ArticleJournal of proteome research2018
Fast Open Modification Spectral Library Searching through Approximate Nearest Neighbor Indexing.
Article in Journal of proteome research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 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
33 citing papers in PubMed.
- Artificial Intelligence and Machine Learning in Mass Spectrometry-Based Proteomics and Metabolomics.Methods in molecular biology (Clifton, N.J.) · 2027Article
- Foundation model enables interpretable open and error-tolerant searching for mass spectrometry-based proteomics.Bioinformatics (Oxford, England) · 2026Article
- A Framework for Database Search with AI Models in Mass Spectrometry-Based Proteomics.Journal of proteome research · 2026Review
- End-to-end deep attention-based multitask pipeline for predicting uncertainty-quantified peptide properties from mass spectrometry data.Scientific reports · 2026Article
- A New Detailed Mass Offset Search in MSFragger for Improved Interpretation of Complex PTMs.Journal of proteome research · 2026Article
- A large language model for deriving spectral embeddings for accurate compound identification in mass spectrometry.Communications chemistry · 2025Article
- Comparative analysis of continuous similarity measures for compound identification in mass spectrometry-based metabolomics.Chemometrics and intelligent laboratory systems : an international journal sponsored by the Chemometrics Society · 2025Article
- Comprehensive Proteomics and Machine Learning Analysis to Distinguish Follicular Adenoma and Follicular Thyroid Carcinoma from Indeterminate Thyroid Nodules.Endocrinology and metabolism (Seoul, Korea) · 2025Article
- Proteomics Can Rise to the Challenge of Pseudogenes' Coding Nature.Journal of proteome research · 2024Review
- The Proteomics Standards Initiative Standardized Formats for Spectral Libraries and Fragment Ion Peak Annotations: mzSpecLib and mzPAF.Analytical chemistry · 2024Article
- Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics.Nature communications · 2023Article
- Fast alignment of mass spectra in large proteomics datasets, capturing dissimilarities arising from multiple complex modifications of peptides.BMC bioinformatics · 2023Article
- Spectroscape enables real-time query and visualization of a spectral archive in proteomics.Nature communications · 2023Article
- Accelerating open modification spectral library searching on tensor core in high-dimensional space.Bioinformatics (Oxford, England) · 2023Article
- MS Ana: Improving Sensitivity in Peptide Identification with Spectral Library Search.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
- DeepLC can predict retention times for peptides that carry as-yet unseen modifications.Nature methods · 2021Article
- ppx: Programmatic Access to Proteomics Data Repositories.Journal of proteome research · 2021Article
- MS Amanda 2.0: Advancements in the standalone implementation.Rapid communications in mass spectrometry : RCM · 2021Article
- Personalized Proteome: Comparing Proteogenomics and Open Variant Search Approaches for Single Amino Acid Variant Detection.Journal of proteome research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Open modification searching (OMS) is a powerful search strategy that identifies peptides carrying any type of modification by allowing a modified spectrum to match against its unmodified variant by using a very wide precursor mass window. A drawback of this strategy, however, is that it leads to a large increase in search time. Although performing an open search can be done using existing spectral library search engines by simply setting a wide precursor mass window, none of these tools have been optimized for OMS, leading to excessive runtimes and suboptimal identification results. We present 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. This approach is combined with a cascade search strategy to maximize the number of identified unmodified and modified spectra while strictly controlling the false discovery rate as well as a shifted dot product score to sensitively match modified spectra to their unmodified counterparts. ANN-SoLo achieves state-of-the-art performance in terms of speed and the number of identifications. On a previously published human cell line data set, ANN-SoLo confidently identifies more spectra than SpectraST or MSFragger and achieves a speedup of an order of magnitude compared with SpectraST. 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.