Demo Data from EDBT 2026 / reviewers in the wild / expert
Sean J. McIlwain
dblp:425/2527
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2024
0000-0002-3820-8400ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 2 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
2 papers |
Bioinformatics and computational biology · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
proteomics |
1.4 | 2 | 2024 | Ranking antibody binding epitopes and proteins across samples from whole proteome tiled linear peptides · Bioinform. 2024 MASH Native: a unified solution for native top-down proteomics data processing · Bioinform. 2023 |
Bioinformatics and computational biology › immunoinformatics
epitope prediction |
0.8 | 1 | 2024 | Ranking antibody binding epitopes and proteins across samples from whole proteome tiled linear peptides · Bioinform. 2024 |
Bioinformatics and computational biology
immunoinformatics |
0.8 | 1 | 2024 | Ranking antibody binding epitopes and proteins across samples from whole proteome tiled linear peptides · Bioinform. 2024 |
Bioinformatics and computational biology › proteomics › mass spectrometry proteomics
top-down proteomics |
0.7 | 1 | 2023 | MASH Native: a unified solution for native top-down proteomics data processing · Bioinform. 2023 |
Methods — techniques the papers use, named apart from their topics
spatial clustering · 0.8meta-analysis · 0.8spectral summing · 0.7deconvolution · 0.7database searching · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Ranking antibody binding epitopes and proteins across samples from whole proteome tiled linear peptidesabstractINTRODUCTION: Ultradense peptide binding arrays that can probe millions of linear peptides comprising the entire proteomes of human or mouse, or hundreds of thousands of microbes, are powerful tools for studying the antibody repertoire in serum samples to understand adaptive immune responses. MOTIVATION: There are few tools for exploring high-dimensional, significant and reproducible antibody targets for ultradense peptide binding arrays at the linear peptide, epitope (grouping of adjacent peptides), and protein level across multiple samples/subjects (i.e. epitope spread or immunogenic regions of proteins) for understanding the heterogeneity of immune responses. RESULTS: We developed Hierarchical antibody binding Epitopes and pROteins from liNear peptides (HERON), an R package, which can identify immunogenic epitopes, using meta-analyses and spatial clustering techniques to explore antibody targets at various resolution and confidence levels, that can be found consistently across a specified number of samples through the entire proteome to study antibody responses for diagnostics or treatment. Our approach estimates significance values at the linear peptide (probe), epitope, and protein level to identify top candidates for validation. We tested the performance of predictions on all three levels using correlation between technical replicates and comparison of epitope calls on two datasets, and results showed HERON's competitiveness in estimating false discovery rates and finding general and sample-level regions of interest for antibody binding. AVAILABILITY AND IMPLEMENTATION: The HERON R package is available at Bioconductor https://bioconductor.org/packages/release/bioc/html/HERON.html. Sean J. McIlwain, Anna Hoefges, Amy K. Erbe, Paul M. Sondel, Irene M. Ong |
Bioinform. | 1 |
| 2023 | MASH Native: a unified solution for native top-down proteomics data processingabstractMOTIVATION: Native top-down proteomics (nTDP) integrates native mass spectrometry (nMS) with top-down proteomics (TDP) to provide comprehensive analysis of protein complexes together with proteoform identification and characterization. Despite significant advances in nMS and TDP software developments, a unified and user-friendly software package for analysis of nTDP data remains lacking. RESULTS: We have developed MASH Native to provide a unified solution for nTDP to process complex datasets with database searching capabilities in a user-friendly interface. MASH Native supports various data formats and incorporates multiple options for deconvolution, database searching, and spectral summing to provide a "one-stop shop" for characterizing both native protein complexes and proteoforms. AVAILABILITY AND IMPLEMENTATION: The MASH Native app, video tutorials, written tutorials, and additional documentation are freely available for download at https://labs.wisc.edu/gelab/MASH_Explorer/MASHSoftware.php. All data files shown in user tutorials are included with the MASH Native software in the download .zip file. Eli J. Larson, Melissa R. Pergande, Michelle E. Moss, Kalina J. Rossler, R. Kent Wenger, Boris Krichel, Harini Josyer, Jake A. Melby, David S. Roberts, Kyndalanne Pike, Zhuoxin Shi, Hsin-Ju Chan, Bridget Knight, Holden T. Rogers, Kyle A. Brown, Irene M. Ong, Michael T. Marty, Sean J. McIlwain, Ying Ge |
Bioinform. | 19 |