Demo Data from EDBT 2026 / reviewers in the wild / expert
Xuemei Han
dblp:97/7430
· DBLP profile ↗
5ranked-venue papers
2as first author
2since 2021 · last 2024
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 first-author · 1 since 2021
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
3 papers |
Bioinformatics and computational biology · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
proteomics |
0.4 | 3 | 2014 | Census 2: isobaric labeling data analysis · Bioinform. 2014 XDIA: improving on the label-free data-independent analysis · Bioinform. 2010 YADA: a tool for taking the most out of high-resolution spectra · Bioinform. 2009 |
Bioinformatics and computational biology › proteomics
mass spectrometry data analysis |
0.3 | 3 | 2014 | Census 2: isobaric labeling data analysis · Bioinform. 2014 YADA: a tool for taking the most out of high-resolution spectra · Bioinform. 2009 XDIA: improving on the label-free data-independent analysis · Bioinform. 2010 |
Bioinformatics and computational biology › proteomics › shotgun proteomics
data-independent acquisition |
0.1 | 1 | 2010 | XDIA: improving on the label-free data-independent analysis · Bioinform. 2010 |
Bioinformatics and computational biology › proteomics
shotgun proteomics |
0.1 | 1 | 2010 | XDIA: improving on the label-free data-independent analysis · Bioinform. 2010 |
Methods — techniques the papers use, named apart from their topics
weighted normalization · 0.2reporter ion impurity correction · 0.2intensity threshold filtering · 0.2electron transfer dissociation · 0.1collision-activated dissociation · 0.1ProLuCID · 0.1DTASelect · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | View-specific anchors coupled tensorial bipartite graph learning for incomplete multi-view clustering
Xuemei Han, Zhenwen Ren, Xueyuan Wang, Xiaojian You |
Inf. Sci. | 1 |
| 2022 | Incomplete multi-view subspace clustering based on missing-sample recovering and structural information learning
Xuemei Han, Zhenwen Ren, Chuanyun Zou, Xiaojian You |
Expert Syst. Appl. | 1 |
| 2014 | Census 2: isobaric labeling data analysisabstractMOTIVATION: We introduce Census 2, an update of a mass spectrometry data analysis tool for peptide/protein quantification. New features for analysis of isobaric labeling, such as Tandem Mass Tag (TMT) or Isobaric Tags for Relative and Absolute Quantification (iTRAQ), have been added in this version, including a reporter ion impurity correction, a reporter ion intensity threshold filter and an option for weighted normalization to correct mixing errors. TMT/iTRAQ analysis can be performed on experiments using HCD (High Energy Collision Dissociation) only, CID (Collision Induced Dissociation)/HCD (High Energy Collision Dissociation) dual scans or HCD triple-stage mass spectrometry data. To improve measurement accuracy, we implemented weighted normalization, multiple tandem spectral approach, impurity correction and dynamic intensity threshold features. AVAILABILITY AND IMPLEMENTATION: Census 2 supports multiple input file formats including MS1/MS2, DTASelect, mzXML and pepXML. It requires JAVA version 6 or later to run. Free download of Census 2 for academic users is available at http://fields.scripps.edu/census/index.php. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Sung Kyu Robin Park, Aaron Aslanian, Daniel B. McClatchy, Xuemei Han, Harshil Shah, Meha Singh, Navin Rauniyar, James J. Moresco, Antonio F. M. Pinto, Jolene K. Diedrich, Claire Delahunty, John R. Yates III |
Bioinform. | 4 |
| 2010 | XDIA: improving on the label-free data-independent analysisabstractSUMMARY: XDIA is a computational strategy for analyzing multiplexed spectra acquired using electron transfer dissociation and collision-activated dissociation; it significantly increases identified spectra (approximately 250%) and unique peptides (approximately 30%) when compared with the data-dependent ETCaD analysis on middle-down, single-phase shotgun proteomic analysis. Increasing identified spectra and peptides improves quantitation statistics confidence and protein coverage, respectively. AVAILABILITY: The software and data produced in this work are freely available for academic use at http://fields.scripps.edu/XDIA CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Paulo C. Carvalho, Xuemei Han, Daniel Cociorva, Maria da Gloria Carvalho, Valmir C. Barbosa, John R. Yates III |
Bioinform. | 2 |
| 2009 | YADA: a tool for taking the most out of high-resolution spectraabstractAbstract Summary: YADA can deisotope and decharge high-resolution mass spectra from large peptide molecules, link the precursor monoisotopic peak information to the corresponding tandem mass spectrum, and account for different co-fragmenting ion species (multiplexed spectra). We describe how YADA enables a pipeline consisting of ProLuCID and DTASelect for analyzing large-scale middle-down proteomics data. Availability: http://fields.scripps.edu/yada Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online. Paulo C. Carvalho, Xuemei Han, Daniel Cociorva, Valmir C. Barbosa, John R. Yates III |
Bioinform. | 3 |