DETAILED ACTION 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. The following is a non-final, first office action on the merits, in response to application filed 9/8/2022. Claims 1-2, 5-33, 40-42 have been examined and are currently pending. Priority Acknowledgment is made of applicant's claim for a provisional application filed on 3/9/2020, 9/8/2020. The Applicant claims benefit of continuation of PCT/US2021/ 0 21282, filed on 3/8/2021. Receipt is acknowledged of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file. Response to Amendment The amendment filed on 9/8/2022 cancelled claim 3, 4, 34-39, 43-55. No claim was previously cancelled. No new claims are added. No claim has been amended. Claims 1- 2, 5-33, 40-42 are considered and pending. Information Disclosure Statement The information disclosure statement (IDS) submitted on 9/8/2022, 11/7/2024 follows the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Specification Modifications made to page 1 to the original specification are acknowledged. 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 1-2, 5-33, 40-42 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) without significantly more. Alice Corp. also establishes that the same analysis should be used for all categories of claims, regardless of a system/apparatus, a method, or a product claim. The claimed invention (Claims 1 - 2, 5-33, 40-42) is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) recite(s) abstract ideas including “Certain Methods of Organizing Human Activity”, “an idea “of itself”, which have been identified/found by the courts as abstract ideas in new 101 memos of the subject matter eligibility in here (https://www.uspto.gov/patent/laws-and-regulations/examination-policy/subject-matter-eligibility) including 2019 Revised Patent Subject Matter Eligibility Guidance. This judicial exception is not integrated into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because it/they is/are recited at a high level of generality and/or are recited as performing generic computer functions routinely used in the computer applications: Independent claim 1 (Step 2A, Prong I): is directed to multiple abstract ideas including “Certain Methods of Organizing Human Activity”, and “Mental process”. Claim 1, Steps of, (a) generating a universal integrated latent space representation by encoding variables derived from two or more types of data obtained from training and testing plant populations into latent vectors through a machine learning- based multi-modal variational autoencoder framework, wherein the two or more types of data comprise genomic data, exomic data, epigenomic data, transcriptomic data, proteomic data, metabolomic data, hyperspectral data, or phenomic data, or combinations thereof and wherein the latent space is independent of the underlying genomic, exomic , epigenomic, transcriptomic, proteomic, metabolomic, hyperspectral, or phenomic association; (b) decoding the integrated latent representation by a decoder to obtain reconstructed data for the training and testing plant populations; (c) inputting the reconstructed data from the training plant population and observed phenotype data for at least one phenotype of interest obtained from the training plant population to train a supervised learning model; (d) predicting the at least one phenotype of interest for one or more plants from the testing population by inputting the reconstructed data for the testing population into the trained supervised learning model; and (e) selecting the one or more plants from the testing population based on at least one predicted phenotype of interest. f all within “Certain Methods of Organizing Human Activity” grouping of abstract idea because these steps recite “ generating data representation, decoding data, inputting data, predicting data, selecting a plant based on predicted phenotype of interest ”, w hich are human activities and/or interactions between users/people/ and therefore, certain methods of organizing human activity which encompasses both certain activity of a single person, certain activity that involves multiple people, and certain activity between a person and a computer. In addition, claim 1, steps mentioned above also falls within the abstract “Mental Processes” grouping of abstract ideas since these limitation covers performance of the limitations in the mind. For example, a human being can o bserve/ generate data representation, can observe/encode/decode data, can observe input/collect data, can evaluate/predict data, can observe/ select a plant . Further, steps of ( “ inputting” ) are considered as “insignificant extra-solution activity” to the judicial exception since they are merely receiving/collecting/providing data . Independent claim 1, Step 2A (Prong II): Accordingly, the claim recites an abstract idea(s) as pointed out above. This judicial exception(s) is/are not integrated into a practical application. In particular, the claim recites additional element ( “autoencoder framework”, “ by a decoder ” ) that are not significant more than the abstract ideas. In particular, there is no machine/hardware/computer to actually perform the abstract steps mentioned above. Other than reciting “ by a decoder” which are programming instruction s , nothing in the claim element precludes the step from practically being performed in the mind, and is simply organized information through human activity or merely mental tasks, and is part of, or a related, judicial exception and does not meaningfully limit the application of the identified judicial exception, and as such does not constitute significantly more. There is no specificity regarding any technology, just broadly, execute the programming in structions to generate data, erode/decode data , input data , predict data, select a plant. There are no additional elements, for example, hardware processor of a machine to actually perform all of the steps at all. The steps are m ainly receiving /inputting data, decoding data, predicting data, selecting data. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Accordingly, there is neither improvement to another technology or technical field nor an improvement to the functioning of the computer itself, and does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Independent claim 1, (step 2B): The additional element “autoencoder framework”, “a decoder ”, is recited at a high level of generality, and add nothing of substance to the underlying abstract idea; thus, they are not significantly more than the identified abstract idea. Th is component is merely recited at a high level of generality and/or are recited as performing generic computer functions routinely used in the computer applications; thus, they are not significantly more than the identified abstract idea. Generic sensor/ computer components recited as performing generic sensing/ computer functions that are well-understood, routine and convention activities amount to no more than implementing the abstract idea with a computerized system. The use of generic computer components to receive/send/display information over communication network/internet does not impose any meaningful limit on the computer implementation of the abstract idea. At best, the claim(s) are merely providing an environment to implement the abstract idea. (see analysis in claim 1). Dependent claims 2 , 5-19 , are merely add further details of the abstract steps/elements recited in claim 1 without including an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, dependent claims 2 , 5-19 , are also non-statutory subject matter. Independent claim 20, 21 : Alice Corp. also establishes that the same analysis should be used for all categories of claims. Therefore, independent system/apparatus claim 20, and product claim 21 , are also rejected as ineligible subject matter under 35 U.S.C. 101 for substantially the same reasons as the method claim(s) 1 . Further, the components (i.e., a processor , a device, a computer-readable medium ) described in independent claims 20, 21 , add nothing of substance to the underlying abstract idea. Similarly, as it relates to the computer system claims, the limitations appear to be performed by a generic sensor/ computing system/device. These components are merely recited at a high level of generality and/or are recited as performing generic computer functions routinely used in the computer applications; thus, they are not significantly more than the identified abstract idea. Generic computer components recited as performing generic sensing/ computer functions that are well-understood, routine and convention activities amount to no more than implementing the abstract idea with a computerized system. The use of generic encoder/decoder / computer components to receive/access/identify/search/transmit/send/display information over communication network/internet does not impose any meaningful limit on the computer implementation of the abstract idea. At best, the claim(s) are merely providing an environment to implement the abstract idea. (see analysis in claim 1 ). According to MPEP 2106.05 (d), elements that the Courts have recognized as well-understood, routine, conventional activity in particular fields are e.g., "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); 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” (evidence required by Berkeimer memo). Further, according to Berkheimer memo 04/19/2018, section III.A.1, “A specification demonstrates the well-understood, routine, conventional nature of additional elements when it describes the additional elements as well-understood or routine or conventional (or an equivalent term), as a commercially available product, or in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a)”. Applicant’s Specification, [ 0025 ] indicate a general-purpose computer perform the instant steps and demonstrates the well-understood, routine, conventional nature of the information processing device (a processor/a memory/a computer) in any computing implementation. Thus, evidence has been provided to show these additional elements are well-understood, routine, conventional activity according to Berkheimer memo. Therefore, for the above-mentioned reasons, viewed as a whole, even in combination, the above steps do not amount to significantly more/do not provide an inventive concept. Similarly, Independent claim 22 (Step 2A, Prong I): is directed to multiple abstract ideas including “Certain Methods of Organizing Human Activity”, and “Mental process”. Claim 22 , Steps of, (a) receiving by a first neural network two or more types of input data obtained from a training population and a testing population, wherein the data comprises genomic data, exomic data, epigenomic data, transcriptomic data, proteomic data, metabolomic data, hyperspectral data, or phenomic data, or combinations thereof, wherein the first neural network comprises a multi-modal autoencoder, wherein the autoencoder comprises an multi-modal autoencoder and an multi-modal autodecoder ; (b) encoding by the multi-modal autoencoder the information from the two or more types of input data into latent vectors through a machine-learning based neural network training framework, wherein the latent space is independent of the underlying genomic, exomic , epigenomic, transcriptomic, proteomic, metabolomic, hyperspectral, or phenomic association; (c) training the decoder to learn to reconstruct the two or more types of input data using unsupervised learning based on an objective function for the encoded latent vectors; and (d) decoding by the decoder the encoded latent vectors into reconstructed input data; (e) receiving by a second neural network, wherein the second neural network comprises a supervised learning model, the reconstructed input data for the training population and observed phenotype data for at least one phenotype of interest obtained from the training population; (f) training the supervised learning model to learn to predict at least one phenotype of interest using the reconstructed input data for the training population and observed phenotype data for at least one phenotype of interest obtained from the training population; and (g) predicting the at least one phenotype of interest for one or more plants from the testing population by inputting the reconstructed input data from the testing population into a trained supervised learning model. f all within “Certain Methods of Organizing Human Activity” grouping of abstract idea because these steps recite “ receiving input data, en coding data, training the decoder , decoding data, predicting data, w hich are human activities and/or interactions between users /people/ and therefore, certain methods of organizing human activity which encompasses both certain activity of a single person, certain activity that involves multiple people, and certain activity between a person and a computer. In addition, claim 22 , steps mentioned above also falls within the abstract “Mental Processes” grouping of abstract ideas since these limitation covers performance of the limitations in the mind. For example, a human being can o bserve/ receive d ata, can observe/encode/decode data, can observe /train a model , can evaluate/predict data. Further, steps of ( “ receiving” ) are considered as “insignificant extra-solution activity” to the judicial exception since they are merely receiving/collecting/providing data . Independent claim 22 , Step 2A (Prong II): Accordingly, the claim recites an abstract idea(s) as pointed out above. This judicial exception(s) is/are not integrated into a practical application. In particular, the claim recites additional element ( “neural network”, “by an autoencoder”, “ by a decoder ” ) that are not significant more than the abstract ideas. In particular, there is no machine/hardware/computer to actually perform the abstract steps mentioned above. Other than reciting , “ by an autoencoder” / “ by a decoder”, nothing in the claim element precludes the step from practically being performed in the mind, and is simply organized information through human activity or merely mental tasks, and is part of, or a related, judicial exception and does not meaningfully limit the application of the identified judicial exception, and as such does not constitute significantly more. There is no specificity regarding any technology, just broadly, execute the programming in structions to receive data, erode/decode data, predict data, train data . The steps are m ainly receiving data, training data, encoding/decoder data, predicting data . The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Accordingly, there is neither improvement to another technology or technical field nor an improvement to the functioning of the computer itself, and does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Independent claim 22 , (step 2B): The additional element s “an autoencoder”, “a decoder”, are recited at a high level of generality, and add nothing of substance to the underlying abstract idea; thus, they are not significantly more than the identified abstract idea. Th is component is merely recited at a high level of generality and/or are recited as performing generic computer functions routinely used in the computer applications; thus, they are not significantly more than the identified abstract idea. Generic sensor/ computer components recited as performing generic sensing/ computer functions that are well-understood, routine and convention activities amount to no more than implementing the abstract idea with a computerized system. The use of generic computer components to receive/send/display information over communication network/internet does not impose any meaningful limit on the computer implementation of the abstract idea. At best, the claim(s) are merely providing an environment to implement the abstract idea. (see analysis in claim 1). Dependent claims 23-33, 40-42 , are merely add further details of the abstract steps/elements recited in claim 22 without including an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, dependent claims 2 3-33, 40-42 , are also non-statutory subject matter. Viewed as a whole, the claims (1-2, 5-33, 40-42) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Thus, the claims do NOT recite limitations that are “significantly more” than the abstract idea because the claims do not recite an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Thus, the claimed invention, as a whole, does not provide 'significantly more' than the abstract idea, and is non-statutory subject matter. Claim 2 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Examiner notes that claim 2 1 recites a computer readable medium co mprising instructions to perform the method. It is noted that the computer readable storage device discussed in the specification ([0075 ] ), under broad interpretation, it is understood to include transitory media and therefore is not in any of the statutory classes. Therefore, claim 2 1 is rejected under non-statutory subject matter. See MPEP 2106. Examiner suggests amending the claim to be “non-transitory” media/medium. Prior Art Rejection Independent claims 1, 20, 21, 22 , as a whole recite a combination of limitations that has Not been found as define over prior art of record (the combination of Rolfe et al. (US 2019/0244680 ), Regev et al. (US 20 22/0180975 ), Baumgarten et al. (US 20 20/0291489 ), Guo et al. (US 2021/0296753 ), Zhang et al. (US 2016/0155136), and Szeto ( WO-2019112966-A2 ), and NPL1, “ Zampieri G, Vijayakumar S, Yaneske E, Angione C. Machine and deep learning meet genome-scale metabolic modeling. PLoS Comput Biol. 2019 Jul 11;15(7 ):e 1007084. doi : 10.1371/journal.pcbi.1007084. PMID: 31295267; PMCID: PMC6622478. NPL2, “ Ubbens J, Cieslak M, Prusinkiewicz P, Parkin I, Ebersbach J, Stavness I. Latent Space Phenotyping: Automatic Image-Based Phenotyping for Treatment Studies. Plant Phenomics. 2020 Jan 20;2020:5801869 . doi : 10.34133/2020/5801869. PMID: 33313558; PMCID: PMC7706325. NPL 3, “ Pinaya WHL, Mechelli A, Sato JR. Using deep autoencoders to identify abnormal brain structural patterns in neuropsychiatric disorders: A large-scale multi-sample study ” . Hum Brain Mapp. 2019 Feb 15;40(3):944-954. doi : 10.1002/hbm.24423. Epub 2018 Oct 11. PMID: 30311316; PMCID: PMC6492107. (Year: 2018) NPL 4 , “ Autoencoding with a Classifier System, by Richard J. Preen, Stewart W. Wilson, Larry Bull, arXiv:1910.10579v 8 [ cs.NE] 12 May 2021 , and the other references teaches all the claimed features. The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. Athey et al. (US 2 020/0135337 , teaches utilizing machine learning and statistical techniques to predict drug response phenotypes for patients, and stratified cohorts of patients, based on their biological, ancestry, demographic, clinical, sociological, and environmental characteristics such as performing a bioinformatics analysis to filter the set of permissive candidate variants into a subset of intermediate candidate variants includes: evaluating g enomic regions around the set of permissive candidate variants for regulatory function . ). Athey (US 201 9/0172584 , teaches identifying pharmacological phenotypes using statistical modeling and machine learning techniques .) Allowable Subject Matter Claims 1-2, 5-33, 40-42 are deemed to be allowed in light of the specification, amendments filed on 9/8/2022 . As to the prior art rejections, upon further search and consideration, it is found that claims 1-2, 5-33, 40-42 are allowable subject to outstanding 101 rejections. As allowable subject matter has been indicated, applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with, and pending remedy to outstanding issues cited above. See 37 CFR 1.111(b) and MPEP § 707.07(a). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to SUN M LI whose telephone number is (571)270-5489. The examiner can normally be reached on Mon-Thurs, 8:30am--5pm. Fax is 571-270-6489. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. 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