B. Searle
Molecular Biology · 2010–2018
A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 56 citations into it; #3,651 of 17,773 by trust here, #14,176 by citations
- Spectroscopy — 53 citations into it; #273 of 1,674 by trust here, #1,278 by citations
Whom B. Searle trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Hugh G. Jr Gauch
- Alexey I. Nesvizhskii
- Lewis Y. Geer
- R. Aebersold
- Paola Picotti
- Guo‐Zhong Li
- R. Craig
- Yoav Benjamini
- Jacques Colinge
- David L. Tabb
Who trusts B. Searle overall
- Jimmy K. Eng
- Karlie A. Neilson
- Tahmina A. Jahan
- Alexey I. Nesvizhskii
- Fengchao Yu
- Michael R. Hoopmann
- Naveid A. Ali
- S. Muralidharan
- Eric W. Deutsch
Papers from B. Searle's perspective
Ordered by how strongly the researchers B. Searle trusts endorse each paper. Same corpus, a different order for every researcher.
- A common open representation of mass spectrometry data and its application to proteomics research (Nature Biotechnology)
- mProphet: automated data processing and statistical validation for large-scale SRM experiments (Nature Methods)
- Open mass spectrometry search algorithm. (Journal of Proteome Research)
- Computational prediction of proteotypic peptides for quantitative proteomics (Nature Biotechnology)
- Selected reaction monitoring for quantitative proteomics: a tutorial (Molecular Systems Biology)
- OLAV: Towards high‐throughput tandem mass spectrometry data identification (Proteomics)
- A statistical model for identifying proteins by tandem mass spectrometry.
- Options and considerations when selecting a quantitative proteomics strategy (Nature Biotechnology)
- Open source system for analyzing, validating, and storing protein identification data. (Journal of Proteome Research)
- Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics (Cell)
Their papers
- The Skyline Ecosystem: Informatics for Quantitative Mass Spectrometry Proteomics (2017) — 676 citations
- Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry (2018) — 474 citations
- Scaffold: A bioinformatic tool for validating MS/MS‐based proteomic studies (2010) — 553 citations