Demo Data from EDBT 2026 / reviewers in the wild / expert
Janine R. Hutchison
dblp:340/5280
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0002-9303-5290ORCID · 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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › proteomics
mass spectrometry data analysis |
0.7 | 1 | 2023 | MS1Connect: a mass spectrometry run similarity measure · Bioinform. 2023 |
Bioinformatics and computational biology
proteomics |
0.7 | 1 | 2023 | MS1Connect: a mass spectrometry run similarity measure · Bioinform. 2023 |
Bioinformatics and computational biology
species identification |
0.2 | 1 | 2023 | MS1Connect: a mass spectrometry run similarity measure · Bioinform. 2023 |
Methods — techniques the papers use, named apart from their topics
MS1 scan comparison · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | MS1Connect: a mass spectrometry run similarity measureabstractMOTIVATION: Interpretation of newly acquired mass spectrometry data can be improved by identifying, from an online repository, previous mass spectrometry runs that resemble the new data. However, this retrieval task requires computing the similarity between an arbitrary pair of mass spectrometry runs. This is particularly challenging for runs acquired using different experimental protocols. RESULTS: We propose a method, MS1Connect, that calculates the similarity between a pair of runs by examining only the intact peptide (MS1) scans, and we show evidence that the MS1Connect score is accurate. Specifically, we show that MS1Connect outperforms several baseline methods on the task of predicting the species from which a given proteomics sample originated. In addition, we show that MS1Connect scores are highly correlated with similarities computed from fragment (MS2) scans, even though these data are not used by MS1Connect. AVAILABILITY AND IMPLEMENTATION: The MS1Connect software is available at https://github.com/bmx8177/MS1Connect. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Andy Lin, Brooke L. Deatherage Kaiser, Janine R. Hutchison, Jeff A. Bilmes, William Stafford Noble |
Bioinform. | 3 |