Paper Citation Record · LEDGER

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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measured 37 of 37 reference resolution

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

Reference 11

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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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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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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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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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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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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:48:04.331113Z

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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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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:48:04.276594Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:48:04.255668Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:47:52.121711Z

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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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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

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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

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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

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