Demo Data from EDBT 2026 / reviewers in the wild / expert
Logan Donaldson
dblp:95/7065
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2012
0000-0001-5034-2699ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2
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 › structural bioinformatics
protein structure determination |
0.1 | 1 | 2012 | Protein Structure by Semidefinite Facial Reduction · RECOMB 2012 |
Bioinformatics and computational biology
protein structure prediction |
0.1 | 1 | 2012 | Protein Structure by Semidefinite Facial Reduction · RECOMB 2012 |
Bioinformatics and computational biology › proteomics › mass spectrometry data analysis
automated peak picking |
0.1 | 1 | 2009 | PICKY: a novel SVD-based NMR spectra peak picking method · Bioinform. 2009 |
Bioinformatics and computational biology
structural biology |
0.1 | 1 | 2009 | PICKY: a novel SVD-based NMR spectra peak picking method · Bioinform. 2009 |
Methods — techniques the papers use, named apart from their topics
semidefinite programming · 0.1facial reduction · 0.1singular value decomposition · 0.1noise-level estimation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Protein Structure by Semidefinite Facial Reduction
Babak Alipanahi, Nathan Krislock, Ali Ghodsi 0001, Henry Wolkowicz, Logan Donaldson, Ming Li 0001 |
RECOMB | 5 |
| 2009 | PICKY: a novel SVD-based NMR spectra peak picking methodabstractMOTIVATION: Picking peaks from experimental NMR spectra is a key unsolved problem for automated NMR protein structure determination. Such a process is a prerequisite for resonance assignment, nuclear overhauser enhancement (NOE) distance restraint assignment, and structure calculation tasks. Manual or semi-automatic peak picking, which is currently the prominent way used in NMR labs, is tedious, time consuming and costly. RESULTS: We introduce new ideas, including noise-level estimation, component forming and sub-division, singular value decomposition (SVD)-based peak picking and peak pruning and refinement. PICKY is developed as an automated peak picking method. Different from the previous research on peak picking, we provide a systematic study of the proposed method. PICKY is tested on 32 real 2D and 3D spectra of eight target proteins, and achieves an average of 88% recall and 74% precision. PICKY is efficient. It takes PICKY on average 15.7 s to process an NMR spectrum. More important than these numbers, PICKY actually works in practice. We feed peak lists generated by PICKY to IPASS for resonance assignment, feed IPASS assignment to SPARTA for fragments generation, and feed SPARTA fragments to FALCON for structure calculation. This results in high-resolution structures of several proteins, for example, TM1112, at 1.25 A. AVAILABILITY: PICKY is available upon request. The peak lists of PICKY can be easily loaded by SPARKY to enable a better interactive strategy for rapid peak picking. Babak Alipanahi, Xin Gao 0001, Emre Karakoç, Logan Donaldson, Ming Li 0001 |
Bioinform. | 4 |