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 .
Status of the Claims
The claim set received 22 December 2022 has been entered into the application.
Claims 1-39 are pending.
Priority
This Application claims benefit to U.S Provisional Application 63/292,066 filed 22 December 2021.
Drawings
The drawings were received on 22 December 2022. These drawings are accepted. It is noted the drawings received 22 December 2022 contain color drawings. However, the Applicant has provided black and white copies of the drawings.
Specification
The specification received 22 December 2022 has been entered into the application.
Claim Rejections - 35 USC § 112
35 USC § 112(b)
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.
Claim 21 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 21 recites “further comprising using the number of distinctive n-mers or a parameter derived therefrom to predict changes in prevalence.” The claim is rendered indefinite because the claim attempts to claim a process (i.e., using number of distinct n-mers or a parameter derived therefrom to predict changes in prevalence) without setting forth any steps involved in the process of using number of distinct n-mers or a parameter derived therefrom to predict changes in prevalence. See MPEP 2173.05(q). It is recommended to amended to the such that to provide how the numbers and parameters are used for predicting changes in prevalence.
Furthermore, claim 21 recite “…a parameter derived therefrom to predict changes in prevalence.” The metes and bounds of the limitation are indefinite because it is not clear what parameter therefrom is being utilized. It is not clear if the number is of a distinct n-mers, a distribution(s), or divergence is to be considered a parameter. The specification does not provide examples or embodiments such that to limits as to what a “parameter” is to encompasses. It is recommended to amended the claim to provide as what is considered a parameter and/or cancel the claimed limitation. It is noted any amendments should be consistent with and supported by the specification.
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 1-39 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Step 1: Process, Machine, Manufacture or Composition
Claims 1-21 are drawn to a method, so a process
Claims 22-30 are drawn to a system, so a machine.
Claims 31-39 are drawn to a computer-readable medium (CRM), so a manufacture.
Step 2A Prong I - Identification of an Abstract Idea
Claim 1 is drawn to a method, and claim 22 is drawn to a system while claim is drawn to CRM. However, the claims recite similar limitations and are therefore examined similarly.
Claims 1, 22, and 30 recite:
identifying a plurality of combinations of biological sequences, wherein each combination comprises one of the plurality of biological sequences from each of the biological datasets
This step can be performed in the human mind to observe and evaluate biological sequences (i.e., nucleic data) to identify combinations of biological sequences and is therefore an abstract idea.
for each combination of biological sequences: generating a plurality of n-mers for each biological sequence of the combination using a sliding window with length n,
This step can be performed in the human mind by organizing information (i.e., biological sequence/nucleic acid data/n-mer) for generating n-mers based on sliding window length and is therefore an abstract idea.
comparing the plurality of n-mers for each biological sequence of the combination with the plurality of n-mers for the other biological sequences of the combination,
This step can be performed in the human mind by observing and evaluating information (n-mers of biological sequences and other biological sequences) for comparing nucleic acid data (i.e., n-mers) and is therefore an abstract idea.
identifying distinctive n-mers for each biological sequence of the combination which are not present among the plurality of n-mers for the other biological sequences of the combination
This step can be performed in the human mind by observing and evaluating distinct n-mers to identify distinctive n-mers not present in other combinations of biological sequences and is therefore an abstract idea.
determining a number of distinctive n-mers for at least one biological sequence of the combination
This step can be performed in the human mind by organizing information (i.e., number of distinctive n-mers) to determine a number of distinctive n-mers for a biological sequence combination and is therefore an abstract idea. This encompasses performing mathematical computations (i.e., determining a number of distinctive n-mers) for biological sequence combinations which reads on abstract ideas.
Claims 2-21, 23-30, and 32-39 are further drawn to limitations that describe the abstract ideas of claim 1 and are therefore also abstract ideas.
Step 2A Prong Two: Consideration of Practical Application
Claims 1, 22, and 31 do not recite any additional element which integrates the recited judicial exception into a practical application.
Here, in the instant case, the claims merely set forth a method of data analysis determining a number of distinctive n-mers for a biological sequence combination. As such, practicing the claims merely results in determining a number of distinctive n-mers. Such a result only produces information and does not provide for a practical application in the physical-realm of physical things and acts, i.e., the claims do not utilize the data generated by the judicial exception to affect any type of change. See MPEP 2106.04(a)(2)(A)(iv). Therefore, the claims do not utilize the measured
This judicial exception is not integrated into a practical application because the claims do not meet any of the following criteria:
An additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
Step 2B: Consideration of Additional Elements and Significantly More
The claimed method also recites "additional elements" that are not limitations drawn to an abstract idea.
The recited additional element of using computer processes, equipment and components of claims of claims 22-39 does not add significantly more than the recited judicial exception because using computer elements to analyze, process, and store abstract ideas is tangential to the claimed invention and is deemed well-known and conventional. See MPEP 2106.05(b), 2106.05(d)(II), and 2106.05(g).
The recited additional element of data gathering by receiving data of claims 1, 22, and 20 receiving step does not add significantly more than the recited judicial exception because receiving data (i.e., nucleic acid data) that is subsequently analyzed by the abstract ideas is deemed a well-known and conventional extra-solution activity. See MPEP 2106.05(d)(II) and 2106.05(g).
In conclusion, and when viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea recited in the instantly presented claims into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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.
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.
Claim(s) 1-6, 8-20, and 22-39 are rejected under 35 U.S.C. 103 as being unpatentable over Baptista et al. (US Patent Pub No.: US 2008/0003565, Patent Pub Date: 03 January 2008) in in view of Zhou et al. (US Patent Pub No.: US 2007/0244652, Patent Pub Date: 18 October 2007).
Claim 1 is drawn to a method, and claim 22 is drawn to a system while claim 31 is drawn to CRM. However, the claims recite similar limitations and are therefore examined similarly.
Claim 1 recites receiving a plurality of biological sequence datasets, wherein each of the biological sequence datasets comprises a plurality of biological sequences.
Claim 1 recites identifying a plurality of combinations of biological sequences, wherein each combination comprises one of the plurality of biological sequences from each of the biological datasets
Claim 1 recites for each combination of biological sequences generating a plurality of n-mers for each biological sequence of the combination using a sliding window with length n,
Claim 1 recites comparing the plurality of n-mers for each biological sequence of the combination with the plurality of n-mers for the other biological sequences of the combination,
Claim 1 recites identifying distinctive n-mers for each biological sequence of the combination which are not present among the plurality of n-mers for the other biological sequences of the combination
Claim 1 recites determining a number of distinctive n-mers for at least one biological sequence of the combination.
Baptista et al. (Baptista) discloses a method for designing n-mers for inclusion in a viral microarray. Baptista discloses “non-conserved sequences" or "non-conserved nucleic acid sequences" refers to nucleic acid sequences that are distinct between multiple species within a genus, and preferably between various viral strains within a species.” [Baptista, page 6, left col para 0051]. Baptista discloses downloading genome sequences from NCBI [Baptista, claim 23], as instant claim 1 receiving a plurality of biological sequence datasets, wherein each of the biological sequence datasets comprises a plurality of biological sequences.
Baptista discloses determining nucleic acid sequences of the detected hybridized nucleic acids (i.e., datasets of combinations of biological sequences) and comparing the sequences with a database to identify the virus or new subtype virus [Baptist, claim 20]. Baptista discloses the term "viral nucleotides" include sequences identical or complementary to viral sequences, for example from the sequences defined by the GenBank numbers included in Table 1 and the sequences in Table 2 (i.e., plurality of biological sequences from each of the biological datasets) [Baptista, page 7 left col], as in instant claim 1 identifying a plurality of combinations of biological sequences, wherein each combination comprises one of the plurality of biological sequences from each of the biological datasets.
Baptista discloses identifying overlapping probes with the length of n-mer base pairs and a moving window of 8 to 12 base pairs [Baptista, claim 23, page 6 right col para 0057], as in instant claim 1 for each combination of biological sequences generating a plurality of n-mers for each biological sequence of the combination using a sliding window with length n.
Baptista discloses performing BLAST comparison for all probes against each other, wherein each the most conserved and non-conserved pairs of probes are selected for the microarray [Baptista, claim 23]. Baptista discloses the invention analyzing the sequences of the detected hybridized sample nucleic acids and comparing the sequences with a database to confirm the identity of the bound sequence or identify the virus or new subtype virus [Baptista, page 2 left col para 0018], as in instant claim 1 comparing the plurality of n-mers for each biological sequence of the combination with the plurality of n-mers for the other biological sequences of the combination. Here, performing BLAST is an analysis for aligning/comparing nucleic acid sequences.
Baptist discloses the term detection and/or detect," or variations thereof as used herein is understood to mean looking for a specific indicator of the presence of one or more nucleic acids bound to a specific location on the solid support corresponding to a specific n-mer [Baptist page 4 left col para 0041]. Baptist discloses the nucleic acid microarray or viral microarray refers to a collection of n-mer oligonucleotide that can be prepared either synthetically or biosynthetically and can be used to test for hybridization of nucleic acids from samples suspected of containing viral nucleic acids [Baptist page 5 left col para 0045]. Baptist discloses testing Flu Mist ® for viral contamination (i.e., viral sequences and/or viruses). Baptist discloses DNA was isolated from the Flu Mist ®, and said DNA Flu Mist ® was subsequently subjected to microarray analysis of the claimed invention (i.e., microarray of n-mers/combination of n-mers). Baptist discloses the labeled nucleic acid sequences (i.e., combinations of biological sequences) hybridized to influenza sequences as expected. Importantly, Baptist discloses detecting labeled nucleic acids that bound to seven human herpes virus 6 (HHV6) sequences and two human herpes virus sequences (i.e., identified distinctive n-mer/k-mers). Baptist discloses “rescuing” the labeled sequences for subsequent PCR and sequencing processing to confirm the sequences were HHV6 [Baptist pages 9-10 para 0095-0097]. Baptist discloses analyzing a sample containing a combination of different sequences (i.e., Flu Mist ® influenza vaccine sequences) using a microarray comprising a combination of sequences (i.e., n-mers for multiple influenza sequences), and identifying sequences not present among the n-mer of the other biological sequence combination (i.e., HHV6 sequences). Next, the “labeled nucleic acid sequences” were subsequently “isolated/rescued” and were identified as distinctly associated with HHV6. Thus, the method of Baptist was able to identify and detect n-mer sequences from contaminants which would otherwise not be contained and/or present within a Flu Mist ® shot/vaccine [Baptist pages 9-10 para 0095-0097], as in instant claim 1 identifying distinctive n-mers for each biological sequence of the combination which are not present among the plurality of n-mers for the other biological sequences of the combination. Here, the microarray (i.e., sequence combination) would inherently contain the “distinct n-mer/k-mer” use to label and identify the HHV6 contaminant. Although Baptist does not disclose the specific n-mer that labeled HHV6, it is obvious the label was only label able to distinctly bind to HHV6, thus, identifying a distinct n-mer. As such, the Flu Mist ® testing of Baptist reads on identifying distinctive n-mers for each biological sequence of the combination (i.e., the HHV6 contaminants of the Flu Mist ®) which would not otherwise be present among the plurality of n-mers for the other biological sequences of the combination (i.e., Flu Mist ® vaccine).
Dependent claim(s): 2, 10-11, 13-15, 18-19, 25-27, 30, 34-36, and 39
Baptista discloses using n-mer oligonucleotides [Baptista, page 4 right col para 0043], as in instant claim 2.
Baptista discloses determining nucleic acid sequences of detected hybridized nucleic acids and comparing the sequences with a database to identify the virus or new subtype virus [Baptista, claim 17]. Baptista discloses sequencing of nucleic acids that hybridize to the microarrays and analysis of the hybridized sequences with existing databases, thus identifying existing or new subtypes of viruses [Baptista, page 1 right col para 007]. Baptista discloses the invention can facilitate in the discovery of new virus [Baptista, page 3 left para 0031], as in claim 10. Thus, because the method of Baptista utilize hybridized sequences, downloads of the viral data from NCBI as of May 2, 2006, and compares the data to databases it is obvious the n-mer data set would contain or could contain a n-mer dataset containing a new viral variant sequence.
Baptista discloses using n-mer the length of 8-12 base pairs [Baptista, claim 23], about 10 base pairs and 4-6 base pairs [Baptista, claim 24-25]. Baptista discloses the n-mer of the present invention are preferably 60 to 70 nucleotides in length, however, other lengths are possible [Baptista, page 4 right col para 0044]. Baptist discloses the term nucleic acid microarray or viral microarray refers to the intentionally created collection of n-mers oligonucleotides that can be prepared either synthetically or biosynthetically and can be used to test for hybridization of nucleic acids from samples suspected of containing viral nucleic acids. Baptist discloses the term “array” is meant to include those libraries of nucleic acids that can be prepared by spotting nucleic acids of essentially any length (for example, from 1 to about 1000 nucleotide monomers in length) onto a substrate [Baptist page 5 left col para 0045], as in instant claims 11, 13-14, 25-26, and 34-35. Here, Baptista discloses n-mers of 3-10 because they disclose n-mer length 8-12. Baptista teaches lengths upto 12 but does not teach lengths 12-30 as in the range required in claim 13. However, Baptista discloses preferred lengths of 60-70 and using spotting nucleic acids essentially of any length (i.e., from 1 to 1000 monomer (i.e., 1-mer)). Baptista, therefore, makes obvious modifying length of n-mers which would make other lengths such as 12 to 30.
Baptist discloses downloading identical or complementary conserved and non-conserved regions of all known viruses as of May 2, 2006 NCBI [Baptista, claim 23], as instant claim 15, 27, and 36. Thus, it would obvious the downloaded dataset(s) would encompass common/similar dataset of n-mers two more nucleic acid sequence combinations.
Baptista discloses using Hela cells infected with human papilloma virus (HPV), JSC-1 cells with Epstein-Barr virus (EBV), and BCBL-1 cell with harbors Kaposi's sarcoma associated herpesvirus (KSHV) [Baptista, page 6 left col para’s 0028-0030]. Baptista discloses analyzing HPV in tissues of Cervical Intraepithelial Neoplasia’s (CIN 1/2/3) cancer patients and detecting the viruses [Baptista, page 10 para’s 0098-0103. Baptist discloses downloading nucleotide sequences of n-mer nucleotides that are identical, complementary to conserved and not conserved regions of all known viruses as of May 2, 2006 [Baptista, claim 23], as in instant claim 18, 30, and 39. Baptist discloses using a dataset of all known viruses. Here, since the downloaded sequences (i.e., sequence dataset) of all viruses inherently contains different strains/variants of viruses (i.e., HHV6, HHV3, bacteriophage) which infect different species (i.e., human, insects, bacteria), it is obvious the datasets of Baptiste could/would encompass datasets with different viral variants.
Baptista discloses using Hela cells infected with human papilloma virus (HPV), JSC-1 cells with Epstein-Barr virus (EBV), and BCBL-1 cell with harbors Kaposi's sarcoma associated herpesvirus (KSHV) [Baptista, page 6 left col para’s 0028-0030]. Baptista discloses analyzing HPV in tissues of Cervical Intraepithelial Neoplasia’s (CIN 1/2/3) cancer patients and detecting the viruses [Baptista, page 10 para’s 0098-0103]. Baptista discloses the sample is of viral stock and a cell line [Baptista, claims 21-22]. Baptist discloses a complex population of nucleic acids can comprise viral and host nucleic acids [Baptist page 5 right col para 0050], as in claim 19. Here, although Baptist does not explicitly disclose specific viral/host datasets, Baptist does disclose processing both viral and host nucleic acids using enrichments methods [Baptist page 5 right col para 0050] which would subsequently produce datasets of said viral and host nucleic acids. Therefore, the above limitations of Baptist read on claim 19.
Obvious claim(s): 16-17, 28-29, and 37-38
Baptist discloses downloading nucleotide sequences of n-mer nucleotides that are identical, complementary to conserved and not conserved regions of all known viruses as of May 2, 2006 [Baptista, claim 23], as in instant claims 16-17, 28-29, and 37-38. Therefore, it is obvious the datasets of the all-known viruses originate from different time windows and/or geographical locations.
Baptista does not disclose claim 1 determining a number of distinctive n-mers for at least one biological sequence of the combination. Baptista does not discloses claims 3-5, 8-9, 24, 12, 20, and 33.
Zhou et al. (Zhou) discloses subsequences of polypeptide sequences are referred to as n-mers. [Zhou, page 3 right col para 0052]. Zhou discloses an occurrence frequency which can be represented as number of occurrences of the n-mer in the data set [Zhou, page 3 right col para 0054], as in instant claim 1 determining a number of distinctive n-mers for at least one biological sequence of the combination.
Dependent claim(s): 3, 6, 20, 23, and 32
Zhou et al. (Zhou) discloses subsequences of polypeptide sequences are referred to as n-mers [Zhou claim 1]. Zhou discloses the dataset comprises protein sequence [Zhou, claim 2]. Zhou discloses the subsequences are referred to as n-mers [Zhou, page 3 right col para 0052], as instant claim 3.
Zhou et al. (Zhou) discloses subsequences of polypeptide sequences are referred to as n-mers. [Zhou, page 3 right col para 0052]. Zhou discloses an occurrence frequency which can be represented as number of occurrences of the n-mer in the data set [Zhou, page 3 right col para 0054]. Zhou discloses the threshold value may be based on a set percentile cutoff based on a distribution of pScores for residues in or more proteins [Zhou, page 5 left col para 0072], as in instant claim 6, 23, and 32.
Zhou discloses residue conservation is an indirect measurement of functional or structural importance [Zhou page 1 left col para 0006]. Zhou discloses “conservations can often indicate areas that are functionally or structurally important, such signatures are not always specific to a protein of interest. For example, residues found in functional domains such as the basic leucine zipper domain are conserved. However, basic leucine zipper domains are found in large number of proteins and therefore cannot be used to generate a signature which specifically identifies a given protein.” [Zhou page 1 left col para 0007]. Zhou discloses the method can confer virulence, drug resistance, and metastatic properties to develop reagents that can block functionality of regions [Zhou page 3 right col 0046-0049], as instant claim 20.
Obvious claim(s): 4-5, 8-9, 12, 24, and 33
Baptista discloses two single stranded RNA or DNA molecules are said to be complementary when the nucleotides are aligned and compared with appropriate nucleotide insertions, deletions, pair with at least 80%, 90-95%, and to 98%-100% (i.e., reference sequences). Baptista discloses that BLAST can be used to perform the alignments [Baptista, pages 6-7 para 0060]. Zhou discloses the starting residues number of each subsequence with said first set of subsequences differs by one position [Zhou, claim 12]. Zhou discloses a residue is referred to herein encompass the combination of an amino acid and its position in a polypeptide sequence, for example, D31 or A234 [Zhou, page 2 right col para 0029]. Zhou discloses using mismatches comparisons and perfect match comparisons [Zhou, page 3 left col para 0039], as in instant claims 4-5. Here, it is obvious that n-mers or subsequences are aligned to their complementary RNA or DNA sequence using hybridization methods and comparing the results of the hybridization methods using BLAST or other alignment/comparison tools (i.e., Mismatch comparison, and Perfect matches).
Baptist discloses using viral strain of HPV-18 virus [Baptista page 9 left col para 0090] and discloses Epstein-Barr Virus (EBV)/human herpes virus 4, Kaposi's sarcoma-associated herpes virus (KSHV), also known as human herpes virus 8 [Baptista page 9 right col para 0091]. Baptista discloses virus detected using probes (i.e., n-mer probes) and detected HPV, HHV-3. HTLV1/2 [Baptista page 9 left col para 0090]. Baptista discloses a microarray with a plurality of n-mer viral nucleotides of conserved and not conserved nucleotide regions (i.e., distinctive n-mers) [Baptista, claim 1]. Baptista discloses “Using nucleic acid sequence data, the most highly conserved sequences from each viral family of interest were used to create a microarray. This allows for the detection of members of viral families for which sequences are not specifically included in the microarray sequences as highly similar to the conserved sequences are present in at least a majority of members of each viral family or group” [Baptista, page 1 left para 0006]. Here, is it obvious the methods of Baptista can be utilized to identify distinctive n-mers for each biological sequence which are not present among the plurality of n-mers for the other biological sequences. Zhou discloses an occurrence frequency which can be represented as number of occurrences of the n-mer in the data set [Zhou, page 3 right col para 0054]. Zhou discloses generating a first subsequences [Zhou claim 1] and generating second set of subsequences [Zhou, claim 3]. Zhou discloses “A second set of subsequences is generated from a dataset of sequence. Occurrence frequencies are calculated for the second set of subsequences based on their occurrence in the dataset. Records are generated for subsequences in the second set of subsequences, the records comprising the associated occurrence frequency of the subsequence. These records can be searched with the first set of subsequences to identify the occurrence frequencies of the first set of subsequences in a database.” [Zhou page 1 right col para 0014]. Zhou discloses the combining the scores to generate a score for said polypeptide [Zhou, claim 7].
Zhou discloses determining how often each subsequence occurred in the NR databases and is called “popularity” (i.e., distinctiveness). Zhou discloses “for each residue in the reference sequence, a score was computed as the sum of the popularity values for each of then windows that the residue was a member of, divided by n ( =average popularity for a set of n windows containing the residue), thus each window was weighted equally [Zhou, page 7 left col para 0097], as in instant claims 8, 24, and 33.
Zhou discloses an occurrence frequency which can be represented as number of occurrences of the n-mer in the data set [Zhou, page 3 right col para 0054]. Zhou discloses generating a first subsequences [Zhou claim 1] and generating second set of subsequences [Zhou, claim 3]. Zhou discloses “A second set of subsequences is generated from a dataset of sequence. Occurrence frequencies are calculated for the second set of subsequences based on their occurrence in the dataset. Records are generated for subsequences in the second set of subsequences, the records comprising the associated occurrence frequency of the subsequence. These records can be searched with the first set of subsequences to identify the occurrence frequencies of the first set of subsequences in a database.” [Zhou page 1 right col para 0014]. Zhou discloses the combining the scores to generate a score for said polypeptide [Zhou, claim 7]. Zhou discloses conservation uniqueness scores (i.e., distinctiveness) are displayed onto a three-dimensional representation of a polypeptide to identify a set of high scoring residues on the surface of the protein which are proximate in three-dimensional space. Zhou discloses display is used to identify a set of residues which define a protein signature. Zhou discloses the set can contain any number of residues but in most embodiments will be three or more residues, such as, e.g., three, four, five, six, seven, eight, nine, ten, or more residues. Zhou discloses high scoring values with residues proximate in three-dimensional space can be identified computationally [Zhou, page 3 left col para 0069], as in instant claim 9.
Baptista discloses using n-mer the length of 8-12 base pairs [Baptista, claim 23], about 10 base pairs and 4-6 base pairs [Baptista, claim 24-25]. Baptista discloses the n-mer of the present invention are preferably 60 to 70 nucleotides in length, however, other lengths are possible [Baptista, page 4 right col para 0044]. Zhou also discloses using subsequences with length (i.e., n= 4-6) [Zhou, page 7 right col para 0103], as in instant claims 12. Therefore, Baptista and Zhou makes obvious using various lengths for n-mers such as n-mers of 1 residue in length.
It would be obvious to one of ordinary skill in the art by the effective filing date of the claimed invention to modify Baptista in view of Zhou because Zhou discloses methods for analyzing n-mer subsequences within polypeptide sequences [Zhou, claims 1 and 23]. One of ordinary skill in the would recognize that Baptista and Zhou are in similar fields of endeavor such as nucleic acid (i.e., n-mer) analysis with respect to analyzing biological sequence data. One of ordinary skill in the art would be motivated to combine the n-mer microarray data of Baptista with the n-mer protein subsequences of Zhou as Baptista discloses methods for analyzing polymers (i.e., proteins) arrays [Baptista, page 5 left col para 0047] and Zhou expands on the protein analysis of Baptista by providing a method for determining a subsequences “popularity” (i.e., distinctive n-mer) and numbers of distinctive n-mers. Here, the method of Zhou determines the “popularity” of a subsequences’ occurrence which would provide an additional/supportive quantitative measure for analyzing k-mers/nucleic acids (i.e., how many times the k-mer/subsequence occurs). Thus, because the method of Zhou encompasses a nucleic acid data analysis, one of ordinary skill in the art would recognize the method of Zhou can be utilized to process and evaluate the n-mer microarray data of Baptista. Therefore, one of ordinary skill in the art would have a reasonable expectation of success combining the n-mer microarray data analysis of Baptista with the n-mer protein subsequences occurrence “popularity” and determining a score of Zhou to yield a predictable method for analyzing both nucleic acid n-mers and polypeptide n-mers for identifying distinctive n-mer for determining the number of said distinctive n-mer in genetic sequence datasets.
Claim(s) 7 is rejected under 35 U.S.C. 103 as being unpatentable over Baptista in in view of Zhou, as applied to claims 1-6, 8-20, 21, and 22-39, and in further view of Danko in view of Tarazona et al. (NATURE COMMUNICATIONS, 2020-06, Vol.11 (1), p.3092-13, Article 3092).
Baptista in view of Zhou teach 1-6, 8-20, 21, and 22-39
Baptista in view of Zhou teach a method discloses a method to receive nucleic acid and protein sequence data for determining a number of distinctive n-mers combinations of biological sequences and predicting changes in prevalence.
Baptista in view of Zhou do not teach claim 7.
With respect to claim 7, Tarazona et al. (Tarazona) teach the comparing and analyzing sequencing method data such as microarrays for predicting of different omics combination using error rates [Tarazona, page 6 figure 4gd page 8 figure 5]. Tarazona teaches using Cohen’s d test for relating the initial Cohen’s d to the optimal sample size needed to detect each magnitude of change [Tarazona, page 6 figure 4gd]. Danko teaches using Jensen-Shannon divergence (JSD) [Danko, page 3384 left col second para]. Here, because the Jensen-Shannon divergence (JSD) of Danko and Cohen’s d test of Tarazona can be utilized for determining/identifying differences in nucleic acids datasets (i.e., viral/host datasets), it would be obvious to combine the Cohen’s d microarray sequence analysis of Tarazona with J-S divergence analysis of Danko to construct a claimed step using Cohen’s d and J-S divergence for determining divergences between distributions of biological sequence data.
It would be obvious to one of ordinary skill in the art by the effective filing date of the claimed invention to modify Baptista in view of Zhou in further view of Danko in view of Tarazona because Danko teaches using J-S divergence analysis of Danko determining distances in taxonomic profiles and Tarazona teaches methods utilizing Cohen’s d for analyzing microarray data. One of ordinary skill in the art would recognize that although Tarazona does not teach explicit n-mer/k-mer analysis, Tarazona does teach analyzing nucleic acid sequence data produced from microarrays using Cohen’s d test. One of ordinary skill in the art would be motivated to combine the n-mer microarray data and n-mer analysis of Baptista and Zhou with the k-mer J-S divergence analysis of Danko and the Cohen’s d test of Tarazona because Baptista discloses using n-mer microarrays for designing and identifying cancers and Zhou discloses using datasets from various databases (i.e., NIBI and SWISSPROT). Here, the microarray data of Baptista and the datasets of Zhou could be analyzed using the Cohen’s d test of Tarazona and the J-S divergence of Danko because the Jensen-Shannon divergence (JSD) and Cohen’s d test are tools that are utilized for determining/identifying differences between nucleic acids datasets (i.e., viral/host datasets). Therefore, one of ordinary skill in the art would have a reasonable expectation of success combining the methods of Baptista, Zhou, Danko, and Tarazona to yield a predictable claimed step for utilizing Cohen’s d test and the J-S divergence for calculating divergence between distributions of biological sequence combinations.
Claim(s) 21 is rejected under 35 U.S.C. 103 as being unpatentable over Baptista in in view of Zhou, as applied to claims 1-6, 8-20, and 22-39, and in further view of Danko et al. (Cell, 2021-06, Vol.184 (13), p.3376-3393.e17).
Baptista in view of Zhou in view teach 1-6, 8-20, and 22-39.
Baptista in view of Zhou teach disclose a method discloses a method to receive nucleic acid and protein sequence data for determining a number of distinctive n-mers combinations of biological sequences.
Baptista in view of Zhou do not teach claim 21
Danko et al. (Danko) teach studying global metagenomic map of urban microbiomes and antimicrobial resistance [title]. Danko teaches MetaSUB Core Analysis Pipeline, CAP), which includes a comprehensive set of state-of-the-art, peer-reviewed, metagenomic tools for taxonomic identification, k-mer (i.e., n-mer) analysis, AMR gene prediction, functional profiling, de novo assembly, taxon annotation, and geospatial mapping [Danko, page 3378 right col second para]. Danko teaches k-mer analysis between skin microbiomes and continent and soil microbiome by continent [Danko, page 3381 figure 1 E-F]. Danko teaches viral discovery and identifying host interactions [Danko, pages e8-e9]. Danko teaches their study tracked changes in ecology and virulence [Danko, page 3389 right col third paragraph]. Danko teaches the prevalence of AMR gene with a particular resistance mechanism [Danko, page figure S5 at page 36], as in instant claim 21.
It would be obvious to one of ordinary skill in the art by the effective filing date of the claimed invention to modify Baptista in view of Zhou in view, and in further view of Danko because Danko teaches analyzing microbiomes data from different sources, ethnicities, geographical locations for determining distributions of species prevalence of all samples [Danko, page 3381 figure 1 B-C, table S5]. Danko also teaches viral discovery and host interactions and k-mer counts [Danko, at page 28 GeoDNA sequence search]. One of ordinary skill in the art would be motivated to combine Baptista in view of Zhou, and in further view of Danko because Danko, similar to Baptista and Zhou, teaches an analysis of counts of small pieces/fragments of nucleic acid (i.e., k-mers) [Danko page e9 GeoDNA sequence search] and applying the analysis of the k-mers for determining or predicting changes in prevalence such as antimicrobial resistance, for example. Thus, one of ordinary skill in the art would have a reasonable expectation of success combining Baptista and Zhou with Danko because Danko expands on the use k-mers (i.e., n-mers) by using k-mer counts and k-mers analysis and determines microbial prevalences. Therefore, combining the n-mer microarray analysis of Baptista, n-mer protein analysis of Zhou, and the k-mer counts and prevalence analysis of Danko would yield a predictable method step that can utilize the number of n-mers or parameters to predict changes in prevalence.
Conclusion
Claims 1-39 are rejected.
No claims are allowed.
Finality
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 action.
Inquiries
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSEPH C PULLIAM whose telephone number is (571)272-8696. The examiner can normally be reached 0730-1700 M-F.
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.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Karlheinz Skowronek can be reached at (571) 272-9047. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/J.C.P./Examiner, Art Unit 1687
/Anna Skibinsky/
Primary Examiner, AU 1635
Prosecution Insights