Matches in SemOpenAlex for { <https://semopenalex.org/work/W2802348903> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W2802348903 abstract "Motivation: Post-database searching is a key procedure in peptide dentification with tandem mass spectrometry (MS/MS) strategies for refining peptide-spectrum matches (PSMs) generated by database search engines. Although many statistical and machine learning-based methods have been developed to improve the accuracy of peptide identification, the challenge remains on large-scale datasets and datasets with an extremely large proportion of false positives (hard datasets). A more efficient learning strategy is required for improving the performance of peptide identification on challenging datasets. Results: In this work, we present an online learning method to conquer the challenges remained for exiting peptide identification algorithms. We propose a cost-sensitive learning model by using different loss functions for decoy and target PSMs respectively. A larger penalty for wrongly selecting decoy PSMs than that for target PSMs, and thus the new model can reduce its false discovery rate on hard datasets. Also, we design an online learning algorithm, OLCS-Ranker, to solve the proposed learning model. Rather than taking all training data samples all at once, OLCS-Ranker iteratively feeds in only one training sample into the learning model at each round. As a result, the memory requirement is significantly reduced for large-scale problems. Experimental studies show that OLCS-Ranker outperforms benchmark methods, such as CRanker and Batch-CS-Ranker, in terms of accuracy and stability. Furthermore, OLCS-Ranker is 15--85 times faster than CRanker method on large datasets. Availability and implementation: OLCS-Ranker software is available at no charge for non-commercial use at https://github.com/Isaac-QiXing/CRanker." @default.
- W2802348903 created "2018-05-17" @default.
- W2802348903 creator A5009925355 @default.
- W2802348903 creator A5012331541 @default.
- W2802348903 creator A5020921222 @default.
- W2802348903 creator A5050445079 @default.
- W2802348903 creator A5055555857 @default.
- W2802348903 creator A5061941155 @default.
- W2802348903 date "2018-05-08" @default.
- W2802348903 modified "2023-09-26" @default.
- W2802348903 title "Efficient online learning for large-scale peptide identification" @default.
- W2802348903 cites W1525575010 @default.
- W2802348903 cites W1984450835 @default.
- W2802348903 cites W1994720006 @default.
- W2802348903 cites W1999751815 @default.
- W2802348903 cites W2139212933 @default.
- W2802348903 cites W2172612767 @default.
- W2802348903 cites W3028642772 @default.
- W2802348903 doi "https://doi.org/10.48550/arxiv.1805.03006" @default.
- W2802348903 hasPublicationYear "2018" @default.
- W2802348903 type Work @default.
- W2802348903 sameAs 2802348903 @default.
- W2802348903 citedByCount "0" @default.
- W2802348903 crossrefType "posted-content" @default.
- W2802348903 hasAuthorship W2802348903A5009925355 @default.
- W2802348903 hasAuthorship W2802348903A5012331541 @default.
- W2802348903 hasAuthorship W2802348903A5020921222 @default.
- W2802348903 hasAuthorship W2802348903A5050445079 @default.
- W2802348903 hasAuthorship W2802348903A5055555857 @default.
- W2802348903 hasAuthorship W2802348903A5061941155 @default.
- W2802348903 hasBestOaLocation W28023489031 @default.
- W2802348903 hasConcept C104317684 @default.
- W2802348903 hasConcept C116834253 @default.
- W2802348903 hasConcept C119857082 @default.
- W2802348903 hasConcept C13280743 @default.
- W2802348903 hasConcept C154945302 @default.
- W2802348903 hasConcept C185592680 @default.
- W2802348903 hasConcept C185798385 @default.
- W2802348903 hasConcept C193244246 @default.
- W2802348903 hasConcept C205649164 @default.
- W2802348903 hasConcept C41008148 @default.
- W2802348903 hasConcept C55493867 @default.
- W2802348903 hasConcept C59822182 @default.
- W2802348903 hasConcept C64869954 @default.
- W2802348903 hasConcept C774472 @default.
- W2802348903 hasConcept C86803240 @default.
- W2802348903 hasConceptScore W2802348903C104317684 @default.
- W2802348903 hasConceptScore W2802348903C116834253 @default.
- W2802348903 hasConceptScore W2802348903C119857082 @default.
- W2802348903 hasConceptScore W2802348903C13280743 @default.
- W2802348903 hasConceptScore W2802348903C154945302 @default.
- W2802348903 hasConceptScore W2802348903C185592680 @default.
- W2802348903 hasConceptScore W2802348903C185798385 @default.
- W2802348903 hasConceptScore W2802348903C193244246 @default.
- W2802348903 hasConceptScore W2802348903C205649164 @default.
- W2802348903 hasConceptScore W2802348903C41008148 @default.
- W2802348903 hasConceptScore W2802348903C55493867 @default.
- W2802348903 hasConceptScore W2802348903C59822182 @default.
- W2802348903 hasConceptScore W2802348903C64869954 @default.
- W2802348903 hasConceptScore W2802348903C774472 @default.
- W2802348903 hasConceptScore W2802348903C86803240 @default.
- W2802348903 hasLocation W28023489031 @default.
- W2802348903 hasOpenAccess W2802348903 @default.
- W2802348903 hasPrimaryLocation W28023489031 @default.
- W2802348903 hasRelatedWork W1485630101 @default.
- W2802348903 hasRelatedWork W2020413892 @default.
- W2802348903 hasRelatedWork W2102122784 @default.
- W2802348903 hasRelatedWork W2951109249 @default.
- W2802348903 hasRelatedWork W3117549273 @default.
- W2802348903 hasRelatedWork W3129868498 @default.
- W2802348903 hasRelatedWork W4226417751 @default.
- W2802348903 hasRelatedWork W4283819635 @default.
- W2802348903 hasRelatedWork W4304699798 @default.
- W2802348903 hasRelatedWork W4319453009 @default.
- W2802348903 isParatext "false" @default.
- W2802348903 isRetracted "false" @default.
- W2802348903 magId "2802348903" @default.
- W2802348903 workType "article" @default.