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 .
Remarks
In response to communications sent July 26, 2023, claim(s) 1-20 are pending in this application; of these claims 1, 15, and 20 are in independent form.
Drawings
The drawing(s) filed on April 12, 2023 are accepted by the Examiner.
Information Disclosure Statement
The listing of references in the specification is not a proper information disclosure statement. 37 CFR 1.98(b) requires a list of all patents, publications, or other information submitted for consideration by the Office, and MPEP § 609.04(a) states, "the list may not be incorporated into the specification but must be submitted in a separate paper." Therefore, unless the references have been cited by the examiner on form PTO-892, they have not been considered.
Although this non-provisional application, 18/299,560, does not list references in the Specification, the provisional application 63/092,815 does and it is a priority document.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The independent claim(s) recite(s) several mental processes (curating, determining, classifying, and determining) that utilize the mathematical calculation of resampling using a simulated sample. This judicial exception is not integrated into a practical application because the only additional elements beyond the judicial exceptions are necessary pre-solution activity needed to carry out the abstract idea, and one element that is carried out in parallel. The parallel-computation cannot practically be performed in the human mind, but the parallel computation is not integrated into a practical application that is not itself abstract. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the necessary pre-solution activity is well-understood, routine, and conventional because sending and receiving data, e.g., over a network, is well-understood, routine, and conventional according to buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014).
For further details of the rejection see below, including the grounds of rejection for the dependent claims:
1. A method, comprising:
receiving, by a processor, at least one target genome file, the target genome file including a genome sequence of a target pathogen (an additional element beyond the judicial exception involving sending or receiving data; but this necessary pre-solution activity to carry out the abstract idea; sending and receiving data, e.g., over a network, is well-understood, routine, and conventional according to buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014);
receiving, by a processor, at least one near-neighbor genome file, the near-neighbor genome file including a genome sequence of at least one organism found in a taxonomy close relative of the target pathogen (an additional element beyond the judicial exception involving sending or receiving data; but this necessary pre-solution activity to carry out the abstract idea; sending and receiving data, e.g., over a network, is well-understood, routine, and conventional according to buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014);
analyzing the target genome file and the near-neighbor genome file via a parallel comparison to generate a plurality of raw e-probe sequences to provide at least one raw e-probe sequence set, with each raw e-probe sequence set unique to the target pathogen (an additional element because the comparisons are performed in parallel, and therefore cannot be performed by the human mind, which generally performs comparisons sequentially);
curating the plurality of raw e-probes sequences to classify each raw e-probe as a curated e-probe or a false positive e-probe, the curated e-probes forming at least one curated e-probe sequence set (mental process of curating that is scaled by using a general purpose computer);
performing in silico validation on the at least one curated e-probe sequence set to provide an in silico validated e-probe set, in silico validation including the steps of:
obtaining at least one simulated sample provided by a metagenome simulator, the at least one simulated sample having different relative prevalence of the genome sequence of the target pathogen mixed into host genome sequences (mathematical resampling; this is mathematical because of the use of different relative prevalences for the resampling; mathematical resampling falls under the category of mathematics, which is a judicial exception);
determining comparative hits between the at least one curated e-probe sequence set and the at least one simulated sample (mental process of curating that is scaled by using a general purpose computer);
classifying the comparative hits using at least one alignment metric (mental process of classifying that is scaled by using a general purpose computer);
validating the curated e-probe sequence set as the in silico validated e-probe set based on the classification of the comparative hits (mental process of validating that is scaled by using a general purpose computer); and,
determining, by an e-probe diagnostic system, presence of the target pathogen in a sample metagenome of a host using the in silico validated e-probe set (mental process of determining that is scaled by using a general purpose computer).
2. The method of claim 1, wherein the target genome file includes a partially assembled genome sequence of the target pathogen (part of the additional element, but still sending and receiving particular data over a network, as noted for the independent claim, which is well-understood, routine, and conventional).
3. The method of claim 1, wherein the target genome file includes a draft subset genome of the target pathogen (part of the additional element, but still sending and receiving particular data over a network, as noted for the independent claim, which is well-understood, routine, and conventional).
4. The method of claim 1, further comprising the step of selecting, by a user, nucleotide (nt) length for each raw e-probe (an additional element of interacting with a user interface, but which is not specific enough to an improvement to the functioning of the computer).
5. The method of claim 1, wherein curating the plurality of raw e-probe sequences adjusts diagnostic sensitivity of the curated e-probe sequence set (intended result of a mental process that limits the mental process).
6. The method of claim 1, further comprising the step of performing in vitro validation on the at least one in silico validated e-probe set to provide an in vitro validated e-probe set (mental process of validation), the in vitro validated e-probe set being used to determine presence of the target pathogen in a sample metagenome (intended result of the additional element and not a positively recited step).
7. The method of claim 6, wherein performing in vitro validation on the curated e-probe sequence set to provide an in vitro validated e-probe set includes the steps of:
providing a plurality of in vitro samples having the target pathogen (additional element);
analyzing the plurality of in vitro samples with the at least one in silico validated e-probe set to determine at least one comparative hit (mental process that can be performed in the mind with the aid of a general purpose computer);
classifying the comparative hits using at least one alignment metric to determine a comparative score (mental process that can be performed in the mind with the aid of a general purpose computer; broadest reasonable interpretation of the claims includes a problem size that can be aligned by scaling a mental process with the use of general purpose computer); and,
validating the in silico validated e-probe set based on the comparative score to provide the in vitro validated e-probe set (mental process performable in the human mind).
8. The method of claim 6, further comprising the step of performing field validation (note that the Examiner is not confusing a “field validation” to be a mere “field of use”) on the in vitro validated e-probe set to provide a field validated e-probe set (improvement to a diagnostic product, but the scope of the improvement is not particular because the set of probes is not specified; the Examiner argues that field validations are well-understood, routine, and conventional because “calibration” in the Mayo case was considered ineligible subject matter; see Mayo, 566 U.S. at 76, 101 USPQ2d at 1967), the field validated e-probe set being used to determine presence of the target pathogen in a sample metagenome (mental process of a determination).
9. The method of claim 1, further comprising the step of performing field validation (note that the Examiner is not confusing a “field validation” to be a mere “field of use”) on the in silico validated e-probe set to provide a field validated e-probe set (improvement to a diagnostic product, but the scope of the improvement is not particular because the set of probes is not specified; the Examiner argues that field validations are well-understood, routine, and conventional because “calibration” in the Mayo case was considered ineligible subject matter; see Mayo, 566 U.S. at 76, 101 USPQ2d at 1967), the field validated e-probe set being used to determine presence of the target pathogen in a sample metagenome (mental process of a determination).
10. The method of claim 1, wherein curating the plurality of raw e-probe sequences includes comparative analysis of the raw e-probe sequences using a Basic Local Alignment Search Tool for nucleotides (BLASTn) and at least one database to provide the curated e-probe sequence set (limitations to the mental process which involves sequence alignment, which can be practically performed by the human mind on a small scale; the broadest reasonable interpretation of the claims includes small sequence alignments that can be performed by scaling up human processing of alignment algorithms to search against a large genome with the help of a general purpose computer).
11. The method of claim 10, wherein curating the plurality of raw e-probe sequences further comprises performing a multiplicity analysis using p-values to eliminate non-responsive e-probes (mental process combined with mathematics, which is a judicial exception as well).
12. The method of claim 1, wherein the at least one alignment metric includes percent identity and query coverage of the comparative hits (mental process combined with mathematics, which is a judicial exception as well).
13. The method of claim 1, further comprising the step of validating the in silico validated e-probe set using internal control e-probes (mental process using data outputted from internal controls).
14. The method of claim 13, wherein validating the in silico validated e-probe set uses at least five internal control e-probes (mental process using data outputted from internal controls).
15. One or more non-transitory computer readable medium storing a set of computer executable instructions for running on one or more processors that when executed cause the one or more processors (general purpose computer) to:
receive at least one target genome file and at least one near-neighbor genome file (an additional element beyond the judicial exception involving sending or receiving data; but this necessary pre-solution activity to carry out the abstract idea; sending and receiving data, e.g., over a network, is well-understood, routine, and conventional according to buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014);
analyze the target genome file and the near-neighbor genome file to generate a plurality of raw e-probes with each raw e-probe unique to a target pathogen (an additional element because the comparisons are performed in parallel, and therefore cannot be performed by the human mind, which generally performs comparisons sequentially);
curate the plurality of raw e-probes to provide a curated e-probe set;
receive at least one simulated sample and perform in silico validation on the curated e-probe set to provide an in silico validated e-probe set (mental process of curating that is scaled by using a general purpose computer); and,
determine presence of the target pathogen in a sample metagenome using the in silico validated e-probe set in an e-probe diagnostic system (mental process of determining that is scaled by using a general purpose computer).
16. The one or more non-transitory computer readable medium storing a set of computer executable instructions for running on one or more processors of claim 15, wherein the one or more processors curate the plurality of raw e-probes by performing a multiplicity analysis using p-values to eliminate non-responsive e-probes (mental process combined with mathematics, which is a judicial exception as well).
17. The one or more non-transitory computer readable medium storing a set of computer executable instructions for running on one or more processors of claim 15, wherein in silico validation includes the steps of:
providing at least one simulated sample from a metagenomic database, the simulated sample having different relative prevalence of a genome sequence of the target pathogen mixed into host genome sequences (mathematical resampling; this is mathematical because of the use of different relative prevalences for the resampling; mathematical resampling falls under the category of mathematics, which is a judicial exception);
analyzing the at least one simulated sample with the curated e-probe set to determine comparative hits (mental process of curating that is scaled by using a general purpose computer);
classifying the comparative hits using at least one alignment metric to determine a comparative score (mental process that can be performed in the mind with the aid of a general purpose computer; broadest reasonable interpretation of the claims includes a problem size that can be aligned by scaling a mental process with the use of general purpose computer); and,
validating the curated e-probe based on the comparative score to provide the in silico validated e-probe set (mental process performable in the human mind).
18. The one or more non-transitory computer readable medium storing a set of computer executable instructions for running on one or more processors of claim 17, wherein the at least one alignment metric includes percent identity and query coverage of the comparative hits (a limitation to the mental process itself).
19. The one or more non-transitory computer readable medium storing a set of computer executable instructions for running on one or more processors of claim 17, further comprising the step of validating the in silico validated e-probe set using internal control e-probes (the validation is a mental process using information from control probes).
20. A method, comprising:
receiving at least one target genome file and at least one near-neighbor genome file (an additional element beyond the judicial exception involving sending or receiving data; but this necessary pre-solution activity to carry out the abstract idea; sending and receiving data, e.g., over a network, is well-understood, routine, and conventional according to buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014);
analyzing the target genome file and the near-neighbor genome file to generate a plurality of raw e-probes unique to a target pathogen having a pathogen genome, each raw e-probe having a unique nucleic acid signature sequence selected from along a length of the pathogen genome (an additional element because the comparisons are performed in parallel, and therefore cannot be performed by the human mind, which generally performs comparisons sequentially);
curating the plurality of raw e-probes to provide a curated e-probe set (mental process of curating that is scaled by using a general purpose computer);
receiving at least one simulated sample and perform in silico validation on the curated e-probe set to provide an in silico validated e-probe set (mathematical resampling; this is mathematical because of the use of different relative prevalences for the resampling; mathematical resampling falls under the category of mathematics, which is a judicial exception);
performing in vitro validation on the in silico validated e-probe set to provide an in vitro validated e-probe set (mental process of validating that is scaled by using a general purpose computer), the in vitro validated e-probe set being used to determine presence of the target pathogen in a sample metagenome (mental process of determining that is scaled by using a general purpose computer); and,
determining presence of the target pathogen in a sample metagenome using the in vitro validated e-probe set in an e-probe diagnostic system (mental process of determining that is scaled by using a general purpose computer).
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by the “Stobbe” reference, hereafter refers to:
Stobbe, Anthony H., et al. "E-probe Diagnostic Nucleic acid Analysis (EDNA): A theoretical approach for handling of next generation sequencing data for diagnostics." Journal of microbiological methods 94.3 (2013): 356-366.
As to claim 1, Stobbe teaches a method, comprising:
receiving, by a processor, at least one target genome file, the target genome file including a genome sequence of a target pathogen (Stobbe Figure 1: “Target Genome”; section 2.3 paragraph 2 regarding “target genome”);
receiving, by a processor, at least one near-neighbor genome file, the near-neighbor genome file including a genome sequence of at least one organism found in a taxonomy close relative of the target pathogen (Stobbe Figure 1: “Near Neighbor Genome”; section 2.3 paragraph 2 regarding “near neighbor selection”);
analyzing the target genome file and the near-neighbor genome file via a parallel comparison to generate a plurality of raw e-probe sequences to provide at least one raw e-probe sequence set (Stobbe Figure 1: “E-probe design”; section 2.3 paragraph 1 regarding “e-probe design”), with each raw e-probe sequence set unique to the target pathogen (Stobbe Figure 1: “Target/Decoy E-probe set” ”; section 2.3 paragraph 1 regarding “e-probe design”);
curating the plurality of raw e-probes sequences to classify each raw e-probe as a curated e-probe or a false positive e-probe, the curated e-probes forming at least one curated e-probe sequence set (Stobbe Figure 1: “BLASTn”; section 2.3 paragraph 1 regarding “BLAST” “to assure specificity”);
performing in silico validation on the at least one curated e-probe sequence set to provide an in silico validated e-probe set (Stobbe Figure 1: “NGS Simulation”; section 2.4 “simulations”), in silico validation including the steps of:
obtaining at least one simulated sample provided by a metagenome simulator, the at least one simulated sample having different relative prevalence of the genome sequence of the target pathogen mixed into host genome sequences (Stobbe Figure 1: “Mock Sample Database”; ”; section 2.4 “simulations” result in a “mock database” with varying “pathogen abundance”);
determining comparative hits between the at least one curated e-probe sequence set and the at least one simulated sample (Stobbe Figure 1: “BLASTn”; section 2.5 paragraph 1: “querying mock databases”);
classifying the comparative hits using at least one alignment metric (Stobbe Figure 1: “Score E-probes” ”; section 2.5 paragraph 1: “e-values” and in section 2.5 paragraph 2: “designate a sample as positive or negative for a pathogen”);
validating the curated e-probe sequence set as the in silico validated e-probe set based on the classification of the comparative hits (Stobbe Figure 1: “Similar Scores”; section 2.5 paragraph 3: validation); and,
determining, by an e-probe diagnostic system, presence of the target pathogen in a sample metagenome of a host using the in silico validated e-probe set (Stobbe Figure 1: “Plant Sample” “NGS” “Simple Sample Database” and “Target Absent” vs. “Target Present”; section 2.5 paragraph 3: classifying a “sample”).
As to claim 2, Stobbe teaches the method of claim 1, wherein the target genome file includes a partially assembled genome sequence of the target pathogen (Stobbe Para 2.2: “raw unassembled sequence reads” as a basis for the experimental flow).
As to claim 3, Stobbe teaches the method of claim 1, wherein the target genome file includes a draft subset genome of the target pathogen (Stobbe Para 3.1 first paragraph on page 362: various genome coverage levels).
As to claim 4, Stobbe teaches the method of claim 1, further comprising the step of selecting, by a user, nucleotide (nt) length for each raw e-probe (Stobbe Figure 7 and section 3.2: optimization of nucleotide length by a user-initiated process).
As to claim 5, Stobbe teaches the method of claim 1, wherein curating the plurality of raw e-probe sequences adjusts diagnostic sensitivity of the curated e-probe sequence set (Stobbe section 2.3 paragraph 1: assuring specificity, which the Examiner argues affects sensitivity as well).
As to claim 6, Stobbe teaches the method of claim 1, further comprising the step of performing in vitro validation on the at least one in silico validated e-probe set to provide an in vitro validated e-probe set, the in vitro validated e-probe set being used to determine presence of the target pathogen in a sample metagenome (Stobbe section 3.5: correctly calling sample pathogens using a metagenomic sample).
As to claim 7, Stobbe teaches the method of claim 6, wherein performing in vitro validation on the curated e-probe sequence set to provide an in vitro validated e-probe set includes the steps of:
providing a plurality of in vitro samples having the target pathogen (Stobbe section 3.5: positive samples);
analyzing the plurality of in vitro samples with the at least one in silico validated e-probe set to determine at least one comparative hit (Stobbe section 3.5: determining validated hits, which implicitly uses e-probes from section 2.3);
classifying the comparative hits using at least one alignment metric to determine a comparative score (Stobbe section 3.5: classifying positives and negatives); and,
validating the in silico validated e-probe set based on the comparative score to provide the in vitro validated e-probe set (Stobbe section 3.5: checking for correct identifications).
As to claim 8, Stobbe teaches the method of claim 6, further comprising the step of performing field validation on the in vitro validated e-probe set to provide a field validated e-probe set, the field validated e-probe set being used to determine presence of the target pathogen in a sample metagenome (Stobbe abstract: the intended purpose of the technique is plant biosecurity through detection of pathological organisms, and this is done using the e-probes).
As to claim 9, Stobbe teaches the method of claim 1, further comprising the step of performing field validation on the in silico validated e-probe set to provide a field validated e-probe set, the field validated e-probe set being used to determine presence of the target pathogen in a sample metagenome (Stobbe Discussion second to last paragraph on page 366: “The theoretical ability of next generation sequencing coupled with bioinformatics to detect highly consequential plant pathogens (EDNA), at varying abundances, and in a complex host sample was validated”).
As to claim 10, Stobbe teaches the method of claim 1, wherein curating the plurality of raw e-probe sequences includes comparative analysis of the raw e-probe sequences using a Basic Local Alignment Search Tool for nucleotides (BLASTn) and at least one database to provide the curated e-probe sequence set (Stobbe Figure 1: “BLASTn”; section 2.3 paragraph 1 regarding “BLAST” “to assure specificity”).
As to claim 11, Stobbe teaches the method of claim 10, wherein curating the plurality of raw e-probe sequences further comprises performing a multiplicity analysis using p-values to eliminate non-responsive e-probes (Stobbe Table 3” P-values of diagnostic calls).
As to claim 12, Stobbe teaches the method of claim 1, wherein the at least one alignment metric includes percent identity and query coverage of the comparative hits (Stobbe Section 2.5 paragraph 2: percentage coverage; the percent identity is implied by the usage of the BLASTn algorithm; see section 4.3 last paragraph for running the BLASTn algorithm with specific parameters).
As to claim 13, Stobbe teaches the method of claim 1, further comprising the step of validating the in silico validated e-probe set using internal control e-probes (Stobbe Figure 1: “NGS Simulation”; section 2.4 “simulations” including host genomes and mitochondria at controlled ratios).
As to claim 14, Stobbe teaches the method of claim 13, wherein validating the in silico validated e-probe set uses at least five internal control e-probes (Stobbe Figure 1: “NGS Simulation”; section 2.4 “simulations” including 1000 mitochondria and chloroplasts vs. 100 host genomes).
As to claim 15, Stobbe teaches one or more non-transitory computer readable medium storing a set of computer executable instructions for running on one or more processors that when executed cause the one or more processors to (Stobbe Figure 1: a computerized flowchart):
receive at least one target genome file and at least one near-neighbor genome file (Stobbe Figure 1: “Target Genome”; section 2.3 paragraph 2 regarding “target genome”);
analyze the target genome file and the near-neighbor genome file to generate a plurality of raw e-probes (Stobbe Figure 1: “E-probe design”; section 2.3 paragraph 1 regarding “e-probe design”) with each raw e-probe unique to a target pathogen (Stobbe Figure 1: “Target/Decoy E-probe set” ”; section 2.3 paragraph 1 regarding “e-probe design”);
curate the plurality of raw e-probes to provide a curated e-probe set;
receive at least one simulated sample and perform in silico validation on the curated e-probe set to provide an in silico validated e-probe set (Stobbe Figure 1: “BLASTn”; section 2.3 paragraph 1 regarding “BLAST” “to assure specificity”); and,
determine presence of the target pathogen in a sample metagenome using the in silico validated e-probe set in an e-probe diagnostic system (Stobbe abstract: the intended purpose of the technique is plant biosecurity through detection of pathological organisms, and this is done using the e-probes).
As to claim 16, Stobbe teaches the one or more non-transitory computer readable medium storing a set of computer executable instructions for running on one or more processors of claim 15, wherein the one or more processors curate the plurality of raw e-probes by performing a multiplicity analysis using p-values to eliminate non-responsive e-probes Stobbe Table 3” P-values of diagnostic calls).
As to claim 17, Stobbe teaches the one or more non-transitory computer readable medium storing a set of computer executable instructions for running on one or more processors of claim 15, wherein in silico validation includes the steps of:
providing at least one simulated sample from a metagenomic database, the simulated sample having different relative prevalence of a genome sequence of the target pathogen mixed into host genome sequences (Stobbe Figure 1: “Mock Sample Database”; ”; section 2.4 “simulations” result in a “mock database” with varying “pathogen abundance”);
analyzing the at least one simulated sample with the curated e-probe set to determine comparative hits (Stobbe Figure 1: “BLASTn”; section 2.5 paragraph 1: “querying mock databases”);
classifying the comparative hits using at least one alignment metric to determine a comparative score (Stobbe Figure 1: “Score E-probes” ”; section 2.5 paragraph 1: “e-values” and in section 2.5 paragraph 2: “designate a sample as positive or negative for a pathogen”); and,
validating the curated e-probe based on the comparative score to provide the in silico validated e-probe set (Stobbe Figure 1: “Similar Scores”; section 2.5 paragraph 3: validation).
As to claim 18, Stobbe teaches the one or more non-transitory computer readable medium storing a set of computer executable instructions for running on one or more processors of claim 17, wherein the at least one alignment metric includes percent identity and query coverage of the comparative hits (Stobbe Section 2.5 paragraph 2: percentage coverage; the percent identity is implied by the usage of the BLASTn algorithm; see section 4.3 last paragraph for running the BLASTn algorithm with specific parameters).
As to claim 19, Stobbe teaches the one or more non-transitory computer readable medium storing a set of computer executable instructions for running on one or more processors of claim 17, further comprising the step of validating the in silico validated e-probe set using internal control e-probes (Stobbe Figure 1: “NGS Simulation”; section 2.4 “simulations” including host genomes and mitochondria at controlled ratios).
As to claim 20, Stobbe teaches a method, comprising:
receiving at least one target genome file and at least one near-neighbor genome file (Stobbe Figure 1: “Target Genome”; section 2.3 paragraph 2 regarding “target genome”; Stobbe Figure 1: “Near Neighbor Genome”; section 2.3 paragraph 2 regarding “near neighbor selection”);
analyzing the target genome file and the near-neighbor genome file to generate a plurality of raw e-probes unique to a target pathogen having a pathogen genome, each raw e-probe having a unique nucleic acid signature sequence selected from along a length of the pathogen genome (Stobbe Figure 1: “E-probe design”; section 2.3 paragraph 1 regarding “e-probe design”; Stobbe Figure 1: “Target/Decoy E-probe set” ”; section 2.3 paragraph 1 regarding “e-probe design”);
curating the plurality of raw e-probes to provide a curated e-probe set (Stobbe Figure 1: “BLASTn”; section 2.3 paragraph 1 regarding “BLAST” “to assure specificity”);
receiving at least one simulated sample (Stobbe Figure 1: “Mock Sample Database”; ”; section 2.4 “simulations” result in a “mock database” with varying “pathogen abundance”) and perform in silico validation on the curated e-probe set to provide an in silico validated e-probe set (Stobbe Figure 1: “NGS Simulation”; section 2.4 “simulations”);
performing in vitro validation on the in silico validated e-probe set to provide an in vitro validated e-probe set, the in vitro validated e-probe set being used to determine presence of the target pathogen in a sample metagenome (Stobbe Figure 1: “Plant Sample” “NGS” “Simple Sample Database” and “Target Absent” vs. “Target Present”; section 2.5 paragraph 3: classifying a “sample”); and,
determining presence of the target pathogen in a sample metagenome using the in vitro validated e-probe set in an e-probe diagnostic system (Stobbe abstract: the intended purpose of the technique is plant biosecurity through detection of pathological organisms, and this is done using the e-probes).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Visser, Marike, Johan T. Burger, and Hans J. Maree. "Targeted virus detection in next-generation sequencing data using an automated e-probe based approach." Virology 495 (2016): 122-128.
US 11783914 B2: pertinent because of “panels” for metagenomics.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jesse P Frumkin whose telephone number is (571)270-1849. The examiner can normally be reached Monday - Friday, 10-5 ET.
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/JESSE P FRUMKIN/ Primary Examiner, Art Unit 1685 August 20, 2026
