Implementation of data-dependent isotopologue fragmentation in 13C-based metabolic flux analysis
Sign Up to like & getrecommendations! Published in 2017 at "Analytical and Bioanalytical Chemistry"
DOI: 10.1007/s00216-017-0339-1
Abstract: AbstractA novel analytical approach based on liquid chromatography coupled to quadrupole time of flight mass spectrometry, employing data-dependent triggering for analysis of isotopologue and tandem mass isotopomer fractions of metabolites of the primary carbon metabolism… read more here.
Keywords: mass; 13c based; data dependent; fragmentation ... See more keywords
Optimised data-independent acquisition strategy recaptures the classification of early-stage hepatocellular carcinoma based on data-dependent acquisition.
Sign Up to like & getrecommendations! Published in 2021 at "Journal of proteomics"
DOI: 10.1016/j.jprot.2021.104152
Abstract: Proteomics is increasingly used for exploring disease biomarkers and therapeutic targets. The data-independent acquisition (DIA) method collects all peptide signals in a sample, and provides a convenient way to archive disease-related molecular features for further… read more here.
Keywords: dia; hepatocellular carcinoma; data independent; independent acquisition ... See more keywords
Development of a data dependent acquisition-based approach for the identification of unknown fast-acting toxins and their ester metabolites.
Sign Up to like & getrecommendations! Published in 2021 at "Talanta"
DOI: 10.1016/j.talanta.2020.121842
Abstract: Phycotoxins in the marine food-web represent a serious threat to human health. Consumption of contaminated shellfish and/or finfish poses risk to consumer safety: several cases of toxins-related seafood poisoning have been recorded so far worldwide.… read more here.
Keywords: dependent; development data; dependent acquisition; identification ... See more keywords
Data-Dependent Scoring Parameter Optimization in MS-GF+ Using Spectrum Quality Filter.
Sign Up to like & getrecommendations! Published in 2018 at "Journal of proteome research"
DOI: 10.1021/acs.jproteome.8b00415
Abstract: Most database search tools for proteomics have their own scoring parameter sets depending on experimental conditions such as fragmentation methods, instruments, digestion enzymes, and so on. These scoring parameter sets are usually predefined by tool… read more here.
Keywords: search; scoring parameter; scoring parameters; quality filter ... See more keywords
Optimization of Data-Dependent Acquisition Parameters in Mass Spectrometry for Oligonucleotide Identification.
Sign Up to like & getrecommendations! Published in 2025 at "Journal of the American Society for Mass Spectrometry"
DOI: 10.1021/jasms.5c00250
Abstract: Accurate characterization of RNAs and their chemical modifications is critical for understanding RNA biology and post-transcriptional regulation. Mass spectrometry using data-dependent acquisition (DDA) is a crucial tool for identifying oligonucleotides (OGN) in epitranscriptomics. In this… read more here.
Keywords: data dependent; spectrometry; mass spectrometry; identification ... See more keywords
Similar, but not the same: multiomics comparison of human valve interstitial cells and osteoblast osteogenic differentiation expanded with an estimation of data-dependent and data-independent PASEF proteomics
Sign Up to like & getrecommendations! Published in 2025 at "GigaScience"
DOI: 10.1093/gigascience/giae110
Abstract: Abstract Osteogenic differentiation is crucial in normal bone formation and pathological calcification, such as calcific aortic valve disease (CAVD). Understanding the proteomic and transcriptomic landscapes underlying this differentiation can unveil potential therapeutic targets for CAVD.… read more here.
Keywords: differentiation; data dependent; valve interstitial; interstitial cells ... See more keywords
Identification of Widely Linear Systems Using Data-Dependent Superimposed Training
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3212959
Abstract: In this correspondence, we address the identification of widely linear (WL) systems using data-dependent superimposed training (DDST). The analysis shows that the nonlinear nature of WL systems can be exploited to decouple the finite impulse… read more here.
Keywords: data dependent; identification widely; using data; widely linear ... See more keywords
Igniting Advancements in Iron-Making Process Monitoring: Exploring a Novel and Cutting-Edge Joint Sparse-Constrained Data-Dependent Kernel CVA Method
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2024.3353270
Abstract: The blast furnace iron-making process (BFIP) holds immense significance in the iron and steel industry. However, due to its nonlinear and dynamic properties, establishing an effective process monitoring model has remained a major challenge. This… read more here.
Keywords: method; data dependent; making process; iron making ... See more keywords
Data-Dependent Generalization Bounds for Multi-Class Classification
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2019.2893916
Abstract: In this paper, we study data-dependent generalization error bounds that exhibit a mild dependency on the number of classes, making them suitable for multi-class learning with a large number of label classes. The bounds generally… read more here.
Keywords: tex math; inline formula; class; data dependent ... See more keywords
Cognitive and cultural models in psychological science: A tutorial on modeling free-list data as a dependent variable in Bayesian regression.
Sign Up to like & getrecommendations! Published in 2022 at "Psychological methods"
DOI: 10.31234/osf.io/4n2jm
Abstract: Assessing relationships between culture and cognition is central to psychological science. To this end, free-listing is a useful methodological instrument. To facilitate its wider use, we here present the free-list method along with some of… read more here.
Keywords: data dependent; list; dependent variable; free list ... See more keywords
Denoising in Representation Space via Data-Dependent Regularization for Better Representation
Sign Up to like & getrecommendations! Published in 2023 at "Mathematics"
DOI: 10.3390/math11102327
Abstract: Despite the success of deep learning models, it remains challenging for the over-parameterized model to learn good representation under small-sample-size settings. In this paper, motivated by previous work on out-of-distribution (OoD) generalization, we study the… read more here.
Keywords: data dependent; better representation; feature; oofs noise ... See more keywords