On the public citation graph

DART-ID increases single-cell proteome coverage

https://doi.org/10.1101/399121
0 signed · 72 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/mas.21488openalex-snapshot
Peptide retention time prediction
inferredcites →https://doi.org/10.1002/pmic.200800564openalex-snapshot
Database searching and accounting of multiplexed precursor and product ion spectra from the data independent analysis of simple and complex peptide mixtures
inferredcites →https://doi.org/10.1002/pmic.200900765openalex-snapshot
Fragmentation‐free LC‐MS can identify hundreds of proteins
inferredcites →https://doi.org/10.1002/pmic.201100425openalex-snapshot
Information‐dependent LC ‐ MS / MS acquisition with exclusion lists potentially generated on‐the‐fly: Case study using a whole cell digest of C lostridium thermocellum
inferredcites →https://doi.org/10.1002/pmic.201100463openalex-snapshot
Using i RT , a normalized retention time for more targeted measurement of peptides
inferredcites →https://doi.org/10.1002/pmic.201500488openalex-snapshot
High‐precision iRT prediction in the targeted analysis of data‐independent acquisition and its impact on identification and quantitation
inferredcites →https://doi.org/10.1016/0021-9673(86)80102-9openalex-snapshot
Prediction of peptide retention times in reversed-phase high-performance liquid chromatography I. Determination of retention coefficients of amino acid residues of model synthetic peptides
inferredcites →https://doi.org/10.1016/j.chroma.2006.03.114openalex-snapshot
A comparison of three algorithms for chromatograms alignment
inferredcites →https://doi.org/10.1016/j.jasms.2005.05.009openalex-snapshot
The Utility of Accurate Mass and LC Elution Time Information in the Analysis of Complex Proteomes
inferredcites →https://doi.org/10.1016/j.jchromb.2003.11.007openalex-snapshot
Protein identification by liquid chromatography–mass spectrometry using retention time prediction
inferredcites →https://doi.org/10.1016/s0021-9673(00)94457-1openalex-snapshot
Prediction of peptide retention times
inferredcites →https://doi.org/10.1021/ac0002386openalex-snapshot
Utility of Accurate Mass Tags for Proteome-Wide Protein Identification
inferredcites →https://doi.org/10.1021/ac0205154openalex-snapshot
Use of Artificial Neural Networks for the Accurate Prediction of Peptide Liquid Chromatography Elution Times in Proteome Analyses
inferredcites →https://doi.org/10.1021/ac0256890openalex-snapshot
Prediction of Chromatographic Retention and Protein Identification in Liquid Chromatography/Mass Spectrometry
inferredcites →https://doi.org/10.1021/ac025747hopenalex-snapshot
Empirical Statistical Model To Estimate the Accuracy of Peptide Identifications Made by MS/MS and Database Search
inferredcites →https://doi.org/10.1021/ac0341261openalex-snapshot
A Statistical Model for Identifying Proteins by Tandem Mass Spectrometry
inferredcites →https://doi.org/10.1021/ac048455kopenalex-snapshot
Quantitative Proteomic Analysis by Accurate Mass Retention Time Pairs
inferredcites →https://doi.org/10.1021/ac051437yopenalex-snapshot
XCMS: Processing Mass Spectrometry Data for Metabolite Profiling Using Nonlinear Peak Alignment, Matching, and Identification
inferredcites →https://doi.org/10.1021/ac060143popenalex-snapshot
Improved Peptide Elution Time Prediction for Reversed-Phase Liquid Chromatography-MS by Incorporating Peptide Sequence Information
inferredcites →https://doi.org/10.1021/ac060251bopenalex-snapshot
Use of Peptide Retention Time Prediction for Protein Identification by off-line Reversed-Phase HPLC−MALDI MS/MS
inferredcites →https://doi.org/10.1021/ac060777wopenalex-snapshot
Sequence-Specific Retention Calculator. Algorithm for Peptide Retention Prediction in Ion-Pair RP-HPLC: Application to 300- and 100-Å Pore Size C18 Sorbents
inferredcites →https://doi.org/10.1021/ac060913xopenalex-snapshot
Liquid Chromatography at Critical Conditions: Comprehensive Approach to Sequence-Dependent Retention Time Prediction
inferredcites →https://doi.org/10.1021/ac070262kopenalex-snapshot
Improving Tandem Mass Spectrum Identification Using Peptide Retention Time Prediction across Diverse Chromatography Conditions
inferredcites →https://doi.org/10.1021/ac9016693openalex-snapshot
Peptide Retention Standards and Hydrophobicity Indexes in Reversed-Phase High-Performance Liquid Chromatography of Peptides
inferredcites →https://doi.org/10.1021/acs.analchem.5b02287openalex-snapshot
PredRet: Prediction of Retention Time by Direct Mapping between Multiple Chromatographic Systems
inferredcites →https://doi.org/10.1021/acs.jproteome.6b00881openalex-snapshot
ABRF Proteome Informatics Research Group (iPRG) 2015 Study: Detection of Differentially Abundant Proteins in Label-Free Quantitative LC–MS/MS Experiments
inferredcites →https://doi.org/10.1021/acs.jproteome.7b00248openalex-snapshot
Targeted Feature Detection for Data-Dependent Shotgun Proteomics
inferredcites →https://doi.org/10.1021/acs.jproteome.7b00836openalex-snapshot
CharmeRT: Boosting Peptide Identifications by Chimeric Spectra Identification and Retention Time Prediction
inferredcites →https://doi.org/10.1021/acs.jproteome.8b00257openalex-snapshot
Transformative Opportunities for Single-Cell Proteomics
inferredcites →https://doi.org/10.1021/acs.jproteome.8b00484openalex-snapshot
Innovations in Proteomics: The Drive to Single Cells
inferredcites →https://doi.org/10.1021/acs.jproteome.8b00737openalex-snapshot
Web-Based Search Tool for Visualizing Instrument Performance Using the Triple Knockout (TKO) Proteome Standard
inferredcites →https://doi.org/10.1021/pr049780ropenalex-snapshot
Prediction of Peptide Retention at Different HPLC Conditions from Multiple Linear Regression Models
inferredcites →https://doi.org/10.1021/pr049965yopenalex-snapshot
Application of Peptide LC Retention Time Information in a Discriminant Function for Peptide Identification by Tandem Mass Spectrometry
inferredcites →https://doi.org/10.1021/pr1005058openalex-snapshot
Training, Selection, and Robust Calibration of Retention Time Models for Targeted Proteomics
inferredcites →https://doi.org/10.1021/pr100594kopenalex-snapshot
Efficient Marginalization to Compute Protein Posterior Probabilities from Shotgun Mass Spectrometry Data
inferredcites →https://doi.org/10.1021/pr101065jopenalex-snapshot
Andromeda: A Peptide Search Engine Integrated into the MaxQuant Environment
inferredcites →https://doi.org/10.1021/pr700739dopenalex-snapshot
Posterior Error Probabilities and False Discovery Rates: Two Sides of the Same Coin
inferredcites →https://doi.org/10.1021/pr900064bopenalex-snapshot
Improving Peptide Identification in Proteome Analysis by a Two-Dimensional Retention Time Filtering Approach
inferredcites →https://doi.org/10.1038/nbt.1511openalex-snapshot
MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification
inferredcites →https://doi.org/10.1038/nbt.2841openalex-snapshot
OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data
inferredcites →https://doi.org/10.1038/nmeth.4075openalex-snapshot
moFF: a robust and automated approach to extract peptide ion intensities
inferredcites →https://doi.org/10.1038/nmeth1019openalex-snapshot
Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry
inferredcites →https://doi.org/10.1038/nmeth1113openalex-snapshot
Semi-supervised learning for peptide identification from shotgun proteomics datasets
inferredcites →https://doi.org/10.1038/nprot.2006.427openalex-snapshot
A practical recipe for stable isotope labeling by amino acids in cell culture (SILAC)
inferredcites →https://doi.org/10.1038/nprot.2016.136openalex-snapshot
The MaxQuant computational platform for mass spectrometry-based shotgun proteomics
inferredcites →https://doi.org/10.1038/srep43959openalex-snapshot
Locus-specific Retention Predictor (LsRP): A Peptide Retention Time Predictor Developed for Precision Proteomics
inferredcites →https://doi.org/10.1042/ebc20180014openalex-snapshot
Single cell protein analysis for systems biology
inferredcites →https://doi.org/10.1073/pnas.77.3.1632openalex-snapshot
Prediction of peptide retention times in high-pressure liquid chromatography on the basis of amino acid composition
inferredcites →https://doi.org/10.1074/mcp.m113.031591openalex-snapshot
Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ
inferredcites →https://doi.org/10.1074/mcp.m400031-mcp200openalex-snapshot
An Improved Model for Prediction of Retention Times of Tryptic Peptides in Ion Pair Reversed-phase HPLC
inferredcites →https://doi.org/10.1074/mcp.o111.016717openalex-snapshot
Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis
inferredcites →https://doi.org/10.1074/mcp.o115.055475openalex-snapshot
DeMix-Q: Quantification-Centered Data Processing Workflow
inferredcites →https://doi.org/10.1093/bioinformatics/btl219openalex-snapshot
Semi-supervised LC/MS alignment for differential proteomics
inferredcites →https://doi.org/10.1093/bioinformatics/btl276openalex-snapshot
A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS
inferredcites →https://doi.org/10.1093/bioinformatics/btp052openalex-snapshot
Retention time alignment algorithms for LC/MS data must consider non-linear shifts
inferredcites →https://doi.org/10.1093/bioinformatics/btq054openalex-snapshot
Skyline: an open source document editor for creating and analyzing targeted proteomics experiments
inferredcites →https://doi.org/10.1101/399774openalex-snapshot
Automated sample preparation for high-throughput single-cell proteomics
inferredcites →https://doi.org/10.1186/1471-2105-11-395openalex-snapshot
MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data
inferredcites →https://doi.org/10.1186/1471-2105-8-468openalex-snapshot
Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational proteomics
inferredcites →https://doi.org/10.1186/1471-2105-9-375openalex-snapshot
Critical assessment of alignment procedures for LC-MS proteomics and metabolomics measurements
inferredcites →https://doi.org/10.1186/s13059-018-1547-5openalex-snapshot
SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation
inferredcites →https://doi.org/10.1371/journal.pcbi.1005535openalex-snapshot
Post-transcriptional regulation across human tissues
inferredcites →https://doi.org/10.18637/jss.v076.i01openalex-snapshot
Stan : A Probabilistic Programming Language
inferredcites →https://doi.org/10.7490/f1000research.1096450.1openalex-snapshot
Spectronaut A fast and efficient algorithm for MRM-like processing of data independent acquisition (SWATH-MS) data

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1038/s41592-023-01830-1openalex-snapshot
Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics
inferred← citeshttps://doi.org/10.1038/s41596-021-00616-zopenalex-snapshot
Multiplexed single-cell proteomics using SCoPE2
inferred← citeshttps://doi.org/10.1101/399774openalex-snapshot
Automated sample preparation for high-throughput single-cell proteomics
inferred← citeshttps://doi.org/10.1186/s13059-018-1547-5openalex-snapshot
SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation
inferred← citeshttps://doi.org/10.17760/d20474745openalex-snapshot
Increasing the consistency, coverage, and selectivity of single-cell proteomics via priortized LC-MS/MS sample analysis methods
inferred← citeshttps://doi.org/10.26434/chemrxiv-2023-rvr9nopenalex-snapshot
MS²Rescore 3.0 is a modular, flexible, anduser-friendly platform to boost peptideidentifications, as showcased with MS Amanda 3.0
inferred← citeshttps://doi.org/10.26434/chemrxiv-2023-rvr9n-v2openalex-snapshot
MS²Rescore 3.0 is a modular, flexible, anduser-friendly platform to boost peptideidentifications, as showcased with MS Amanda 3.0
inferred← citeshttps://doi.org/10.3390/ijms22094776openalex-snapshot
Proteomics: A Tool to Study Platelet Function
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.