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Computer Science

D-Index
43
Citations
21446
World Ranking
7742
National Ranking
3343

Overview

Brendan MacLean is affiliated with the University of Washington in the United States. Their research primarily spans the fields of Chemistry and Biochemistry, Genetics, and Molecular Biology, with a focused contribution to subfields including Spectroscopy, Molecular Biology, Information Systems and Management, Information Systems, and Ecology.

The scientist's work is centered around several main topics such as Advanced Proteomics Techniques and Applications, Mass Spectrometry Techniques and Applications, and Metabolomics and Mass Spectrometry Studies. Additional areas of involvement include Scientific Computing and Data Management, Research Data Management Practices, Analytical Chemistry and Chromatography, and Machine Learning in Bioinformatics.

Brendan MacLean has been published extensively in a range of scientific journals. Frequent publication venues comprise the Journal of Proteome Research, bioRxiv (Cold Spring Harbor Laboratory), Nature Communications, Nucleic Acids Research, and Nature Methods.

Their recent papers include:

  • The ProteomeXchange consortium at 10 years: 2023 update (2022, Nucleic Acids Research)
  • Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics (2020, Journal of Proteome Research)
  • Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data-Independent Acquisition (2023, Journal of Proteome Research)
  • MSstats Version 4.0: Statistical Analyses of Quantitative Mass Spectrometry-Based Proteomic Experiments with Chromatography-Based Quantification at Scale (2023, Journal of Proteome Research)
  • LipidCreator workbench to probe the lipidomic landscape (2020, Nature Communications)

Their collaborative network includes frequent co-authors such as Michael J. MacCoss, Nicholas Shulman, Michael Riffle, Brian Pratt, and Vagisha Sharma.

Best Publications

  • Skyline: an open source document editor for creating and analyzing targeted proteomics experiments

    Brendan MacLean;Daniela M. Tomazela;Nicholas Shulman;Matthew Chambers

  • A cross-platform toolkit for mass spectrometry and proteomics

    Matthew C Chambers;Brendan Maclean;Robert Burke;Dario Amodei

  • MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments

    Meena Choi;Ching-Yun Chang;Timothy Clough;Daniel Broudy

  • Using iRT, a normalized retention time for more targeted measurement of peptides

    Claudia Escher;Lukas Reiter;Brendan MacLean;Reto Ossola

  • The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics.

    Lindsay K. Pino;Brian C. Searle;James G. Bollinger;Brook Nunn

  • The ProteomeXchange consortium in 2020: enabling 'big data' approaches in proteomics.

    Eric W. Deutsch;Nuno Bandeira;Nuno Bandeira;Vagisha Sharma;Yasset Pérez-Riverol

  • Targeted Peptide Measurements in Biology and Medicine: Best Practices for Mass Spectrometry-based Assay Development Using a Fit-for-Purpose Approach

    Steven A. Carr;Susan E. Abbatiello;Bradley L. Ackermann;Christoph Borchers

  • Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics

    Kendra J. Adams;Brian Pratt;Neelanjan Bose;Laura G. Dubois

  • Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry

    Brian C. Searle;Lindsay K. Pino;Jarrett D. Egertson;Ying S. Ting

  • Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline APPLICATION TO PROTEIN ACETYLATION AND PHOSPHORYLATION

    Birgit Schilling;Matthew J. Rardin;Brendan X. MacLean;Anna M. Zawadzka

  • A multicenter study benchmarks software tools for label-free proteome quantification

    Pedro Navarro;Jörg Kuharev;Ludovic C. Gillet;Oliver M. Bernhardt

  • Building high-quality assay libraries for targeted analysis of SWATH MS data

    Olga T. Schubert;Ludovic C. Gillet;Ben C. Collins;Pedro Navarro

  • Multiplexed MS/MS for improved data-independent acquisition

    Jarrett D Egertson;Andreas Kuehn;Gennifer E Merrihew;Nicholas W Bateman

  • CPTAC Assay Portal: a repository of targeted proteomic assays

    Jeffrey R. Whiteaker;Goran N. Halusa;Andrew N. Hoofnagle;Vagisha Sharma

  • Panorama Public: A Public Repository for Quantitative Data Sets Processed in Skyline.

    Vagisha Sharma;Josh Eckels;Birgit Schilling;Christina Ludwig

  • General framework for developing and evaluating database scoring algorithms using the TANDEM search engine

    Brendan Maclean;Jimmy K. Eng;Ronald C. Beavis;Martin Mcintosh

  • Multiplexed peptide analysis using data-independent acquisition and Skyline

    Jarrett D Egertson;Brendan MacLean;Richard Johnson;Yue Xuan

  • Panorama: a targeted proteomics knowledge base.

    Vagisha Sharma;Josh Eckels;Greg K. Taylor;Nicholas J. Shulman

  • Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses

    George Rosenberger;George Rosenberger;Isabell Bludau;Isabell Bludau;Uwe Schmitt;Moritz Heusel;Moritz Heusel

  • Computational Proteomics Analysis System (CPAS): an extensible, open-source analytic system for evaluating and publishing proteomic data and high throughput biological experiments.

    Adam Rauch;Matthew Bellew;Jimmy Eng;Matthew Fitzgibbon

  • Peptide-Centric Proteome Analysis: An Alternative Strategy for the Analysis of Tandem Mass Spectrometry Data

    Ying Sonia Ting;Jarrett D. Egertson;Samuel H. Payne;Sangtae Kim

Frequent Co-Authors

Michael J. MacCoss
Michael J. MacCoss University of Washington
Birgit Schilling
Birgit Schilling Buck Institute for Research on Aging
Steven A. Carr
Steven A. Carr Broad Institute
daniel c liebler
daniel c liebler Vanderbilt University
Bradford W. Gibson
Bradford W. Gibson Buck Institute for Research on Aging
Amanda G. Paulovich
Amanda G. Paulovich Fred Hutchinson Cancer Research Center
Henry Rodriguez
Henry Rodriguez National Institutes of Health
Christoph H. Borchers
Christoph H. Borchers McGill University
Thomas A. Neubert
Thomas A. Neubert New York University

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