Demo Data from VLDB 2026 / reviewers in the wild / expert
Aivett Bilbao
dblp:277/7580
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0003-2985-8249ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 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
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › metabolomics
collision cross section calculation |
0.5 | 1 | 2021 | AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry-mass spectrometry · Bioinform. 2021 |
Bioinformatics and computational biology › proteomics
mass spectrometry data analysis |
0.5 | 1 | 2021 | AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry-mass spectrometry · Bioinform. 2021 |
Methods — techniques the papers use, named apart from their topics
calibration · 0.5automated peak detection · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry-mass spectrometryabstractMOTIVATION: Ion mobility spectrometry (IMS) separations are increasingly used in conjunction with mass spectrometry (MS) for separation and characterization of ionized molecular species. Information obtained from IMS measurements includes the ion's collision cross section (CCS), which reflects its size and structure and constitutes a descriptor for distinguishing similar species in mixtures that cannot be separated using conventional approaches. Incorporating CCS into MS-based workflows can improve the specificity and confidence of molecular identification. At present, there is no automated, open-source pipeline for determining CCS of analyte ions in both targeted and untargeted fashion, and intensive user-assisted processing with vendor software and manual evaluation is often required. RESULTS: We present AutoCCS, an open-source software to rapidly determine CCS values from IMS-MS measurements. We conducted various IMS experiments in different formats to demonstrate the flexibility of AutoCCS for automated CCS calculation: (i) stepped-field methods for drift tube-based IMS (DTIMS), (ii) single-field methods for DTIMS (supporting two calibration methods: a standard and a new enhanced method) and (iii) linear calibration for Bruker timsTOF and non-linear calibration methods for traveling wave based-IMS in Waters Synapt and Structures for Lossless Ion Manipulations. We demonstrated that AutoCCS offers an accurate and reproducible determination of CCS for both standard and unknown analyte ions in various IMS-MS platforms, IMS-field methods, ionization modes and collision gases, without requiring manual processing. AVAILABILITY AND IMPLEMENTATION: https://github.com/PNNL-Comp-Mass-Spec/AutoCCS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Demo datasets are publicly available at MassIVE (Dataset ID: MSV000085979). Joon-Yong Lee, Aivett Bilbao, Christopher R. Conant, Kent J. Bloodsworth, Daniel J. Orton, Mowei Zhou, Jesse William Wilson, Xueyun Zheng, Ian K. Webb, Ailin Li, Kim K. Hixson, John C. Fjeldsted, Yehia M. Ibrahim, Samuel H. Payne, Christer Jansson, Richard D. Smith, Thomas O. Metz |
Bioinform. | 2 |