Chih-Chiang Tsou

Molecular Biology · 2015–2016

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Chih-Chiang Tsou trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Alexey I. Nesvizhskii
  2. Alejandro Wolf-Yadlin
  3. Eric W. Deutsch
  4. Ralf Tautenhahn
  5. Marcus Bantscheff
  6. R. Aebersold
  7. David D. Shteynberg
  8. John D. Venable
  9. Lukas Reiter
  10. Guo‐Zhong Li

Who trusts Chih-Chiang Tsou overall

  1. Fengchao Yu
  2. Lindsay K. Pino
  3. S. Haynes

Papers from Chih-Chiang Tsou's perspective

Ordered by how strongly the researchers Chih-Chiang Tsou trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. (Analytical Chemistry)
  2. A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics (Journal of Proteomics)
  3. Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis* (Molecular & Cellular Proteomics)
  4. A Guided Tour of the Trans-Proteomic Pipeline (Proteomics)
  5. mProphet: automated data processing and statistical validation for large-scale SRM experiments (Nature Methods)
  6. More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC-MS/MS. (Journal of Proteome Research)
  7. A model for random sampling and estimation of relative protein abundance in shotgun proteomics. (Analytical Chemistry)
  8. Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra (Nature Methods)
  9. Faculty Opinions recommendation of Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.
  10. iProphet: Multi-level Integrative Analysis of Shotgun Proteomic Data Improves Peptide and Protein Identification Rates and Error Estimates* (Molecular & Cellular Proteomics)

Their papers