ArticleResearch (Washington, D.C.)2023
Dear-DIA
Article in Research (Washington, D.C.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Dear-OMG: An Omics-General Compression Method for Genomics, Proteomics and Metabolomics Data.Interdisciplinary sciences, computational life sciences · 2026Article
- Internet-delivered cognitive behavioral therapy for insomnia: The future of insomnia treatment with large language models.Sleep medicine: X · 2025Review
- A Machine Learning Model for Diagnosing Opportunistic Infections in HIV Patients: Broad Applicability Across Infection Types.Journal of cellular and molecular medicine · 2025Article
- TopDIA: A Software Tool for Top-Down Data-Independent Acquisition Proteomics.Journal of proteome research · 2025Article
- Application of Spatial Omics in the Cardiovascular System.Research (Washington, D.C.) · 2025Review
- Artificial intelligence-based evaluation of prognosis in cirrhosis.Journal of translational medicine · 2024Review
- LMCD-OR: a large-scale, multilevel categorized diagnostic dataset for oral radiography.Journal of translational medicine · 2024Article
- Dear-PSM: A deep learning-based peptide search engine enables full database search for proteomics.Smart medicine · 2024Article
- SeFilter-DIA: Squeeze-and-Excitation Network for Filtering High-Confidence Peptides of Data-Independent Acquisition Proteomics.Interdisciplinary sciences, computational life sciences · 2024Article
- ProPept-MT: A Multi-Task Learning Model for Peptide Feature Prediction.International journal of molecular sciences · 2024Article
- FM-FCN: A Neural Network with Filtering Modules for Accurate Vital Signs Extraction.Research (Washington, D.C.) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Data-independent acquisition (DIA) technology for protein identification from mass spectrometry and related algorithms is developing rapidly. The spectrum-centric analysis of DIA data without the use of spectra library from data-dependent acquisition data represents a promising direction. In this paper, we proposed an untargeted analysis method, Dear-DIA
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.