ArticleJournal of proteome research2019
Extremely Fast and Accurate Open Modification Spectral Library Searching of High-Resolution Mass Spectra Using Feature Hashing and Graphics Processing Units.
Article in Journal of proteome research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed.
- Benchmarking MS/MS Featurization Strategies for Machine Learning-Driven Metabolite Structure Annotation.Journal of the American Society for Mass Spectrometry · 2026Article
- ChemEmbed: a deep learning framework for metabolite identification using enhanced MS/MS data and multidimensional molecular embeddings.Briefings in bioinformatics · 2026Article
- Comprehensive Proteomics and Machine Learning Analysis to Distinguish Follicular Adenoma and Follicular Thyroid Carcinoma from Indeterminate Thyroid Nodules.Endocrinology and metabolism (Seoul, Korea) · 2025Article
- Proteome-wide non-cleavable crosslink identification with MS Annika 3.0 reveals the structure of the C. elegans Box C/D complex.Communications chemistry · 2024Article
- Proteomics Can Rise to the Challenge of Pseudogenes' Coding Nature.Journal of proteome research · 2024Review
- Quality Control in the Mass Spectrometry Proteomics Core: A Practical Primer.Journal of biomolecular techniques : JBT · 2024Article
- Multi-Omics integration can be used to rescue metabolic information for some of the dark region of the Pseudomonas putida proteome.BMC genomics · 2024Article
- Demystifying PTM Identification Using MODplus: Best Practices and Pitfalls.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics.Nature communications · 2023Article
- Spectroscape enables real-time query and visualization of a spectral archive in proteomics.Nature communications · 2023Article
- Flash entropy search to query all mass spectral libraries in real time.Nature methods · 2023Article
- AIomics: Exploring More of the Proteome Using Mass Spectral Libraries Extended by Artificial Intelligence.Journal of proteome research · 2023Article
- Accelerating open modification spectral library searching on tensor core in high-dimensional space.Bioinformatics (Oxford, England) · 2023Article
- HyperSpec: Ultrafast Mass Spectra Clustering in Hyperdimensional Space.Journal of proteome research · 2023Article
- The critical role that spectral libraries play in capturing the metabolomics community knowledge.Metabolomics : Official journal of the Metabolomic Society · 2022Review
- ppx: Programmatic Access to Proteomics Data Repositories.Journal of proteome research · 2021Article
- Mapping the plant proteome: tools for surveying coordinating pathways.Emerging topics in life sciences · 2021Review
- Evaluation of open search methods based on theoretical mass spectra comparison.BMC bioinformatics · 2021Article
- Discovery of Protein Modifications Using Differential Tandem Mass Spectrometry Proteomics.Journal of proteome research · 2021Article
- Emerging mass spectrometry-based proteomics methodologies for novel biomedical applications.Biochemical Society transactions · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Open modification searching (OMS) is a powerful search strategy to identify peptides with any type of modification. OMS works by using a very wide precursor mass window to allow modified spectra to match against their unmodified variants, after which the modification types can be inferred from the corresponding precursor mass differences. A disadvantage of this strategy, however, is the large computational cost, because each query spectrum has to be compared against a multitude of candidate peptides. We have previously introduced the ANN-SoLo tool for fast and accurate open spectral library searching. ANN-SoLo uses approximate nearest neighbor indexing to speed up OMS by selecting only a limited number of the most relevant library spectra to compare to an unknown query spectrum. Here we demonstrate how this candidate selection procedure can be further optimized using graphics processing units. Additionally, we introduce a feature hashing scheme to convert high-resolution spectra to low-dimensional vectors. On the basis of these algorithmic advances, along with low-level code optimizations, the new version of ANN-SoLo is up to an order of magnitude faster than its initial version. This makes it possible to efficiently perform open searches on a large scale to gain a deeper understanding about the protein modification landscape. We demonstrate the computational efficiency and identification performance of ANN-SoLo based on a large data set of the draft human proteome. ANN-SoLo is implemented in Python and C++. It is freely available under the Apache 2.0 license at https://github.com/bittremieux/ANN-SoLo .
Indexed as
Identifiers
What 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.