 as being unpatentable over Ball et al. ( Ball et al. AncestryDNA Matching White Paper Discovering Genetic Matches across a Massive, Expanding Genetic Database , March 31, 2016 ) in further view of Curik et al. ( C urik et al. Genomic Dissection of Inbreeding Depression: A Gate to New Opportunities. Revista Brasileira de Zootecnia 2017 , 46 (9), 773–782 ) in further view of Hayward et al. ( Hayward et al. Complex Disease and Phenotype Mapping in the Domestic Dog. Nature Communications 2016 , 7 (1) ) . The italicized text corresponds to the instant claim limitations. With respect to the limitations of Claim 1 , 16 , 19 , Ball et al. teaches that t o develop a machine learning method for accurately estimating relationships from IBD, we use genetic data from thousands of pairs of individuals with known family relationships (either real people with documented pedigrees or simulated individuals with known pedigrees). Additionally, we use other information beyond IBD inferred from genetic data to ensure that our estimates of close relationships—specifically, parent-child and sibling relationships—are as accurate as possible. (pg. 9, paragraph 3 : receiving companion pet DNA information, the companion pet DNA information including at least one DNA sequence, at least one matching companion pet, and at least one familial label corresponding to the familial relationship between the companion pet and the at least one matching companion pet (Claim 1) receiving companion pet DNA information, the companion pet DNA information including at least one DNA sequence, at least one matching companion pet, and at least one familial label corresponding to a relationship between the companion pet and the at least one matching companion pet (Claim 16) , receiving companion pet DNA information, the companion pet DNA information including at least one DNA sequence, at least one matching companion pet, and at least one familial label corresponding to a relationship between the companion pet and the at least one matching companion pet (Claim 19)). Ball et al. also teaches t he first goal of DNA matching is to accurately identify the DNA segments on the 22 chromosome pairs that are identical-by-descent between pairs of individuals. Importantly, we would like to identify these IBD segments for every pair of customers in our database. Doing this accurately as well as efficiently for millions of people is not a trivial problem, and is an active area of research in the scientific community (pg. 5 paragraph 2 - pg. 6, paragraph 1, and upon the receiving, training the machine-learning model to predict at least one familial relationship from the at least one DNA sequence, the training further comprising: for each of the at least one DNA sequence, extracting at least one local DNA fragment pattern from a database, the at least one local DNA fragment pattern corresponding to the at least one matching companion pet; (Claim 1) upon the receiving, training the machine-learning model to predict at least one familial relationship from the at least one DNA sequence, the training further comprising: for each of the at least one DNA sequence, extracting at least one local DNA fragment pattern from a database, the at least one local DNA fragment pattern corresponding to the at least one matching companion pet (Claim 16) upon the receiving, training the machine-learning model to predict at least one familial relationship from the at least one DNA sequence, the training further comprising: for each of the at least one DNA sequence, extracting at least one local DNA fragment pattern from a database, the at least one local DNA fragment pattern corresponding to the at least one matching companion pet (Claim 19)) Ball et al. also teaches that to identify IBD segments, we use this information to estimate how people are related to one another (e.g., first cousins). By drawing connections between relatives through their DNA, we offer the opportunity for AncestryDNA members to expand their documented pedigrees (pg. 2, paragraph 3, analyzing the at least one local DNA fragment pattern to determine at least one predicted familial relationship between the companion pet and the at least one matching companion pet (claim 1) analyzing the at least one local DNA fragment pattern to determine at least one predicted familial relationship between the companion pet and the at least one matching companion pet (claim 16) analyzing the at least one local DNA fragment pattern to determine at least one predicted familial relationship between the companion pet and the at least one matching companion pet (Claim 19)) Ball et al. also teaches that to consider the case when two individuals are estimated to share 1,000 cM IBD. According to our simulations, it is very likely that these two individuals are separated by exactly 4 reproductive events, such as first cousins (see Figure 5.2). Therefore, we could report this relationship estimate with high confidence. On the other hand, consider the case when two individuals share 650 cM IBD. In this situation, we cannot be certain whether the two individuals are separated by 4 or 5 reproductive events; for example, they could be first cousins, or first cousins once removed. This uncertainty is accentuated for more distant relationships and demonstrated by the greater amount of overlap of the corresponding probability density curves in Figure 5.2. We account for greater uncertainty in more distant relationships when delivering estimates to customers by reporting a range of possible relationships (e.g., third to fourth cousins). Figure 5.2 also shows probability based on total IBD length (pg. 32 and pg. 33, paragraph 2, and based on the analyzing, determining at least one predicted familial relationship and at least one corresponding confidence level. (Claim 1) based on the analyzing, determining at least one predicted familial relationship and at least one corresponding confidence level (Claim 16) based on the analyzing, determining at least one predicted familial relationship and at least one corresponding confidence level (Claim 19) ). With respect to the limitations of Claim 2 , Ball et al. teaches that to consider the case when two individuals are estimated to share 1,000 cM IBD. According to our simulations, it is very likely that these two individuals are separated by exactly 4 reproductive events, such as first cousins (see Figure 5.2). Therefore, we could report this relationship estimate with high confidence. On the other hand, consider the case when two individuals share 650 cM IBD. In this situation, we cannot be certain whether the two individuals are separated by 4 or 5 reproductive events; for example, they could be first cousins, or first cousins once removed. This uncertainty is accentuated for more distant relationships and demonstrated by the greater amount of overlap of the corresponding probability density curves in Figure 5.2. We account for greater uncertainty in more distant relationships when delivering estimates to customers by reporting a range of possible relationships (e.g., third to fourth cousins). Figure 5.2 also shows probability based on total IBD length (pg. 32 and pg. 33, paragraph 2, wherein the at least one local DNA fragment pattern includes a plurality of IBD (identical-by-descent) fragments (Claim 2)). With respect to the limitations of Claim s 7 -8 , Ball et al. teaches that their f igure 5.3 shows the empirical distribution of two matching statistics—total detected IBD, and an additional statistic that provides an estimate of the proportion of the genome that is “ IBD2 .” With total IBD alone (the vertical axis in Figure 5.3), we can determine with near-perfect accuracy whether a pair of individuals are parent-child or full siblings. By contrast, full siblings and half siblings show a great deal of overlap in total IBD shared, so we cannot determine as accurately whether a pair of individuals are full siblings or half siblings. However, when we consider the total IBD and IBD2 statistics jointly, in Figure 5.3 we observe that these data clearly separate parent-child pairs from full siblings, and greatly improve the separation of full siblings and half siblings. Therefore, by using both matching statistics simultaneously, we achieve nearly 100% accuracy in distinguishing close relationships—identical twins, parent-child, full siblings, and half siblings. IBD length is measured in centimorgans (pg. 34, paragraph 2 and pg. 32 Figure 3.2, the analyzing further comprising: analyzing the plurality of IBD fragments to determine a total length of the plurality of IBD fragments within the at least one local DNA fragment pattern (Claim 7) wherein the total length of the plurality of IBD fragments is measured in centimorgans (Claim 8). With respect to the limitations of Claim 11 , 18 , 20 Ball et al. teaches that w ith total IBD alone we can determine with near-perfect accuracy whether a pair of individuals are parent-child or full siblings (pg. 34, paragraph 2, wherein the at least one predicted familial relationship includes at least one of a mom, a dad, a sister, a brother, an uncle, an aunt, a niece, a nephew, a cousin, a grandfather, a grandmother, a grandson, a granddaughter, a great-grandfather, a great-grandmother, a great-grandson, a great- granddaughter, a half mom, a half dad, a half sister , a half brother , a half uncle, a half aunt, a half niece, a half nephew, a half cousin, a half grandfather, a half grandmother, a half grandson, a half granddaughter, a half great-grandfather, a half great- grandmother, a half great-grandson, or a half great-granddaughter (claim 11) , wherein the at least one predicted familial relationship includes at least one of a mom, a dad, a sister, a brother, an uncle, an aunt, a niece, a nephew, a cousin, a grandfather, a grandmother, a grandson, a granddaughter, a great-grandfather, a great-grandmother, a great-grandson, a great- granddaughter, a half mom, a half dad, a half sister , a half brother , a half uncle, a half aunt, a half niece, a half nephew, a half cousin, a half grandfather, a half grandmother, a half grandson, a half granddaughter, a half great-grandfather, a half great- grandmother, a half great-grandson, or a half great-granddaughter (Claim 18) , wherein the at least one predicted familial relationship includes at least one of a mom, a dad, a sister, a brother, an uncle, an aunt, a niece, a nephew, a cousin, a grandfather, a grandmother, a grandson, a granddaughter, a great-grandfather, a great-grandmother, a great- grandson, a great-granddaughter, a half mom, a half dad, a half sister , a half brother , a half uncle, a half aunt, a half niece, a half nephew, a half cousin, a half grandfather, a half grandmother, a half grandson, a half granddaughter, a half great-grandfather, a half great-grandmother, a half great-grandson, or a half great-granddaughter (Claim 20)). With respect to the limitations of Claim 13 , Ball et al. teaches that a n important feature of our method is that we do not keep track of all matching segments; in step 5, we filter out a candidate match if its genetic distance is less than 6 cM. The cutoff of 6 cM was chosen after considering several factors. The first factor is data storage. Since the number of matching segments grows exponentially with decreasing length, we dramatically reduce the storage requirements of our matching database by increasing the cutoff. A second, and more critical, factor is that the accuracy of IBD detection drops rapidly with decreasing IBD length—that is, the shorter the length of the detected IBD segment (expressed in genetic distance), the less likely it is that the detected chromosome segment is truly inherited from a common ancestor (pg. 18 paragraph 2 – pg. 19 paragraph 1) Ball et al. does not explicitly teach Determining familial relationship in pets A computer-implemented method for using companion pet DNA information to train a machine-learning model to predict a familial relationship of a companion pet the method comprising (Claim 1), the training further comprising (Claim 1) using pet DNA (Claim 1) determining that the at least one local DNA fragment pattern indicates an overlap of at least one trait (Claim 9) ; and outputting a notification indicating that the at least one trait was shared with the at least one matching companion pet (Claim 9) wherein the at least one trait is breed-specific (claim 10), the training further comprising: determining a homozygosity-by-descent level for the companion pet and for the at least one matching companion pet, the homozygosity-by-descent level indicating a level of inbreeding (Claim 14) a computer system for using companion pet DNA information to train a machine- learning model to predict a familial relationship of a companion pet, the computer system comprising: at least one memory storing instructions; and at least one processor configured to execute the instructions to perform operations comprising (Claim 16) a non-transitory computer-readable medium containing instructions that, when executed by a processor, cause the processor to perform operations for using companion pet DNA information to train a machine-learning model to predict a familial relationship of a companion pet, the operations comprising (Claim 19) However, these limitations were known in the art at the time of the effective filing date of the invention, as taught by Curik et al. in view of Hayward et al. With respect to the limitations of Claims 1 , 16, 19 , Curik et al. teaches a that In the context of shifting from infinitesimal (with dominance) toward oligogenic and mixed inheritance models, new approaches and ideas on how to estimate contribution of inbreeding depression for small regions or individual genes are needed. Recently, three different approaches have been used. In the first approach, an extension of the whole genome inbreeding depression estimation, the whole chromosomes or chromosomal segments divided into pieces were modelled in a classical approach as covariates . In the second approach, an extension of a genome-wise association analysis, each SNP was jointly modelled for the ROH status (0/1) and gene substitution effect . This approach was upgraded that approach by searching for interactions between ROH showing inbreeding depression, using sophisticated regression tree analysis generated by Gradient Boosted Machine algorithm. The machine learning algorithms are analyzing DNA and are inherently run on a computer, a computer-implemented method for using companion pet DNA information to train a machine-learning model to predict a familial relationship of a companion pet the method comprising (Claim 1), the training further comprising (Claim 1) a computer system for using companion pet DNA information to train a machine- learning model to predict a familial relationship of a companion pet, the computer system comprising: at least one memory storing instructions; and at least one processor configured to execute the instructions to perform operations comprising (Claim 16) , a non-transitory computer-readable medium containing instructions that, when executed by a processor, cause the processor to perform operations for using companion pet DNA information to train a machine-learning model to predict a familial relationship of a companion pet, the operations comprising (Claim 19) With respect to the limitations of Claims 1 4 , Curik et al. teaches that a ny diploid individual is inbred if its chromosomal segments located on homologous chromosome pairs, one from each parent, are identical by descent. Inbred individuals arise as a consequence of inbreeding or, at its most restrictive and classical definition, mating of parents that are more closely related than a randomly sampled couple chosen from that population . In populations with finite size, inbreeding is unavoidable and changes genotype frequencies by increasing homozygosity at the expense of heterozygosity, while leaving allele frequencies unaffected . This explains the relationship of h omozygosity-by-descent refers to the phenomenon where an individual possesses two identical alleles at a given locus that are descended from a single source. (pg. 773, col. 1, paragraph 1 , the training further comprising: determining a homozygosity-by-descent level for the companion pet and for the at least one matching companion pet, the homozygosity-by-descent level indicating a level of inbreeding. With respect to the limitations of Claims 9, 10, Hayward et al . teache s that f or the breed-mapped phenotype of fur length, we used a 1 (short hair) to 5 (long hair) phenotypic scale and identified a novel locus on CFA1 ( P¼2.2 10 12, b¼0.16 , Wald test) in addition to the known fur genes FGF5 (located on CFA32 , P¼3.1 10 44, b¼0.31 , Wald test) and RSPO2 (located on CFA13 , P¼2.0 10 28, b¼0.26 , Wald test). This most associated variant at the novel CFA1 locus (at 24,430,748) is a missense mutation in MC5R that changes the ancestral alanine to the boxer reference threonine ( A237T ), and was included as a custom marker on the CanineHD array because it was observed to be segregating in village dog whole-genome sequences. The MC5R protein sequence is evolutionarily conserved across mammals, and we find evidence that the A237T mutation causes a conformational change in the tertiary structure of the protein, with a change in binding site that is ‘probably damaging’ ( Polyphen -2 HumDiv¼0.992 ). MC5R is expressed in human sebaceous glands and is involved in the production of sebum in mice, affecting water repellency and thermo-regulation. While functional studies are needed to determine whether this variant is indeed the causal mutation at this QTL, the identification of a third coat length locus improves our understanding of furtype genetics in the dog and hypothesizes a relationship between sebum production and fur type in some breeds. Longer-haired breeds (for example, Maltese, Old English Sheepdog) are homozygous for the derived FGF5 allele, with the presence of the ancestral RSPO2 allele distinguishing medium–long from long hair . Shorter-haired breeds (for example, Bull Terrier, Greyhound) have the ancestral FGF5 allele and the derived MC5R allele, while medium-haired breeds (for example, Akita, Pembroke Welsh Corgi) have the ancestral MC5R allele (Fig. 4b ). MC5R and RSPO2 were also significantly associated with fur shedding ( P¼5.9 10 17, b¼0.057 , Wald test, and P¼9.8 b¼0.047,Wald test, respectively; Minimal-shedding breeds (for example, Poodle, Bichon Frise ´) are homozygous for the derived RSPO2 allele. Heavy-shedding breeds (for example, Akita, Alaskan Malamute) are homozygous for the ancestral MC5R allele in the presence of the ancestral RSPO2 allele, while medium-shedding breeds (for example, Cocker Spaniel, Pug) have the derived MC5R allele in the presence of the ancestral RSPO2 allele . This work specifically discusses pet bree