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A nonparametric statistical method for deconvolving densities in the analysis of proteomic data

As of 8 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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pith.paper-citation-record.v1
2506.01540 v1

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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

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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

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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

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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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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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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

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This paper cites C., Fialkowski, M.

A nonparametric statistical method for deconvolving densities in the analysis of proteomic data C., Fialkowski, M

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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

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A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Unresolved cited work

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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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A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Unresolved cited work

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A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Density estimation with het eroscedastic error

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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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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

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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

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A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Delaigle and P

Reference 16

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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

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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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A nonparametric statistical method for deconvolving densities in the analysis of proteomic data A fourier approach to nonparamet ric deconvolution of a density estimate

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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

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A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Real and Complex Analysis

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A nonparametric statistical method for deconvolving densities in the analysis of proteomic data F ourier Transforms

Reference 22

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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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A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Numerical calculation of stable densities a nd distribution functions

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A nonparametric statistical method for deconvolving densities in the analysis of proteomic data and Shanthikumar, J

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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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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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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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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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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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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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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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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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A nonparametric statistical method for deconvolving densities in the analysis of proteomic data Deconvoluting kernel den sity estimators

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:47:52.034108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:47:51.430395Z digest=sha256:6b517d0d91113b3ac3608842e1535f88643d04c1b48aade7ae3d0ae3b3e97dde

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:47:51.955140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:47:51.543624Z digest=sha256:a133043e15b737e9e67aef3eddedce09d642f75c1441c5b3bedae7ffbff78587

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

Resolution
verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:47:51.594747Z digest=sha256:2eb2be0d4e1ac7e9a4ce93c724379c53d6269f0e65503427b48d4d0359fdcdc0

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:47:51.821332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T11:47:51.744920Z digest=sha256:4a676065fccab7c9de53c9a6a37a92b7e3dc328291a9c90a196fdefe886b4a99

Pith citing papers

No inbound Pith citation observations are available.