Ludovic C. Gillet

Molecular Biology · 2006–2018

A researcher in the Science corpus: 5 papers; trusts 4 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Ludovic C. Gillet trusts overall

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

  1. R. Aebersold
  2. B. Domon
  3. Paola Picotti
  4. John D. Venable
  5. Lukas Reiter
  6. Jüergen Cox
  7. Matthias Mann
  8. Minoru Kanehisa
  9. V. Lange
  10. Annette Michalski

Who trusts Ludovic C. Gillet overall

  1. L. Galluzzi
  2. M. Larance
  3. Sumit Ghosh
  4. Alexandra C. Schrimpe-Rutledge
  5. Lindsay K. Pino
  6. Christina Ludwig
  7. Eric W. Deutsch
  8. Chih-Chiang Tsou
  9. Angus I. Lamond
  10. B. Searle

Papers from Ludovic C. Gillet's perspective

Ordered by how strongly the researchers Ludovic C. Gillet trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Global analysis of protein expression in yeast (Nature)
  2. Computational prediction of proteotypic peptides for quantitative proteomics (Nature Biotechnology)
  3. Multi-site assessment of the precision and reproducibility of multiple reaction monitoring–based measurements of proteins in plasma (Nature Biotechnology)
  4. 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)
  5. Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics (Cell)
  6. mProphet: automated data processing and statistical validation for large-scale SRM experiments (Nature Methods)
  7. Options and considerations when selecting a quantitative proteomics strategy (Nature Biotechnology)
  8. KEGG for representation and analysis of molecular networks involving diseases and drugs (Nucleic Acids Res.)
  9. A model for random sampling and estimation of relative protein abundance in shotgun proteomics. (Analytical Chemistry)
  10. MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments (Bioinform.)

Their papers