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Paper Citation Record · LEDGER
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data
As of 19 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2506.01540.
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37 of 37 outbound references displayed
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Outbound references
Observation cfdd2a47-b88c-4802-ad04-ef8df8aef66c · outbound
This paper cites Deconvolution analysis of hormone data.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Deconvolution analysis of hormone data
Reference 1
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Observation 8cfac282-2ee1-42a1-9afd-0fefd5eac1f6 · outbound
This paper cites Cdseqr: fas t complete deconvolution for gene expression data from bulk tissues.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Cdseqr: fas t complete deconvolution for gene expression data from bulk tissues
Reference 2
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Observation d7d34ec1-3634-467a-95da-64e24962deea · outbound
This paper cites Density deconvolu tion with laplace errors and unknown variance.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Density deconvolu tion with laplace errors and unknown variance
Reference 3
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Observation b2031c16-35d1-47b9-97b1-e3078308813b · outbound
This paper cites L., Byers, J., Cabral, S., Celi, L.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data L., Byers, J., Cabral, S., Celi, L
Reference 4
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Observation b007406b-efac-4558-ab42-6da237e652a8 · outbound
This paper cites Information bias in health research: Defi nition, pitfalls, and adjustment methods.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Information bias in health research: Defi nition, pitfalls, and adjustment methods
Reference 5
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Observation 9c4e5fcb-727c-4af5-91d4-96c156360627 · outbound
This paper cites Biological variation: Understanding why it is so important? Practical Laboratory Medicine , 23:e00199, Jan 2021.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Biological variation: Understanding why it is so important? Practical Laboratory Medicine , 23:e00199, Jan 2021
Reference 6
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Observation 868d83b7-4e04-4c34-a6a2-ee1e4a7d0021 · outbound
This paper cites C., Fialkowski, M.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data C., Fialkowski, M
Reference 7
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2a0b9e5a-7fad-4ee7-b167-51d69e087821 · outbound
This paper cites B., Eekhout, I., Boers, M., van der Vleuten, C.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data B., Eekhout, I., Boers, M., van der Vleuten, C
Reference 8
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Observation be093e9e-996d-4cfa-a0b4-1a7405fe03f5 · outbound
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A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Unresolved cited work
Reference 9
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Observation e4bf41fe-12c5-44bc-9563-95753491888e · outbound
This paper cites Systematic er rors in peptide and protein identification and quantifi- cation by modified peptides.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Systematic er rors in peptide and protein identification and quantifi- cation by modified peptides
Reference 10
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Observation 78fd2316-86c0-4208-b049-19f033e44401 · outbound
This paper cites an unresolved cited work.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Unresolved cited work
Reference 11
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Observation 4548a3d0-8336-42c0-b8c9-611767514798 · outbound
This paper cites Density estimation with het eroscedastic error.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Density estimation with het eroscedastic error
Reference 12
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Observation d2c013d0-bd79-487f-a071-4cb0b32afa22 · outbound
This paper cites On deconvolution w ith repeated measurements.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data On deconvolution w ith repeated measurements
Reference 13
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Observation 43982fea-dae5-4e74-9e40-8bc3cba37777 · outbound
This paper cites Density estimation in the p resence of heteroscedastic measurement error of un- known type using phase function deconvolution.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Density estimation in the p resence of heteroscedastic measurement error of un- known type using phase function deconvolution
Reference 14
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Observation a9e196a5-d885-4b02-8799-967a61f5b870 · outbound
This paper cites Deconvolution estimation in measu rement error models: The r package decon.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Deconvolution estimation in measu rement error models: The r package decon
Reference 15
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Observation e57b92b1-e708-442b-a195-0e3630bd29f5 · outbound
This paper cites Delaigle and P.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Delaigle and P
Reference 16
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Observation 7485f0d9-236d-479f-bff2-d3b7612d95e9 · outbound
This paper cites Comparative analysis of cell mixtures deconvolut ion and gene signatures generated for blood, immune and cancer cells.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Comparative analysis of cell mixtures deconvolut ion and gene signatures generated for blood, immune and cancer cells
Reference 17
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Observation 2de376a6-b0e6-4238-abe6-df17b93fafd5 · outbound
This paper cites Proteome-wide analysis reveals an age-associated cellular phenotype of in situ age d human fibroblasts.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Proteome-wide analysis reveals an age-associated cellular phenotype of in situ age d human fibroblasts
Reference 18
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Observation 4efcbe5a-7cbb-4dd3-8745-4b6c93f7151d · outbound
This paper cites A fourier approach to nonparamet ric deconvolution of a density estimate.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data A fourier approach to nonparamet ric deconvolution of a density estimate
Reference 19
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Observation 41947eed-6389-4d41-ad9a-50c334b45a2d · outbound
This paper cites On the effect of estimating the error densi ty in nonparametric deconvolution.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data On the effect of estimating the error densi ty in nonparametric deconvolution
Reference 20
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Observation 242c5574-6b96-429a-845e-b677dc16a0ff · outbound
This paper cites Real and Complex Analysis.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Real and Complex Analysis
Reference 21
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Observation 9a55649b-7af2-4795-82c0-4b10c5ee4cc5 · outbound
This paper cites F ourier Transforms.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data F ourier Transforms
Reference 22
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Observation 9ce44aa9-8328-42fe-98bf-28a9e7be402a · outbound
This paper cites On the optimal rates of convergence for nonparam etric deconvolution problems.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data On the optimal rates of convergence for nonparam etric deconvolution problems
Reference 23
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 58f7919c-9d29-41a8-93e1-e3b72a2634f3 · outbound
This paper cites Numerical calculation of stable densities a nd distribution functions.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Numerical calculation of stable densities a nd distribution functions
Reference 24
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9e8e1c55-d425-4231-a336-f35c926b35ab · outbound
This paper cites and Shanthikumar, J.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data and Shanthikumar, J
Reference 25
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Observation 196651d6-5f17-4f28-b0aa-fef6c6e9020a · outbound
This paper cites Bootstrap bandwidth select ion in kernel density estimation from a contaminated sample.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Bootstrap bandwidth select ion in kernel density estimation from a contaminated sample
Reference 26
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- verified fuzzy
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Source-reported events for the cited work
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Observation e0d938ce-1a7f-497d-ace5-2858e4f26538 · outbound
This paper cites Using specially designed ex ponential families for density estimation.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Using specially designed ex ponential families for density estimation
Reference 27
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Source-reported events for the cited work
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Observation 6d8b46ea-67e2-4950-9aa7-e92589fb143b · outbound
This paper cites Empirical bayes analysis of single nucleotide polymorphisms.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Empirical bayes analysis of single nucleotide polymorphisms
Reference 28
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 282f6a48-114e-4981-a46e-248269a8093e · outbound
This paper cites Springer Berlin Heidelberg, Berlin, Heidelberg, 2015.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Springer Berlin Heidelberg, Berlin, Heidelberg, 2015
Reference 29
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Observation f6c95050-db59-40e6-8c99-aa1760ac8673 · outbound
This paper cites deconvolve: Deconvol ution tools for measurement error problems.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data deconvolve: Deconvol ution tools for measurement error problems
Reference 30
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Observation 3e6ea395-5b25-4231-91c2-fa9fc75b214b · outbound
This paper cites The roles of ise and mise in density estimatio n.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data The roles of ise and mise in density estimatio n
Reference 31
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Observation d07d9445-79c4-407b-9a08-9fa845ca1da8 · outbound
This paper cites Functional k-sample problem when data are density functions.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Functional k-sample problem when data are density functions
Reference 32
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Observation e92a83ef-1eda-42f8-a80e-2cb1f348697d · outbound
This paper cites NPFD: N-Power F ourier Deconvolution, 2024.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data NPFD: N-Power F ourier Deconvolution, 2024
Reference 33
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f56eece6-7e3b-4413-b703-fb97ad85eb52 · outbound
This paper cites Deconvoluting kernel den sity estimators.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Deconvoluting kernel den sity estimators
Reference 34
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3391efc1-0c0f-4c38-ba6e-e12a596b1992 · outbound
This paper cites Periodogram analysis and continuous spe ctra.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Periodogram analysis and continuous spe ctra
Reference 35
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 20447749-150d-4a5f-9cf4-43e9200e2393 · outbound
This paper cites On optimal and data-based histograms.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data On optimal and data-based histograms
Reference 36
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- raw_fallback, observed 2026-08-07T11:47:51.892898Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d2d4f418-1b0d-44fb-8ac2-0fe28edaf0d6 · outbound
This paper cites Data-based choice of histogram bin width.
A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Data-based choice of histogram bin width
Reference 37
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- raw_fallback, observed 2026-08-07T11:47:51.821332Z
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