Demo Data from SIGIR 2026 / reviewers in the wild / expert
Jimmy K. Eng
dblp:75/4918
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2018
0000-0001-6352-6737ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 4
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
4 papers |
Bioinformatics and computational biology · 100% |
Topics — the 12 heaviest of 12, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › proteomics
metaproteomics |
0.3 | 1 | 2018 | Sipros Ensemble improves database searching and filtering for complex metaproteomics · Bioinform. 2018 |
Bioinformatics and computational biology › proteomics
peptide identification |
0.3 | 1 | 2018 | Sipros Ensemble improves database searching and filtering for complex metaproteomics · Bioinform. 2018 |
Bioinformatics and computational biology › proteomics
protein identification |
0.3 | 1 | 2018 | Sipros Ensemble improves database searching and filtering for complex metaproteomics · Bioinform. 2018 |
Bioinformatics and computational biology › proteomics
cross-linking mass spectrometry |
0.2 | 1 | 2016 | XLinkDB 2.0: integrated, large-scale structural analysis of protein crosslinking data · Bioinform. 2016 |
Bioinformatics and computational biology › protein analysis
protein-protein interaction |
0.2 | 1 | 2016 | XLinkDB 2.0: integrated, large-scale structural analysis of protein crosslinking data · Bioinform. 2016 |
Bioinformatics and computational biology
proteomics |
0.1 | 2 | 2006 | General framework for developing and evaluating database scoring algorithms using the TANDEM search engine · Bioinform. 2006 A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS · Bioinform. 2006 |
Bioinformatics and computational biology › structural bioinformatics
protein structure |
0.1 | 1 | 2016 | XLinkDB 2.0: integrated, large-scale structural analysis of protein crosslinking data · Bioinform. 2016 |
Bioinformatics and computational biology › metabolomics
LC-MS data analysis |
0.1 | 1 | 2006 | A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS · Bioinform. 2006 |
Bioinformatics and computational biology › proteomics
mass spectrometry data analysis |
0.1 | 1 | 2006 | General framework for developing and evaluating database scoring algorithms using the TANDEM search engine · Bioinform. 2006 |
Bioinformatics and computational biology › proteomics › peptide identification
peptide-spectrum match scoring |
0.1 | 1 | 2006 | General framework for developing and evaluating database scoring algorithms using the TANDEM search engine · Bioinform. 2006 |
Bioinformatics and computational biology › proteomics › quantitative proteomics
label-free quantification |
0.0 | 1 | 2006 | A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS · Bioinform. 2006 |
Bioinformatics and computational biology › proteomics › quantitative proteomics
peptide quantification |
0.0 | 1 | 2006 | A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS · Bioinform. 2006 |
Methods — techniques the papers use, named apart from their topics
logistic regression · 0.3ensemble scoring functions · 0.3database searching · 0.3network analysis · 0.2pluggable scoring architecture · 0.1peptide feature detection · 0.1normalization · 0.1alignment · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Sipros Ensemble improves database searching and filtering for complex metaproteomicsabstractMotivation: Complex microbial communities can be characterized by metagenomics and metaproteomics. However, metagenome assemblies often generate enormous, and yet incomplete, protein databases, which undermines the identification of peptides and proteins in metaproteomics. This challenge calls for increased discrimination of true identifications from false identifications by database searching and filtering algorithms in metaproteomics. Results: Sipros Ensemble was developed here for metaproteomics using an ensemble approach. Three diverse scoring functions from MyriMatch, Comet and the original Sipros were incorporated within a single database searching engine. Supervised classification with logistic regression was used to filter database searching results. Benchmarking with soil and marine microbial communities demonstrated a higher number of peptide and protein identifications by Sipros Ensemble than MyriMatch/Percolator, Comet/Percolator, MS-GF+/Percolator, Comet & MyriMatch/iProphet and Comet & MyriMatch & MS-GF+/iProphet. Sipros Ensemble was computationally efficient and scalable on supercomputers. Availability and implementation: Freely available under the GNU GPL license at http://sipros.omicsbio.org. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online. Xuan Guo 0004, Qiuming Yao, Ryan S. Mueller, Jimmy K. Eng, David L. Tabb, IV William Judson Hervey, Chongle Pan |
Bioinform. | 5 |
| 2016 | XLinkDB 2.0: integrated, large-scale structural analysis of protein crosslinking dataabstractMOTIVATION: Large-scale chemical cross-linking with mass spectrometry (XL-MS) analyses are quickly becoming a powerful means for high-throughput determination of protein structural information and protein-protein interactions. Recent studies have garnered thousands of cross-linked interactions, yet the field lacks an effective tool to compile experimental data or access the network and structural knowledge for these large scale analyses. We present XLinkDB 2.0 which integrates tools for network analysis, Protein Databank queries, modeling of predicted protein structures and modeling of docked protein structures. The novel, integrated approach of XLinkDB 2.0 enables the holistic analysis of XL-MS protein interaction data without limitation to the cross-linker or analytical system used for the analysis. AVAILABILITY AND IMPLEMENTATION: XLinkDB 2.0 can be found here, including documentation and help: http://xlinkdb.gs.washington.edu/ CONTACT: : [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Devin K. Schweppe, Chunxiang Zheng, Juan D. Chavez, Arti T. Navare, Jimmy K. Eng, James E. Bruce |
Bioinform. | 6 |
| 2006 | A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MSabstractMOTIVATION: Comparing two or more complex protein mixtures using liquid chromatography mass spectrometry (LC-MS) requires multiple analysis steps to locate and quantitate natural peptides within a single experiment and to align and normalize findings across multiple experiments. RESULTS: We describe msInspect, an open-source application comprising algorithms and visualization tools for the analysis of multiple LC-MS experimental measurements. The platform integrates novel algorithms for detecting signatures of natural peptides within a single LC-MS measurement and combines multiple experimental measurements into a peptide array, which may then be mined using analysis tools traditionally applied to genomic array analysis. The platform supports quantitation by both label-free and isotopic labeling approaches. The software implementation has been designed so that many key components may be easily replaced, making it useful as a workbench for integrating other novel algorithms developed by a growing research community. AVAILABILITY: The msInspect software is distributed freely under an Apache 2.0 license. The software as well as a Zip file with all peptide feature files and scripts needed to generate the tables and figures in this article are available at http://proteomics.fhcrc.org/. Matthew Bellew, Marc Coram, Matthew Fitzgibbon, Mark Igra, Timothy W. Randolph 0002, Pei Wang 0014, Damon May, Jimmy K. Eng, Ruihua Fang, ChenWei Lin, Jinzhi Chen, David Goodlett, Jeffrey Whiteaker, Amanda G. Paulovich, Martin McIntosh |
Bioinform. | 8 |
| 2006 | General framework for developing and evaluating database scoring algorithms using the TANDEM search engineabstractMOTIVATION: Tandem mass spectrometry (MS/MS) identifies protein sequences using database search engines, at the core of which is a score that measures the similarity between peptide MS/MS spectra and a protein sequence database. The TANDEM application was developed as a freely available database search engine for the proteomics research community. To extend TANDEM as a platform for further research on developing improved database scoring methods, we modified the software to allow users to redefine the scoring function and replace the native TANDEM scoring function while leaving the remaining core application intact. Redefinition is performed at run time so multiple scoring functions are available to be selected and applied from a single search engine binary. We introduce the implementation of the pluggable scoring algorithm and also provide implementations of two TANDEM compatible scoring functions, one previously described scoring function compatible with PeptideProphet and one very simple scoring function that quantitative researchers may use to begin their development. This extension builds on the open-source TANDEM project and will facilitate research into and dissemination of novel algorithms for matching MS/MS spectra to peptide sequences. The pluggable scoring schema is also compatible with related search applications P3 and Hunter, which are part of the X! suite of database matching algorithms. The pluggable scores and the X! suite of applications are all written in C++. AVAILABILITY: Source code for the scoring functions is available from http://proteomics.fhcrc.org Brendan MacLean, Jimmy K. Eng, Ronald C. Beavis, Martin McIntosh |
Bioinform. | 2 |