ArticleJournal of biomolecular NMR2017
Peak picking multidimensional NMR spectra with the contour geometry based algorithm CYPICK.
Article in Journal of biomolecular NMR, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Harmonizing Peak Matching between Multidimensional NMR Spectra.Journal of chemical information and modeling · 2026Article
- MolDeTr: A Chemistry-Informed Deep Learning Model for Next-Generation Automated Analysis of 1H NMR Spectra.Analytical chemistry · 2026Article
- Harmonizing Peak Matching Between Multidimensional NMR Spectra.bioRxiv : the preprint server for biology · 2026Article
- A small antimicrobial peptide derived from a Burkholderia bacterium exhibits a broad-spectrum and high inhibiting activities against crop diseases.Plant biotechnology journal · 2025Article
- UnidecNMR: automatic peak detection for NMR spectra in 1-4 dimensions.Nature communications · 2025Article
- Manual and automatic assignment of two different Aβ40 amyloid fibril polymorphs using MAS solid-state NMR spectroscopy.Biomolecular NMR assignments · 2024Article
- N-terminal domain of polypyrimidine-tract binding protein is a dynamic folding platform for adaptive RNA recognition.Nucleic acids research · 2024Article
- Rapid protein assignments and structures from raw NMR spectra with the deep learning technique ARTINA.Nature communications · 2022Article
- Fundamental and practical aspects of machine learning for the peak picking of biomolecular NMR spectra.Journal of biomolecular NMR · 2022Article
- DEEP picker is a deep neural network for accurate deconvolution of complex two-dimensional NMR spectra.Nature communications · 2021Article
- iPick: Multiprocessing software for integrated NMR signal detection and validation.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2021Article
- Prediction and Activity of a Cationic α-Helix Antimicrobial Peptide ZM-804 from Maize.International journal of molecular sciences · 2021Article
- Prediction and Characterization of Cationic Arginine-Rich Plant Antimicrobial Peptide SM-985 From Teosinte (Frontiers in microbiology · 2020Article
- Increases in Hydrophilicity and Charge on the Polar Face of Alyteserin 1c Helix Change its Selectivity towards Gram-Positive Bacteria.Antibiotics (Basel, Switzerland) · 2019Article
- Automatic structure-based NMR methyl resonance assignment in large proteins.Nature communications · 2019Article
- Non-Uniform and Absolute Minimal Sampling for High-Throughput Multidimensional NMR Applications.Chemistry (Weinheim an der Bergstrasse, Germany) · 2018Review
- Modern Technologies of Solution Nuclear Magnetic Resonance Spectroscopy for Three-dimensional Structure Determination of Proteins Open Avenues for Life Scientists.Computational and structural biotechnology journal · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The automated identification of signals in multidimensional NMR spectra is a challenging task, complicated by signal overlap, noise, and spectral artifacts, for which no universally accepted method is available. Here, we present a new peak picking algorithm, CYPICK, that follows, as far as possible, the manual approach taken by a spectroscopist who analyzes peak patterns in contour plots of the spectrum, but is fully automated. Human visual inspection is replaced by the evaluation of geometric criteria applied to contour lines, such as local extremality, approximate circularity (after appropriate scaling of the spectrum axes), and convexity. The performance of CYPICK was evaluated for a variety of spectra from different proteins by systematic comparison with peak lists obtained by other, manual or automated, peak picking methods, as well as by analyzing the results of automated chemical shift assignment and structure calculation based on input peak lists from CYPICK. The results show that CYPICK yielded peak lists that compare in most cases favorably to those obtained by other automated peak pickers with respect to the criteria of finding a maximal number of real signals, a minimal number of artifact peaks, and maximal correctness of the chemical shift assignments and the three-dimensional structure obtained by fully automated assignment and structure calculation.
Indexed as
Identifiers
28160195What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.