VLDB 2026 Research / reviewers in the wild / expert
Matthew E. Monroe
dblp:53/2155
· DBLP profile ↗
9ranked-venue papers
1as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 9 · 1 first-authorSoftware engineering, systems software and programming languages · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
7 papers |
Bioinformatics and computational biology · 100% |
Topics — the 10 heaviest of 10, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
proteomics |
0.6 | 5 | 2015 | Correcting systematic bias and instrument measurement drift with mzRefinery · Bioinform. 2015 LC-IMS-MS Feature Finder: detecting multidimensional liquid chromatography, ion mobility and mass spectrometry features in complex datasets · Bioinform. 2013 Machine learning based prediction for peptide drift times in ion mobility spectrometry · Bioinform. 2010 |
Bioinformatics and computational biology › proteomics
mass spectrometry data analysis |
0.5 | 4 | 2015 | Correcting systematic bias and instrument measurement drift with mzRefinery · Bioinform. 2015 LC-IMS-MS Feature Finder: detecting multidimensional liquid chromatography, ion mobility and mass spectrometry features in complex datasets · Bioinform. 2013 DeconMSn: a software tool for accurate parent ion monoisotopic mass determination for tandem mass spectra · Bioinform. 2008 |
Bioinformatics and computational biology › functional genomics
functional enrichment analysis |
0.4 | 1 | 2019 | Lipid Mini-On: mining and ontology tool for enrichment analysis of lipidomic data · Bioinform. 2019 |
Bioinformatics and computational biology › metabolomics
lipidomics |
0.4 | 1 | 2019 | Lipid Mini-On: mining and ontology tool for enrichment analysis of lipidomic data · Bioinform. 2019 |
Bioinformatics and computational biology › metabolomics
collision cross section calculation |
0.3 | 1 | 2017 | PIXiE: an algorithm for automated ion mobility arrival time extraction and collision cross section calculation using global data association · Bioinform. 2017 |
Bioinformatics and computational biology
metabolomics |
0.3 | 1 | 2017 | PIXiE: an algorithm for automated ion mobility arrival time extraction and collision cross section calculation using global data association · Bioinform. 2017 |
Bioinformatics and computational biology › proteomics
peptide-spectrum matching |
0.2 | 1 | 2015 | Correcting systematic bias and instrument measurement drift with mzRefinery · Bioinform. 2015 |
Bioinformatics and computational biology › proteomics
peptide identification |
0.1 | 1 | 2007 | VIPER: an advanced software package to support high-throughput LC-MS peptide identification · Bioinform. 2007 |
Bioinformatics and computational biology
isotope labeling |
0.0 | 1 | 2007 | VIPER: an advanced software package to support high-throughput LC-MS peptide identification · Bioinform. 2007 |
Bioinformatics and computational biology › proteomics
quantitative proteomics |
0.0 | 1 | 2007 | VIPER: an advanced software package to support high-throughput LC-MS peptide identification · Bioinform. 2007 |
Methods — techniques the papers use, named apart from their topics
text mining · 0.4network visualization · 0.4enrichment analysis · 0.4global data association · 0.3regression-based calibration · 0.2deisotoping · 0.2clustering · 0.2support vector regression · 0.1partial least squares regression · 0.1machine learning · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Lipid Mini-On: mining and ontology tool for enrichment analysis of lipidomic dataabstractSUMMARY: Here we introduce Lipid Mini-On, an open-source tool that performs lipid enrichment analyses and visualizations of lipidomics data. Lipid Mini-On uses a text-mining process to bin individual lipid names into multiple lipid ontology groups based on the classification (e.g. LipidMaps) and other characteristics, such as chain length. Lipid Mini-On provides users with the capability to conduct enrichment analysis of the lipid ontology terms using a Shiny app with options of five statistical approaches. Lipid classes can be added to customize the user's database and remain updated as new lipid classes are discovered. Visualization of results is available for all classification options (e.g. lipid subclass and individual fatty acid chains). Results are also visualized through an editable network of relationships between the individual lipids and their associated lipid ontology terms. The utility of the tool is demonstrated using biological (e.g. human lung endothelial cells) and environmental (e.g. peat soil) samples. AVAILABILITY AND IMPLEMENTATION: Rodin (R package: https://github.com/PNNL-Comp-Mass-Spec/Rodin), Lipid Mini-On Shiny app (https://github.com/PNNL-Comp-Mass-Spec/LipidMiniOn) and Lipid Mini-On online tool (https://omicstools.pnnl.gov/shiny/lipid-mini-on/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Geremy Clair, Sarah Reehl, Kelly G. Stratton, Matthew E. Monroe, Malak M. Tfaily, Charles Ansong, Jennifer E. Kyle |
Bioinform. | 4 |
| 2017 | PIXiE: an algorithm for automated ion mobility arrival time extraction and collision cross section calculation using global data associationabstractMOTIVATION: Drift tube ion mobility spectrometry coupled with mass spectrometry (DTIMS-MS) is increasingly implemented in high throughput omics workflows, and new informatics approaches are necessary for processing the associated data. To automatically extract arrival times for molecules measured by DTIMS at multiple electric fields and compute their associated collisional cross sections (CCS), we created the PNNL Ion Mobility Cross Section Extractor (PIXiE). The primary application presented for this algorithm is the extraction of data that can then be used to create a reference library of experimental CCS values for use in high throughput omics analyses. RESULTS: We demonstrate the utility of this approach by automatically extracting arrival times and calculating the associated CCSs for a set of endogenous metabolites and xenobiotics. The PIXiE-generated CCS values were within error of those calculated using commercially available instrument vendor software. AVAILABILITY AND IMPLEMENTATION: PIXiE is an open-source tool, freely available on Github. The documentation, source code of the software, and a GUI can be found at https://github.com/PNNL-Comp-Mass-Spec/PIXiE and the source code of the backend workflow library used by PIXiE can be found at https://github.com/PNNL-Comp-Mass-Spec/IMS-Informed-Library . CONTACT: [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Cameron P. Casey, Xueyun Zheng, Yehia M. Ibrahim, Christopher S. Wilkins, Ryan S. Renslow, Dennis G. Thomas, Samuel H. Payne, Matthew E. Monroe, Richard D. Smith, Justin G. Teeguarden, Erin S. Baker, Thomas O. Metz |
Bioinform. | 9 |
| 2015 | Correcting systematic bias and instrument measurement drift with mzRefineryabstractMOTIVATION: Systematic bias in mass measurement adversely affects data quality and negates the advantages of high precision instruments. RESULTS: We introduce the mzRefinery tool for calibration of mass spectrometry data files. Using confident peptide spectrum matches, three different calibration methods are explored and the optimal transform function is chosen. After calibration, systematic bias is removed and the mass measurement errors are centered at 0 ppm. Because it is part of the ProteoWizard package, mzRefinery can read and write a wide variety of file formats. AVAILABILITY AND IMPLEMENTATION: The mzRefinery tool is part of msConvert, available with the ProteoWizard open source package at http://proteowizard.sourceforge.net/ CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Bryson C. Gibbons, Matthew Chambers, Matthew E. Monroe, David L. Tabb, Samuel H. Payne |
Bioinform. | 3 |
| 2013 | LC-IMS-MS Feature Finder: detecting multidimensional liquid chromatography, ion mobility and mass spectrometry features in complex datasetsabstractMOTIVATION: The addition of ion mobility spectrometry to liquid chromatography-mass spectrometry experiments requires new, or updated, software tools to facilitate data processing. RESULTS: We introduce a command line software application LC-IMS-MS Feature Finder that searches for molecular ion signatures in multidimensional liquid chromatography-ion mobility spectrometry-mass spectrometry (LC-IMS-MS) data by clustering deisotoped peaks with similar monoisotopic mass, charge state, LC elution time and ion mobility drift time values. The software application includes an algorithm for detecting and quantifying co-eluting chemical species, including species that exist in multiple conformations that may have been separated in the IMS dimension. AVAILABILITY: LC-IMS-MS Feature Finder is available as a command-line tool for download at http://omics.pnl.gov/software/LC-IMS-MS_Feature_Finder.php. The Microsoft.NET Framework 4.0 is required to run the software. All other dependencies are included with the software package. Usage of this software is limited to non-profit research to use (see README). CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Kevin L. Crowell, Gordon W. Slysz, Erin S. Baker, Brian L. LaMarche, Matthew E. Monroe, Yehia M. Ibrahim, Samuel H. Payne, Gordon A. Anderson, Richard D. Smith |
Bioinform. | 5 |
| 2013 | MultiAlign: a multiple LC-MS analysis tool for targeted omics analysisabstractBACKGROUND: MultiAlign is a free software tool that aligns multiple liquid chromatography-mass spectrometry datasets to one another by clustering mass and chromatographic elution features across datasets. Applicable to both label-free proteomics and metabolomics comparative analyses, the software can be operated in several modes. For example, clustered features can be matched to a reference database to identify analytes, used to generate abundance profiles, linked to tandem mass spectra based on parent precursor masses, and culled for targeted liquid chromatography-tandem mass spectrometric analysis. MultiAlign is also capable of tandem mass spectral clustering to describe proteome structure and find similarity in subsequent sample runs. RESULTS: MultiAlign was applied to two large proteomics datasets obtained from liquid chromatography-mass spectrometry analyses of environmental samples. Peptides in the datasets for a microbial community that had a known metagenome were identified by matching mass and elution time features to those in an established reference peptide database. Results compared favorably with those obtained using existing tools such as VIPER, but with the added benefit of being able to trace clusters of peptides across conditions to existing tandem mass spectra. MultiAlign was further applied to detect clusters across experimental samples derived from a reactor biomass community for which no metagenome was available. Several clusters were culled for further analysis to explore changes in the community structure. Lastly, MultiAlign was applied to liquid chromatography-mass spectrometry-based datasets obtained from a previously published study of wild type and mitochondrial fatty acid oxidation enzyme knockdown mutants of human hepatocarcinoma to demonstrate its utility for analyzing metabolomics datasets. CONCLUSION: MultiAlign is an efficient software package for finding similar analytes across multiple liquid chromatography-mass spectrometry feature maps, as demonstrated here for both proteomics and metabolomics experiments. The software is particularly useful for proteomic studies where little or no genomic context is known, such as with environmental proteomics. Brian L. LaMarche, Kevin L. Crowell, Navdeep Jaitly, Vladislav A. Petyuk, Anuj R. Shah, Ashoka D. Polpitiya, John D. Sandoval, Gary R. Kiebel, Matthew E. Monroe, Stephen J. Callister, Thomas O. Metz, Gordon A. Anderson, Richard D. Smith |
BMC Bioinform. | 9 |
| 2010 | Machine learning based prediction for peptide drift times in ion mobility spectrometryabstractMOTIVATION: Ion mobility spectrometry (IMS) has gained significant traction over the past few years for rapid, high-resolution separations of analytes based upon gas-phase ion structure, with significant potential impacts in the field of proteomic analysis. IMS coupled with mass spectrometry (MS) affords multiple improvements over traditional proteomics techniques, such as in the elucidation of secondary structure information, identification of post-translational modifications, as well as higher identification rates with reduced experiment times. The high throughput nature of this technique benefits from accurate calculation of cross sections, mobilities and associated drift times of peptides, thereby enhancing downstream data analysis. Here, we present a model that uses physicochemical properties of peptides to accurately predict a peptide's drift time directly from its amino acid sequence. This model is used in conjunction with two mathematical techniques, a partial least squares regression and a support vector regression setting. RESULTS: When tested on an experimentally created high confidence database of 8675 peptide sequences with measured drift times, both techniques statistically significantly outperform the intrinsic size parameters-based calculations, the currently held practice in the field, on all charge states (+2, +3 and +4). AVAILABILITY: The software executable, imPredict, is available for download from http:/omics.pnl.gov/software/imPredict.php CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Anuj R. Shah, Khushbu Agarwal, Erin S. Baker, Mudita Singhal, Anoop M. Mayampurath, Yehia M. Ibrahim, Lars J. Kangas, Matthew E. Monroe, Mikhail E. Belov, Gordon A. Anderson, Richard D. Smith |
Bioinform. | 8 |
| 2009 | An Architecture for Real Time Data Acquisition and Online Signal Processing for High Throughput Tandem Mass SpectrometryabstractIndependent, greedy collection of data events using simple heuristics results in massive over-sampling of the prominent data features in large-scale studies over what should be achievable through ¿intelligent", online acquisition of such data. As a result, data generated are more aptly described as a collection of a large number of small experiments rather than a true large-scale experiment. Nevertheless, achieving ¿intelligent¿, online control requires tight interplay between state-of-the-art, data-intensive computing infrastructure developments and analytical algorithms. In this paper, we propose a Software Architecture for Mass spectrometry-based Proteomics coupled with Liquid chromatography Experiments (SAMPLE) to develop an ¿intelligent¿ online control and analysis system to significantly enhance the information content from each sensor (in this case, a mass spectrometer). Using online analysis of data events as they are collected and decision theory to optimize the collection of events during an experiment, we aim to maximize the information content generated during an experiment by the use of pre-existing knowledge to optimize the dynamic collection of events. Anuj R. Shah, Navdeep Jaitly, Nino Zuljevic, Matthew E. Monroe, Andrei Liyu, Ashoka D. Polpitiya, Joshua N. Adkins, Mikhail E. Belov, Gordon A. Anderson, Richard D. Smith, Ian Gorton |
eScience | 4 |
| 2008 | DeconMSn: a software tool for accurate parent ion monoisotopic mass determination for tandem mass spectraabstractUNLABELLED: DeconMSn accurately determines the monoisotopic mass and charge state of parent ions from high-resolution tandem mass spectrometry data, offering significant improvement for LTQ_FT and LTQ_Orbitrap instruments over the commercially delivered Thermo Fisher Scientific's extract_msn tool. Optimal parent ion mass tolerance values can be determined using accurate mass information, thus improving peptide identifications for high-mass measurement accuracy experiments. For low-resolution data from LCQ and LTQ instruments, DeconMSn incorporates a support-vector-machine-based charge detection algorithm that identifies the most likely charge of a parent species through peak characteristics of its fragmentation pattern. AVAILABILITY: http://ncrr.pnl.gov/software/ or http://www.proteomicsresource.org/. Anoop M. Mayampurath, Navdeep Jaitly, Samuel O. Purvine, Matthew E. Monroe, Kenneth J. Auberry, Joshua N. Adkins, Richard D. Smith |
Bioinform. | 4 |
| 2007 | VIPER: an advanced software package to support high-throughput LC-MS peptide identificationabstractAbstract Summary: The accurate mass and time (AMT) tag approach is used for analysis of large scale experiments by combining information generated over multiple datasets and instrument types. The VIPER software package is one of the key components of the data processing pipeline and implements automated algorithms to discover LC-MS features, align and match these LC-MS features to a database of peptides previously identified in LC-MS/MS analyses, and identify and quantify pairs of isotopically labeled peptides. Availability: VIPER may be downloaded free of charge at http://ncrr.pnl.gov/software/ Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online. Matthew E. Monroe, Nikola Tolic, Navdeep Jaitly, Jason L. Shaw, Joshua N. Adkins, Richard D. Smith |
Bioinform. | 1 |