DETAILED ACTION
The Applicant’s filing, received 02 March 2023, has been fully considered. The following rejections and/or objections constitute the complete set presently being applied to the instant application.
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
The preliminary amendment received 19 May 2023 has been accepted.
Claims 1-7, 9, 11, 13, 15, and 23-31 are pending.
Claims 1-7, 9, 11, 13, 15, and 23-31 are rejected.
Priority
This application claims benefit of 63/380,837, filed 25 October 2022,
and claims benefit of 63/315,962, filed 02 March 2022.
Therefore, the effective filing date of the claimed invention is 02 March 2022.
Information Disclosure Statement
The information disclosure statements (IDS) received 11 September 2024 and 04 September 2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements have been considered by the examiner.
Drawings
The drawings received 02 March 2023 are objected to as failing to comply with) 37 CFR 1.84(t) because:
The sheets of drawings should be numbered in consecutive Arabic numerals, starting with 1, within the sight as defined in paragraph (g) of this section, and the number of each sheet should be shown by two Arabic numerals placed on either side of an oblique line, with the first being the sheet number and the second being the total number of sheets of drawings, with no other marking.
The drawings received 02 March 2023 are further objected to as failing to comply with 37 CFR 1.84(p)(5) because:
Reference characters not mentioned in the description shall not appear in the drawings.
For example, reference character #215 appears in Fig. 2B, but does not appear in the written description.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-7, 9, 11, 13, 15, and 23-31 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "the enhancer-promoter pair" in line seven. There is insufficient antecedent basis for this limitation in the claim, because the claim previously recites “for the one or more enhancer-promoter pairs” in line four, and therefore it is not clear as to which of the one or more enhancer-promoter pairs is being referred to in line seven.
Claims 2-7, 9, 11, 13, 15, and 23-31 are indefinite for depending from claim 1 and for failing to remedy the indefiniteness of claim 1.
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 1-7, 9, 11, 13, 15, and 23-31 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: Step 1 of the eligibility analysis asks: Is the claim to a process, machine, manufacture or composition of matter?
Claims 1-7, 9, 11, 13, 15, and 23-31 recite a method (i.e., a process) of using a machine learning model to analyze features of enhancer-promoter pairs.
Therefore, these claims are encompassed by the categories of statutory subject matter, and thus, satisfy the subject matter eligibility requirements under step 1.
[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:
generating values for a plurality of features comprising a first set of features and a second set of features of the enhancer-promoter pair by:
generating values for the first set of features (i.e., mental processes and mathematical concepts); and
generating values for the second set of features engineered from subsets of the first set of features (i.e., mental processes and mathematical concepts);
applying a machine learning model to analyze the values for the plurality of features of the one or more enhancer-promoter pairs (i.e., mental processes and mathematical concepts); and
determining whether one of the one or more enhancer-promoter pairs is a functional enhancer-promoter pair based on an output of the machine learning model (i.e., mental processes).
Dependent claims 2-7, 9, 11, 13, 15, and 23-31 further recite the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas, as noted below.
Dependent claim 2 further recites:
the second set of features engineered from subsets of the first set of features comprise an enhancer contribution feature that quantifies relative contribution of the enhancer across a plurality of enhancers to a gene operably controlled by the promoter (i.e., mental processes).
Dependent claim 3 further recites:
the second set of features further comprise a composite feature of the enhancer representing a combination of an ATAC feature, an EP300 feature, a H3K4me1 feature, and a HiChIP feature (i.e., mental processes).
Dependent claim 4 further recites:
the enhancer contribution feature is a ratio of the composite feature of the enhancer to a combination of a plurality of composite features for the enhancer (i.e., mental processes and mathematical concepts).
Dependent claim 5 further recites:
the second set of features engineered from subsets of the first set of features comprise a gene contribution feature that quantifies relative contribution to a gene operably controlled by the promoter across a plurality of genes influenced by the enhancer (i.e., mental processes and mathematical concepts).
Dependent claim 6 further recites:
the second set of features further comprise a composite feature of the gene representing a combination of an ATAC feature, an EP300 feature, a H3K4me1 feature, and a HiChIP feature (i.e., mental processes).
Dependent claim 7 further recites:
the gene contribution feature is a ratio of the composite feature of the gene to a combination of a plurality of composite features for the gene (i.e., mental processes and mathematical concepts).
Dependent claim 9 further recites:
the second set of features comprise APMI, fracEnh, and fracGene features (i.e., mental processes).
Dependent claim 11 further recites:
the second set of features comprise APMI, fracEnh, fracGene, fracGmE, fracGpE, apmiGene, apmiEnh, apmiGmE, and apmiGpE features (i.e., mental processes).
Dependent claim 13 further recites:
the first set of features comprise features of ATAC, EP300, H3K4me1, HiChIP, and genomic distance (i.e., mental processes).
Dependent claim 15 further recites:
at least one feature of the second set has a higher feature importance value in comparison to at least one feature of the first set (i.e., mental processes and mathematical concepts).
Dependent claim 23 further recites:
the machine learning model is a random forest model (i.e., mathematical concepts).
Dependent claim 24 further recites:
the dataset comprises one or more of: chromatin accessibility data identifying chromatin-accessible regions across the genome; and chromatin binding data identifying chromatin interactions (i.e., mental processes).
Dependent claim 25 further recites:
the chromatin accessibility data comprises DNase-seq or ATAC-seq data (i.e., mental processes).
Dependent claim 26 further recites:
the chromatin binding data comprises data for one or more of: DNA-DNA interactions; chromatin domains; protein-chromatin binding sites; and transcription factor binding motifs (i.e., mental processes).
Dependent claim 27 further recites:
the chromatin binding data comprising HiChIP or ChIP-seq data (i.e., mental processes).
Dependent claim 28 further recites:
the chromatin binding data comprises data for one or more active enhancer marks (i.e., mental processes).
Dependent claim 29 further recites:
the one or more active enhancer marks comprise EP300, H3K27ac, or H3K4me1 (i.e., mental processes).
Dependent claim 30 further recites:
the chromatin binding data comprises data for one or more repressive factors (i.e., mental processes).
Dependent claim 31 further recites:
the one or more repressive factors comprise H3K27me3, H3K9me3, H4K20me1, NCOR1, HDAC1/2/3, EZH2, SUZ12, ZEB2, or REST (i.e., mental processes).
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 pen and paper (e.g., determining whether one of the one or more enhancer-promoter pairs is a functional enhancer-promoter pair based on an output of the machine learning model), 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 (e.g., applying a machine learning model to analyze the values for the plurality of features of the one or more enhancer-promoter pairs) are abstract ideas irrespective of whether or not the limitations are practical to perform in the human mind.
Therefore, claims 1-7, 9, 11, 13, 15, and 23-31 recite an abstract idea.
[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.
Dependent claims 2-7, 9, 11, 13, 15, and 23-31 do not recite any elements in addition to the judicial exception, and thus are part of the judicial exception.
The additional elements in independent claim 1 include:
a computer; and
obtaining a dataset comprising epigenomic data for one or more enhancer-promoter pairs (i.e., obtaining data).
Regarding the additional element of a computer, to the extent that the claim as a whole provides machine learning on a computer, there is no evidence of record that the claims as a whole or the method steps actually require a computer or that they somehow affect the function of the computer beyond performing the calculations or analysis of data, and therefore, the claim invokes a computer merely as a tool for use in the claimed process, such that it amounts to no more than mere instructions to apply the exceptions using a generic computer (MPEP 2106.05(f)), and therefore is not an improvement to computer functionality itself, or an improvement to any other technology or technical field, and thus, does not integrate the judicial exceptions into a practical application (MPEP 2106.04(d)(1)).
The additional element of obtaining a dataset comprising epigenomic data for one or more enhancer-promoter pairs (i.e., obtaining data) is merely a pre-solution activity of gathering data for use in the claimed process – a nominal or tangential addition to the claims that does not meaningfully limit the claims, and therefore does not add more than insignificant extra-solution activity to the judicial exceptions (MPEP 2106.05(g)).
Thus, the additionally recited elements merely invoke a computer as a tool; and/or amount to insignificant extra-solution activity; and as such, when all limitations in claims 1-7, 9, 11, 13, 15, and 23-31 have been considered as a whole (i.e., the analysis takes into consideration all the claim limitations and how those limitations interact and impact each other when evaluating whether the exception is integrated into a practical application), the claims are deemed to not recite any additional elements that would integrate a judicial exception into a practical application, and therefore claims 1-7, 9, 11, 13, 15, and 23-31 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.
Dependent claims 2-7, 9, 11, 13, 15, and 23-31 do not recite any elements in addition to the judicial exception(s).
The additional elements recited in independent claim 1 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).
Given the breadth of the claims, the teachings of the specification, and limitations presented in the claims such as “applying a machine learning model,” under step 2B the claims are being evaluated as a method of analysis performed using a computer. Thus, the additional elements of a computer and obtaining data are conventional computer components and/or functions (see MPEP at 2106.05(b) and 2106.05(d)(II) regarding conventionality of computer components and computer processes).
Therefore, when taken alone (i.e., individually), all additional elements in claims 1-7, 9, 11, 13, 15, and 23-31 do not amount to significantly more than the above-identified judicial exception(s). Even when evaluated as an ordered combination, the additional elements fail to transform the exception(s) into a patent-eligible application of that exception. Thus, claims 1-7, 9, 11, 13, 15, and 23-31 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.
Claims 1, 2, 4, 5, 7, 9, 11, 15, and 23-31 are rejected under 35 U.S.C. 103 as being unpatentable over Whalen et al. (“Enhancer-promoter interactions are encoded by complex genomic signatures on looping chromatin.” Nature Genetics, 2016, vol. 48, no. 5, pp. 488-496) and Liu et al. (“EPIHC: Improving Enhancer-Promoter Interaction Prediction by Using Hybrid Features and Communicative Learning.” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2022 (Date of publication 02 September 2021), vol. 19, no. 6, pp. 3435-3443) and Schmidt et al. (“Integrative prediction of gene expression with chromatin accessibility and conformation data.” Epigenetics & Chromatin, 2020, vol. 13:4, pp. 1-17).
Independent claim 1 is broadly directed to a method for using a machine learning model to determine whether enhancer-promoter pairs are functional based on a generated dataset comprising first and second sets of features wherein the second set of features are engineered from a subset of the first set of features.
Dependent claims 2, 4, 5, 7, 9, 11, 15, and 23-31 further define the attributes of the data used with the machine learning model, and further define attributes of the model.
Whalen et al. is broadly directed to an algorithm that integrates hundreds of genomics data sets to identify the minimal subset of features necessary to accurately predict individual enhancer-promoter interactions across the genome.
Liu et al. is broadly directed to a deep learning-based enhancer-promoter interaction prediction method that uses hybrid features, including both sequence-derived features and genomic features.
Schmidt et al. is broadly directed to investigating whether promoter-enhancer interactions inferred from chromatin conformation capture experiments or computational approaches can be meaningfully utilized in gene expression modeling.
Regarding independent claim 1, Whalen et al. shows obtaining hundreds of diverse data sets for pairs of enhancers and promoters of expressed genes found to have significant Hi-C interactions (positives), as well as random pairs of enhancers and promoters without significant interactions (negatives) (Figure 4); generating lists of features for all enhancer-promoter pairs in each cell line using functional genomics data such as measures of open chromatin, DNA methylation, gene expression, and ChIP-seq peaks for transcription factors, architectural proteins, and modified histones (page 489, col. 1, bottom), and quantified signals at the promoter, at the enhancer, and in the genomic window between them, and also computed features for conserved synteny of the enhancer and promoter, as well as the similarity of transcription factor and target gene annotations (page 489, col. 2, para. 1), and further created a ‘combined’ data set by pooling the enhancer-promoter pairs and features from four cell lines, wherein only features measured in all four cell lines were retained (page. 489, col. 2, para. 2); and a machine-learning pipeline to quantitatively model the interaction status of enhancer-promoter pairs as a function of their genomic features (page 490, col. 1, para. 2).
Regarding independent claim 1, Whalen et al. does not show features engineered from subsets of features; or determining whether an enhancer-promoter pair is a functional enhancer-promoter pair.
Regarding independent claim 1, Liu et al. shows a machine learning model for predicting enhancer-promoter interactions using hybrid features (Title; and Abstract) and further shows combining features from sequence data and genomic data to obtain hybrid features (page 3438, col. 1, Section 2.2.3) and further shows for an enhancer-promoter pair, several ways of fusing features of the enhancer and promoter (page 3437, col. 2, Section 2.2.2).
Regarding independent claim 1, Schmidt et al. shows that despite the availability of promoter-enhancer interaction data derived from chromatin conformation data, it has not yet been integrated into computational methods inferring gene expression using experimentally or computationally determined transcription binding events, and further shows investigating whether promoter-enhancer interactions can be meaningfully utilized in gene expression modelling (page 3, col. 1, para. 1).
Regarding dependent claims 2, 4, 5, and 7, Liu et al. further shows enhancer features and promoter features weighted by their contribution to the enhancer-promoter communication (page 3437, col. 1, bottom).
Regarding claims 9 and 11, Liu et al. does not show the particular engineered features, but Liu et al. does show combining features from the different data sets (i.e., sequence data and genomic data) to obtain hybrid features (page 3438, col. 1, Section 2.2.3).
Regarding dependent claim 15, Liu et al. further shows a feature analysis of the hybrid features that include genomic features and sequence-derived features, and figuring out the importance of the hybrid features (page 3439, col. 2, Section 3.4.1).
Regarding dependent claim 23, Liu et al. further shows that earlier machine learning-based methods included random forest-based enhancer-promoter interaction prediction models (page 3435, col. 2, para. 1).
Regarding dependent claims 24, 25, 26, 27, 28, 29. 30, and 31, Whalen et al. further shows data sets including DNase-seq (claims 24 and 25) (Figure 4); data sets including ChIP-seq (claims 26 and 27) (Figure 4); epigenetic marks comprising H3K27ac and H3K4me1 (claims 28 and 29) (Figure 8); and repressive factors comprising H4K20me1 and H3K9me3 (claims 30 and 31) (Figure 8).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Whalen et al. by incorporating methods for engineering hybrid features for improving enhancer-promoter interaction prediction, as shown by Liu et al. and discussed above. One of ordinary skill in the art would have been motivated to combine the methods of Whalen et al. with the methods of Liu et al., because Liu et al. shows that hybrid features are able to enhance the performance of prediction models. This modification would have had a reasonable expectation of success given that both Whalen et al. and Liu et al. disclose methods for predicting enhancer-promoter interactions.
It would have been further prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Whalen et al. by incorporating methods for determining whether promoter-enhancer interaction inferred from chromatin data can be meaningfully utilized in gene expression modelling (i.e., determining whether a promoter-enhancer interaction is a functional interaction), as shown by Schmidt et al. and discussed above. One of ordinary skill in the art would have been motivated to combine the methods of Whalen et al. with the methods of Schmidt et al., because Schmidt et al. shows that despite the availability of promoter-enhancer interaction, it has not yet been integrated into computational methods inferring gene expression using experimentally or computationally determined transcription factor binding events. This modification would have had a reasonable expectation of success given that both Whalen et al. and Schmidt et al. disclose methods for distinguishing between interacting and non-interacting promoter-enhancer pairs to reveal true enhancer targets.
Claims 3, 6, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Whalen et al. and Liu et al. and Schmidt et al. as applied to claims 1, 2, 4, 5, 7, 9, 11, 15, and 23-31 above, and further in view of Giaimo et al. (“A Comprehensive Toolbox to Analyze Enhancer-Promoter Functions.” Enhancers and Promoters: Methods and Protocols, Methods in Molecular Biology, 2021, vol. 2351, pp. 3-22).
Dependent claims 3, 6, and 13 further define the engineered features of the second set of features.
Regarding dependent claims 3, 6, and 13, Whalen et al. and Liu et al. and Schmidt et al. as applied to claims 1, 2, 4, 5, 7, 9, 11, 15, and 23-31 above, do not show the second set of features further comprise a composite feature of the enhancer representing a combination of an ATAC feature, an EP300 feature, a H3K4me1 feature, and a HiChIP feature (claim 3); second set of features further comprise a composite feature of the gene representing a combination of an ATAC feature, an EP300 feature, a H3K4me1 feature, and a HiChIP feature (claim 6); or the first set of features comprise features of ATAC, EP300, H3K4me1, HiChIP, and genomic distance (claim 13).
Regarding dependent claims 3, 6, and 13, Whalen et al. and Liu et al. and Schmidt et al. as applied to claims 1, 2, 4, 5, 7, 9, 11, 15, and 23-31 above, further show composite features and first and second sets of features, as discussed above, and further show using genomic distance as a feature (e.g., Whalen et al. shows interacting enhancer-promoter pairs were assigned on the basis of the distance between the enhancer and the promoter (Online Methods, col. 1, para. 2).
Regarding dependent claims 3, 6, and 13, Giaimo et al. shows histone marks enrichment represent predictors of promoters and enhancers (e.g., ATAC-Seq, EP300, and H3K4me1) (Fig. 2); and further shows techniques for gathering data representing long-range chromatin interactions (e.g., Hi-C) (page 11) and combining the principle of the Hi-C with the one of the ChIP (page 12).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method shown by Whalen et al. and Liu et al. and Schmidt et al. as applied to claims 1, 2, 4, 5, 7, 9, 11, 15, and 23-31 above, by incorporating methods for utilizing chromatin structure data for monitoring enhancer-promoter contacts, as shown by Giaimo et al. and discussed above. One of ordinary skill in the art would have been motivated to combine the methods of Whalen et al. and Liu et al. and Schmidt et al. as applied to claims 1, 2, 4, 5, 7, 9, 11, 15, and 23-31 above, with the methods of Giaimo et al., because Giaimo et al. shows that the binding of transcription factors to enhancers allow recruitment of chromatin modulators that interact with the RNA polymerase II that is bound to the promoter, and that this communication leads to chromatin looping and gene activation. This modification would have had a reasonable expectation of success given that both Whalen et al. and Liu et al. and Schmidt et al. as applied to claims 1, 2, 4, 5, 7, 9, 11, 15, and 23-31 above, and Giaimo et al. disclose methods for analyzing enhancer-promoter functions.
Conclusion
No claims are allowed.
This Office action is a Non-Final action. A shortened statutory period for reply to this action is set to expire THREE MONTHS from the mailing date of this application.
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/S.W.B./Examiner, Art Unit 1687
/Joseph Woitach/Primary Examiner, Art Unit 1687
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