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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 10/06/2025 has been entered.
Applicant's amendments and remarks, filed, 07/16/2025, are acknowledged. Rejections and/or objections not reiterated from previous office actions are hereby withdrawn. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Status of Claims
Claims 1-6, 8-16, 18-22 are under examination.
Claims 7 and 17 are cancelled. Claims 21 and 22 are newly added.
Priority
The instant application does not claim the benefit of priority under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) to any prior applications. Accordingly, the effective priority date for the instant application is the filing date of 03/18/2019.
Withdrawn Rejections
The rejection of claims 1-6, 8-16, 18-20 under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement is withdrawn in view of applicant’s amendments and arguments.
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.
The following rejection is maintained.
Claims 1-6, 8-16, 18-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
The Supreme Court has established a two-step framework for this analysis, wherein a claim does not satisfy § 101 if (1) it is “directed to” a patent-ineligible concept, i.e., a law of nature, natural phenomenon, or abstract idea, and (2), if so, the particular elements of the claim, considered “both individually and ‘as an ordered combination,” do not add enough to “transform the nature of the claim into a patent-eligible application.” Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1353 (Fed. Cir. 2016) (quoting Alice, 134 S. Ct. at 2355).
Guidance: Step 1. Under the broadest reasonable interpretation, the claimed invention (claims 1, 11, 21, 22 being representative) is directed to a method, system, and CRM performing a process and therefore falls within one of the four statutory categories.
A. Guidance Step 2A, Prong 1
The Revised Guidance instructs us first to determine whether any judicial exception to patent eligibility is recited in the claim. The Revised Guidance identifies three judicially-excepted groupings identified by the courts as abstract ideas: (1) mathematical concepts, (2) certain methods of organizing human behavior such as fundamental economic practices, and (3) mental processes. In this case, the following steps of claims 1, 11, 21, 22 encompass an abstract idea:
separating…the spectral file into spectral split files…comprising mass spectrometry-based proteomics data corresponding to a predetermined range of precursor masses; identifying…candidate peptides based on the querying;
determining…protein identification scores corresponding to candidate peptides, wherein the computing is performed in parallel across the plurality of GPU cores; identifying…a top-N number of…peptides based on…scores and discarding all but said top-N candidate peptides;
combining…the protein identification scores of said top-N candidate peptides and determining a final main score; identifying…a peptide corresponding to the mass spectrometry-based proteomics data based on the final main score.
Mental Processes
Under the broadest reasonable interpretation, the italicized steps above amount to observing/manipulating data, analyzing data (by determining scores), and making a determination based on said analysis. As such, all of these steps can be reasonably performed by the human mind of a scientist. Furthermore, a review of the specification clearly describes algorithmic processes for analyzing peptide data using conventional computer system architecture [see at least pages 16, 17]. Accordingly, the specification provides sufficient evidence that the claims are directed to an abstract idea since the specific descriptions provided for accomplishing these tasks include only data reception and analysis. Accordingly, but for the claimed CPU and GPU, there is nothing in the claims that foreclose this step from being performed by the mind of a scientist. Therefore, all of the above steps fall within the “mental processes” grouping of abstract idea. See also MPEP 2106.04 and 2106.05(II). [Step 2A, Prong 1: YES].
Mathematical Concept
In addition, several of the italicized steps recite a mathematical concept. In particular, the steps for determining and calculating “scores” necessarily require mathematical calculations as the scores are numerical values assigned to candidates. Applicant is reminded that a mathematical calculation is an act of calculating using mathematical methods to determine a variable or number, e.g., a numerical score associated with a candidate peptide. See MPEP 2106.04(a)(2). This position is further supported by applicant’s own specification, which teaches mathematical algorithms/operations for calculating peptide scores, e.g. PSM score [pages 9, 10, 12]. Therefore, when read in light of the specification, the claimed steps reasonably encompass a mathematical concept and applicant is invited to present evidence to the contrary.
B. Guidance Step 2A, Prong 2
This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception. In this case, the claimed steps that are not part of the abstract idea are as follows:
receiving, using a communication device, a spectral file comprising mass spectrometry-based proteomics data from a user device; querying, using a protein database, based on the plurality of spectral split files;
In this case, the claimed receiving step is generically recited and amounts to necessary gathering of spectral data for use by the abstract idea. Similarly, the above querying step is nominally recited (i.e. not limited to any particular acts or techniques for achieving the claimed function) and amounts to collecting or selecting data for use by the abstract idea. Therefore, the above steps amount to “insignificant extra-solution activity” and do not integrate the judicial exception into a practical application. See MPEP 2106.05(g).
With regards to the recited processing device, communication device, GPU cores, and database, these are recited at a high level of generality and thus can be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. In addition, “generic computer components such as a computer and database do not satisfy the inventive concept requirement.” See MPEP 2106.05(h). With regards to the recited “proteomics pipeline”, this is broadly interpreted as a computer program absent any limiting definition to the contrary. As such, this feature can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer (since programs run on computers). To the extent that applicant is also asserting that the claimed GPU and CPU amount to an improvement in computer technology (e.g. via automation of processes or speeding up calculations), the MPEP 2106.05(a) provides several examples that are not sufficient to show an improvement in computer-functionality:
Accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016);
Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017) or speeding up a loan-application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential);
In other words, the claimed invention appears to be using general purpose CPU and GPU cores to implement the claimed process. The MPEP is clear that a conventional computer applying an abstract idea does not qualify as a particular machine. See MPEP 2106.04(a)(2)(III)(C). For these reasons, and absent any evidence to the contrary, the examiner maintains that the claims as a whole are directed to an abstract idea and do not integrate the abstract idea into a practical application. [Step 2A, Prong 2: NO]
C. Guidance Step 2B:
Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. In this case, the claims do not include additional steps and/or elements appended to the judicial exception that are sufficient to amount to significantly more than the judicial exception(s) for the following reasons:
As discussed above, the above non-abstract steps (including the full limitations and not just the verbs) amount to nothing more than insignificant extra-solution activity and/or instructions to “apply” the exception in a generic way. In this case, the specification teaches routine and conventional computer hardware, client server architecture, and quantitative analysis software for carrying out the claimed invention [See pages 18-22]. Moreover, a review of the prior art teaches that the above non-abstract limitations were routine and conventional in the art. For example, Li et al. (BMC Bioinformatics 2014, 15:121, pp.1-11; IDS filed 03/18/2019) teaches a method for improving the speed of mass spectrometry-based protein search identification using multi-GPU cores and parallel processors [page 2, col. 1] and a database comprising spectral data [page 3, entire, Table 2, Figure 3]. Additionally, Deutsch et al. (Proteomics Clin Appl., 2015, 9(0): 745–754) teaches a Trans-Proteomic Pipeline that is associated with a complete suite of open-source tools for processing proteomics data with statistical validation that includes initial conversion to open formats, sequence database and spectral library-based searching, statistical post-validation of the search results, quantification information extraction, protein inference, and graphical exploration of the results. Therefore, even when viewed as a combination, there is nothing unconventional with regards to the non-abstract steps set forth above or the use of CPUs and GPU cores in proteomics analysis. Thus, the independent claim(s) as a whole do not amount to significantly more than the exception itself. For these reasons, the claim(s) is/are not patent eligible. [Step 2B: NO].
Dependent Claims
Dependent claims 2-6, 8-10, 12-16, 18-20 have also been considered under the two-part analysis but do not include additional steps/elements appended to the judicial exception that are sufficient to amount to significantly more than the judicial exception(s) for the following reasons. Regarding claim(s) 2-4, 8-9, and 12-14, 18, 19, these are all directed to limitations that further limit the specificity of the abstract idea set forth above or the nature of the data being used by the abstract, and therefore are also encompass a mental processor and/or mathematical concepts for reasons discussed above in the Step 2A (prong 1) analysis. Regarding claim(s) 5, 6, 10, 15, 16, 20, these claims further limit the structural or functional performed of the claimed processing device, and therefore are not patent eligible for all the reasons discussed above in the Step 2A (prong 2) and Step 2B analysis. Therefore, the claims as a whole are not patent eligible. For additional guidance, applicant is directed generally to the October 2019 Revised Patent Subject Matter Eligibility Guidance.
Response to Arguments
Applicant’s arguments, filed 07/16/2025, have been fully considered but are not persuasive for the following reasons.
Applicant essentially argues that the claimed invention is patent eligible in view of the Park declaration. Accordingly, this document has been carefully considered but does not put the claims into condition for allowance for the following reasons.
In particular, the Park declaration's primary assertion is that the claimed step of "splitting incoming mass spectrometry-based proteomics data into spectral split files corresponding to a range of precursor masses" provides an improvement to the technology by providing a performance boost in the speed at which the proteomics pipeline can process spectral data and search/query a database (using GPUs). In response, it is noted with particularity that the 'splitting' step is generically recited without any specific details with regards to how this step is being performed computationally. Moreover, this step has been reasonably interpreted as part of the judicial exception (for reasons explained in the Final Office Action, pages 3-5). Therefore, the Park declaration is asserting that the inventive concept is the abstract idea. However, Applicant is reminded that “[i]t has been clear since Alice that a claimed invention’s use of the ineligible concept to which it is directed cannot supply the inventive concept that renders the invention ‘significantly more’ than that ineligible concept.” BSG Tech LLC v. BuySeasons, Inc., 899 F.3d 1281, 1290 (Fed. Cir. 2018). In addition, there is also case law supporting the determination that claims that merely provide efficiency or accuracy increases over mental calculations do not recite eligible subject matter. See Bancorp Servs., L.L.C. v. Sun Life Assurance Co. of Can. (US.), 687 F.3d 1266, 1279 (Fed. Cir. 2012).
The Park declaration additionally asserts that the claimed invention provides an improvement to a specific machine (namely a pipeline using a CPU and GUPs). In response, the claimed invention is directed to a method of accelerating execution of a search query for peptide identification. While the Park declaration asserts [on page 3] that it took “substantial inventive effort” to develop software for CPUs to operate on parallel GPUs, no evidence of such efforts have been provided (e.g. algorithms, code, etc.) nor is there any such evidence reflected in the claims or the specification. Moreover, the Park declaration also does not contend that it invented any new type of GPU cores or processors for purposes of performing the claimed invention. The claims merely require “software running on a CPU and GPUs cores” which are recited at a high level of generality and the specification to teaches that these are generic computer hardware elements performing routine and conventional functions [Figure 2]. Accordingly, the claimed CPU and GPU elements have been reasonably interpreted as conventional computer elements and using a computer as a tool to perform an abstract idea (as noted and supported with evidence in the Final Office Action, pages 6-7). As such, the claimed invention does not appear to result in improvements to the functioning of a particular machine or add a specific limitation other than what is well-understood, routine, conventional activity in the field, e.g., a non-conventional and non-generic arrangement of various computer components. The claimed invention is directed to obtaining data, analyzing data, and generating a result (peptide identification) and merely invokes generic computer elements for performing the claimed steps rather than a specific method that improves the relevant technology. The Federal Circuit has held that claims involving data collection, analysis, and output often are directed to abstract ideas. Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1353 (Fed. Cir. 2016).
The Park declaration additionally argues that the claimed invention cannot be performed by the human mind, citing various sizes of large proteomics data files (e.g. 5-10GB) that are typically processed by computer. In response, it is noted with particularity that the claimed "proteomics data", "spectral files", or "split files" being analyzed are not limited to any particular file sizes, amounts of data, or particular types of MS spectral data (e.g. MS1, MS/MS). That being said, Applicant is reminded that the Office's eligibility guidance does not set limit on the number of calculations that can or cannot be performed mentally. MPEP § 2106.04(a)(2)III. In addition, it is noted that the Park declaration plainly acknowledges specific claim steps that require mathematical calculations (see pages 3-4). That being said, the examiner has provided sufficient reasoning as to why the comparing and calculating steps recite a mathematical concept (final Office Action, page 5). In addition, the courts have stated “[i]t is of no moment that the algorithm is not expressed in terms of a mathematical formula. Words used in a claim operating on data to solve a problem can serve the same purpose as a formula.” In re Grams, 888 F.2d 835, 837 (Fed. Cir. 1989). Therefore, when read in light of applicant’s own specification and the Park declaration, the examiner maintains that the asserted improvement is to the method of data processing techniques. As such, the improvement is integral to the abstract idea of mathematical concepts and therefore is not to the “non-abstract application realm.” SAP, 898 F.3d at 1168. Accordingly, the Park declaration is not sufficient to overcome the rejection under 35 USC 101. For these reasons (and those set forth in the Final Office action), the examiner maintains that the claims as a whole are directed to an abstract idea and do not integrate the abstract idea into a practical application.
Examiner Comment
In the interest of advancing prosecution, the examiner is open to discussing clarifying amendments that may serve to better reflect the nature of the “improvements” to the technology and/or non-conventional and non-generic arrangements of various computer components, e.g. by amending claims 1, 11, 21, and 22 such that: (1) the claimed methods and system comprise software running on a CPU and a plurality of parallel GPU cores” [as suggested in the Park declaration, page 2], and (2) further limiting the search and scoring to “post-translational modification search” and “PSM calculations” [as suggested in the Park declaration on page 2]. Please note that this is only a suggestion for purposes of discussion [in light of the Park declaration] and not necessarily indicative of allowable subject matter. Feel free to reach out to the examiner at your convenience.
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 1-6, 8-16, 18-20 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 pre-AIA the applicant regards as the invention. Claims that depend directly or indirectly from claim(s) 1 and 11 are also rejected due to said dependency.
Claims 1 and 11 recite “receiving, by a proteomics pipeline, comprising software running on a CPU and GPUs, via a communication device, a spectral file…from a user device”. Firstly, it is unclear what is meant by the term “receiving by a proteomics pipeline”. As best understood, the proteomics pipeline is merely a “software program” (running on a CPU and GPUs). That being the case, receiving a spectral file “from a proteomics pipeline” would make sense but that is not what is being claimed. Accordingly, it is unclear who/what is doing the “receiving”, e.g. the pipeline software, a user of the software, or otherwise. Notably, this single step confusingly requires plurality of additional claim elements that are not even recited in subsequent claim steps (e.g. a communication device and a user device). Accordingly, Applicant is encouraged to eliminate any superfluous claim elements that are not required to practice the claimed invention. Clarification is requested via amendment.
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 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 1-6, 8-16, 18-22 are rejected under 35 U.S.C. 103 as being unpatentable over Kong et al. (Computational Strategies for Proteogenomics Analysis, Dissertation, 2017, pp.1-149) in view of Weisser et al. (J. Proteome Res. 2016, 15, 4686-4695).
Regarding claim(s) 1, 11, 21, 22, Kong teaches methods of proteogenomics analysis. In particular, Kong teaches an efficient GPU-accelerated database search tool (EGADS) that receives MS/MS mass spectral data from a database. Kong does not specifically teach separating spectral files into a plurality of split spectral files comprising data corresponding to a predetermined range of precursor masses using the proteomics pipeline, as claimed. However, given the breadth of what is being claimed, Kong makes obvious this limitation by filtering out a specified range of m/z peaks in the input spectrum and sub-dividing files into unit m/z bins [page 20, Section 3.2.1], which at a minimum suggests separating files via splitting, as well as partitioning files into chunks that can be processed within the limited GPU memory [page 43, Section 3.3.1,], which also suggests splitting as claimed.
Furthermore, Weisser teaches an automated data analysis pipeline for analyzing proteomics data using the OpenMS computational framework [See entire]. In particular, Weisser teaches an software utility (MzMLSplitter) for splitting large spectral files into smaller equally sized spectral files that are more suitable for subsequent for pipeline analysis [page 4689, col. 2]. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to have modified the teachings of Kong by separating spectral files into spectral split files, as taught by Weisser, since Kong already suggests separating files within the pipeline and since applying software-based tools (i.e. splitter utility) to the proteomics data of Kong would have been well within the capabilities of one of ordinary skill in the art. The motivation would have been to optimize the query process by using smaller spectral files more suitable for GPU memory, as taught by Kong and Weisser.
Kong additionally teaches various methods for querying a protein database using scoring algorithms for identifying candidate peptides, wherein the search includes computing similarity scores and wherein the search was run on both CPU and GPU mode combinations [page 33, 36-39, and page 47-48, page 52 Figure 3-10]. Kong additionally teaches a peptide identification pipeline performed using three different database search engines [page 13].
Kong additionally teaches calculating an hyperscore for all candidates (which broadly reads on a final main score) and identifying top-N candidates based on specified search parameters [page 39], which reads on the claimed computing and identifying steps. Kong does not specifically teach combining scores of top-N candidates and a final main score. However, absent any limiting definitions or equations to the contrary, Kong at a minimum suggests this limitation since the hyperscore is expressed a linear combination of scores and then used for reporting top-N candidates.
Kong additionally teaches identifying novel top-N peptide candidates and then processing them using the tools from the Trans-Proteomics Pipeline (i.e. proteomics pipeline) [page 39, see also pages 27 and 80]. Kong does not specifically teach performing all of the above steps “using a proteomics pipeline running on a CPU and GPUs”, as claimed. However, Kong makes obvious this feature since their peptide identification pipeline was performed using different database search engines and for scoring and peptide identification purposes along with a TPP that operates on GPU and CPUs [see pages 13, 40, and as discussed above].
With regard to dependent claims 2, 3, 4, 5, 6, 8, 9, 10, 12, 13, 14, 15, 16, 18, 19, 20, the combination of Kong and Weisser teaches or suggests all aspects of these claims for the following reasons. Regarding claim(s) 2, 12, Kong teaches searching for PTMs [page 20, 24, 54]. Regarding claim(s) 3, 13, Kong teaches calculating scores for candidate peptides and then converting these into probability values [pages 7, 15 and Section 3.2.1]. Regarding claim(s) 4, 14, Kong teaches scoring algorithms and procedures for selecting a plurality of top candidates, as set forth above. Regarding claim(s) 5, 6, 7, 15, 16, 17, Kong teaches methods and multicore CPU and GPU systems that allow the fast identification of peptides using a parallel search algorithm, as discussed above [see also page 39 and Figures 3-3 and 3-5]. Regarding claim(s) 8, 18, Kong teaches searching databases comprising tryptic peptides [pages 12-13, Section 2.2.1]. Regarding claim(s) 9, 19, Kong teaches determining computational times associated with performing peptide identification functions as being over 150X faster than conventional database search tools [page viii]. Regarding claim(s) 10, 20, Kong teaches algorithms using GPUs to accelerate similarity scoring/searching by up 30-40X over conventional tools in common search scenarios, and another (MSFragger) that provides speed increase over 150X faster than existing tools [pages 80, see also pages 26, 27]. For these reasons, the claimed invention as a whole does not recite any new element, new function, or unpredictable result, and would have been prima facie obvious at the time it was made.
Claims 1-6, 8-16, 18-22 are rejected under 35 U.S.C. 103 as being unpatentable over Eng et al. (J Am SoccMass Spectrom, 1994, 5, 976-989) in view of Li et al. (BMC Bioinformatics 2014, 15:121, pp.1-11; IDS filed 03/18/2019) and Kong et al. (Computational Strategies for Proteogenomics Analysis, Dissertation, 2017, pp.1-149).
Regarding claim(s) 1, 11, 21, 22, Eng teaches a computational method for searching a protein database. In particular, Eng teaches receiving a spectral file comprising mass spectrometry-based proteomics data from a mass spectrometer (user device) [page 979 and Figure 1]. Eng teaches performing pre-search processing of spectral data that includes reduction of spectral data using predefined windows around precursor ions [page 979, Step 1], which at a minimum suggests separating spectral files as claimed absent any limiting definition to the contrary. Eng teaches searching a protein database to match spectral files to protein sequences and identifying candidate peptides [page 979, Step 2], which reads on querying and identifying as claimed. Eng teaches determining identification scores corresponding to candidate peptides, wherein the scoring process additionally includes identifying top-500 (i.e. top-N) peptide candidates and eliminating those that fail to rank in the top-500 [pages 981-82, Step 3]. Lastly, Eng teaches performing correlation-based scores (i.e. final scores) for top-500 sequences using a computer [page 979 and pages 982-85, Step 4], wherein the cross-correlation analysis broadly reads on identifying final scores used to select a final peptide.
Eng does not specifically teach using a proteomics pipeline (software) running on a CPU and GPU, and determining scores using a plurality of GPU cores as claimed. However, absent any limiting definition to the contrary, the claimed “proteomics pipeline” is reasonably interpreted as software facilitating the analysis of MS data as there is nothing in the claims or the specification that serve to describe any associated computations, algorithms, or equations that correspond to the claimed function.
Moreover, Li et al. (BMC Bioinformatics 2014, 15:121, pp.1-11; IDS filed 03/18/2019) teaches a method for improving the speed of mass spectrometry-based protein search identification using multi-GPU cores and parallel processors [page 2, col. 1] and a database comprising spectral data [page 3, entire, Table 2, Figure 3]. Alternatively, Kong teaches an efficient GPU-accelerated database search tool (EGADS) using MS/MS mass spectral data from a database and proteomics pipeline software, as set forth above.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to have modified the teachings of Eng by using software running on a CPU and GPU cores, as taught by Li and Hong, since such techniques were well known, routine, and conventional in the art of proteomics, and since Eng already teaches using computer software for performing search and scoring. The motivation would have been to improve the speed of proteomics searches using conventional computer technology.
With regard to dependent claims 2, 3, 4, 5, 6, 8, 9, 10, 12, 13, 14, 15, 16, 18, 19, 20, the combination of Eng, Li, and Kong teaches or suggests all aspects of these claims for the following reasons. Regarding claim(s) 2, 12, Kong teaches searching for PTMs [page 20, 24, 54]. Regarding claim(s) 3, 13, Kong teaches calculating scores for candidate peptides and then converting these into probability values [pages 7, 15 and Section 3.2.1]. Regarding claim(s) 4, 14, Kong teaches scoring algorithms and procedures for selecting a plurality of top candidates, as set forth above. Regarding claim(s) 5, 6, 7, 15, 16, 17, Kong teaches methods and multicore CPU and GPU systems that allow the fast identification of peptides using a parallel search algorithm, as discussed above [see also page 39 and Figures 3-3 and 3-5]. Regarding claim(s) 8, 18, Kong teaches searching databases comprising tryptic peptides [pages 12-13, Section 2.2.1]. Regarding claim(s) 9, 19, Kong teaches determining computational times associated with performing peptide identification functions as being over 150X faster than conventional database search tools [page viii]. Regarding claim(s) 10, 20, Kong teaches algorithms using GPUs to accelerate similarity scoring/searching by up 30-40X over conventional tools in common search scenarios, and another (MSFragger) that provides speed increase over 150X faster than existing tools [pages 80, see also pages 26, 27]. For these reasons, the claimed invention as a whole does not recite any new element, new function, or unpredictable result, and would have been prima facie obvious at the time it was made.
Response to Arguments
Applicant’s arguments, filed 07/16/2025, have been fully considered but are not persuasive but are moot in view of the modified rejections set forth above.
Conclusion
No claims are allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PABLO S WHALEY whose telephone number is (571)272-4425. The examiner can normally be reached between 1pm-9pm EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Anita Coope can be reached at 571-270-3614. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PABLO S WHALEY/Primary Examiner, Art Unit 3619