Spectral clustering in eye‐movement researches
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Chemometrics"
DOI: 10.1002/cem.3003
Abstract: Eye tracking is a widely used technology to capture the eye movements of participants completing different tasks. Several eye‐tracking parameters are measured, which later can be used to characterize the gazing pattern of the individuals.… read more here.
Keywords: spectral clustering; clustering eye; eye movement; movement researches ... See more keywords
Motif-based spectral clustering of weighted directed networks
Sign Up to like & getrecommendations! Published in 2020 at "Applied Network Science"
DOI: 10.1007/s41109-020-00293-z
Abstract: Clustering is an essential technique for network analysis, with applications in a diverse range of fields. Although spectral clustering is a popular and effective method, it fails to consider higher-order structure and can perform poorly… read more here.
Keywords: spectral clustering; based spectral; directed networks; clustering weighted ... See more keywords
Distance metrics optimized for clustering temporal dietary patterning among U.S. adults
Sign Up to like & getrecommendations! Published in 2020 at "Appetite"
DOI: 10.1016/j.appet.2019.104451
Abstract: OBJECTIVE Few attempts to determine dietary patterns have incorporated concepts of time, specifically time and proportion of energy intake consumed throughout a day. A type of modified dynamic time warping (MDTW) was previously developed using… read more here.
Keywords: spectral clustering; distance metrics; distance; time ... See more keywords
Bi-cross validation of spectral clustering hyperparameters
Sign Up to like & getrecommendations! Published in 2020 at "Powder Diffraction"
DOI: 10.1017/s0885715620000214
Abstract: One challenge impeding the analysis of terabyte scale X-ray scattering data from the Linac Coherent Light Source (LCLS) is determining the number of clusters required for the execution of traditional clustering algorithms. Here, we demonstrate… read more here.
Keywords: spectral clustering; number; clustering hyperparameters; validation spectral ... See more keywords
HyperSpec: Ultrafast Mass Spectra Clustering in Hyperdimensional Space.
Sign Up to like & getrecommendations! Published in 2023 at "Journal of proteome research"
DOI: 10.1021/acs.jproteome.2c00612
Abstract: As current shotgun proteomics experiments can produce gigabytes of mass spectrometry data per hour, processing these massive data volumes has become progressively more challenging. Spectral clustering is an effective approach to speed up downstream data… read more here.
Keywords: hyperspec ultrafast; hyperspec; spectral clustering; spectra ... See more keywords
Spectral Clustering Improves Label-Free Quantification of Low-Abundant Proteins
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Proteome Research"
DOI: 10.1021/acs.jproteome.8b00377
Abstract: Label-free quantification has become a common-practice in many mass spectrometry-based proteomics experiments. In recent years, we and others have shown that spectral clustering can considerably improve the analysis of (primarily large-scale) proteomics data sets. Here… read more here.
Keywords: data sets; spectral clustering; low abundant; free quantification ... See more keywords
A comparison of spectral clustering and the walktrap algorithm for community detection in network psychometrics.
Sign Up to like & getrecommendations! Published in 2022 at "Psychological methods"
DOI: 10.1037/met0000509
Abstract: Spectral clustering is a well-known method for clustering the vertices of an undirected network. Although its use in network psychometrics has been limited, spectral clustering has a close relationship to the commonly used walktrap algorithm.… read more here.
Keywords: network psychometrics; walktrap algorithm; spectral clustering;
Spectral clustering of single cells using Siamese nerual network combined with improved affinity matrix.
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac113
Abstract: Limitations of bulk sequencing techniques on cell heterogeneity and diversity analysis have been pushed with the development of single-cell RNA-sequencing (scRNA-seq). To detect clusters of cells is a key step in the analysis of scRNA-seq.… read more here.
Keywords: spectral clustering; scrna seq; cell; single cell ... See more keywords
Spectrum: fast density-aware spectral clustering for single and multi-omic data
Sign Up to like & getrecommendations! Published in 2019 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btz704
Abstract: Abstract Motivation Clustering patient omic data is integral to developing precision medicine because it allows the identification of disease subtypes. A current major challenge is the integration multi-omic data to identify a shared structure and… read more here.
Keywords: spectral clustering; omic data; spectrum; multi omic ... See more keywords
Robust Spectral Clustering via Matrix Aggregation
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2871030
Abstract: Spectral clustering has become one of the most popular clustering algorithms in recent years. In real-world clustering problems, the data points for clustering may have considerable noise. To the best of our knowledge, no single… read more here.
Keywords: robust spectral; spectral clustering; matrix aggregation; clustering methods ... See more keywords
The Fast Spectral Clustering Based on Spatial Information for Large Scale Hyperspectral Image
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2942923
Abstract: Spectral clustering is one of the most popular clustering approaches and has been applied in Hyperspectral Image (HSI) clustering well. However, most of these methods are not suitable for large scale HSI. In this paper,… read more here.
Keywords: spectral clustering; hyperspectral image; large scale; spatial information ... See more keywords