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Jens P. Linge

dblp:40/4553 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2025
0000-0001-5541-7610ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021Human-computer interaction and ubiquitous 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 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › structural biology
NMR structure calculation
0.012003
ARIA: automated NOE assignment and NMR structure calculation · Bioinform. 2003
Bioinformatics and computational biology
structural biology
0.012003
ARIA: automated NOE assignment and NMR structure calculation · Bioinform. 2003
Bioinformatics and computational biology › structural bioinformatics
protein structure determination
0.012003
ARIA: automated NOE assignment and NMR structure calculation · Bioinform. 2003
Bioinformatics and computational biology › genomics
structural genomics
0.012003
ARIA: automated NOE assignment and NMR structure calculation · Bioinform. 2003

Methods — techniques the papers use, named apart from their topics

relaxation matrix approach · 0.0ambiguous restraints iterative assignment · 0.0
YearPublicationVenuePosition
2025 UKElectionNarratives: A Dataset of Misleading Narratives Surrounding Recent UK General Elections
abstract
Misleading narratives play a crucial role in shaping public opinion during elections, as they can influence how voters perceive candidates and political parties. This entails the need to detect these narratives accurately. To address this, we introduce the first taxonomy of common misleading narratives that circulated during recent elections in Europe. Based on this taxonomy, we construct and analyse UKElectionNarratives: the first dataset of human-annotated misleading narratives which circulated during the UK General Elections in 2019 and 2024. We also benchmark Pre-trained and Large Language Models (focusing on GPT-4o), studying their effectiveness in detecting election-related misleading narratives. Finally, we discuss potential use cases and make recommendations for future research directions using the proposed codebook and dataset.
Fatima Haouari, Carolina Scarton, Nicolò Faggiani, Nikolaos Nikolaidis 0004, Bonka Kotseva, Ibrahim Abu Farha, Jens P. Linge, Kalina Bontcheva
ICWSM7
2003 ARIA: automated NOE assignment and NMR structure calculation
abstract
MOTIVATION: In the light of several ongoing structural genomics projects, faster and more reliable methods for structure calculation from NMR data are in great demand. The major bottleneck in the determination of solution NMR structures is the assignment of NOE peaks (nuclear Overhauser effect). Due to the high complexity of the assignment problem, most NOEs cannot be directly converted into unambiguous inter-proton distance restraints. RESULTS: We present version 1.2 of our program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of NOE data and NMR structure calculation. We summarize recent progress in correcting for spin diffusion with a relaxation matrix approach, representing non-bonded interactions in the force field and refining final structures in explicit solvent. We also discuss book-keeping, data exchange with spectra assignment programs and deposition of the analysed experimental data to the databases. AVAILABILITY: ARIA 1.2 is available from: http://www.pasteur.fr/recherche/unites/Binfs/aria/. SUPPLEMENTARY INFORMATION: XML DTDs (for chemical shifts and NOE crosspeaks), Python scripts for the conversion of various NMR data formats and the results of example calculations using data from the S. cerevisiae HRDC domain are available from: http://www.pasteur.fr/recherche/unites/Binfs/aria/
Jens P. Linge, Michael Habeck, Wolfgang Rieping, Michael Nilges
Bioinform.1