Results 131 to 140 of about 8,380,583 (373)
Explaining three-dimensional dimensionality reduction plots
Information Visualization, 2016 Understanding three-dimensional projections created by dimensionality reduction from high-variate datasets is very challenging. In particular, classical three-dimensional scatterplots used to display such projections do not explicitly show the relations ...
D. Coimbra +4 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.Using mass cytometry, we analyzed serial blood samples from patients with relapsed epithelial ovarian cancer (EOC) treated with oleclumab–durvalumab combination immunotherapy in the NSGO‐OV‐UMB1/ENGOT‐OV30 trial. Our analysis identified potential predictive, monitoring, and response biomarkers detectable through liquid biopsy. These findings facilitate
Luka Tandaric +11 more
wiley +1 more source
Joint Dimensionality Reduction for Separable Embedding Estimation [PDF]
arXiv, 2021 Low-dimensional embeddings for data from disparate sources play critical roles in multi-modal machine learning, multimedia information retrieval, and bioinformatics. In this paper, we propose a supervised dimensionality reduction method that learns linear embeddings jointly for two feature vectors representing data of different modalities or data from ...
arxiv
Nonlinear dimensionality reduction on graphs [PDF]
2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2017 In this era of data deluge, many signal processing and machine learning tasks are faced with high-dimensional datasets, including images, videos, as well as time series generated from social, commercial and brain network interactions. Their efficient processing calls for dimensionality reduction techniques capable of properly compressing the data while
Georgios B. Giannakis +2 more
openaire +2 more sources
Stochastic variation in the FOXM1 transcription program mediates replication stress tolerance
Molecular Oncology, EarlyView.Cellular heterogeneity is a major cause of drug resistance in cancer. Segeren et al. used single‐cell transcriptomics to investigate gene expression events that correlate with sensitivity to the DNA‐damaging drugs gemcitabine and prexasertib. They show that dampened expression of transcription factor FOXM1 and its target genes protected cells against ...
Hendrika A. Segeren +4 more
wiley +1 more source
A Review, Framework and R toolkit for Exploring, Evaluating, and Comparing Visualizations [PDF]
arXiv, 2019 This paper gives a review and synthesis of methods of evaluating dimensionality reduction techniques. Particular attention is paid to rank-order neighborhood evaluation metrics. A framework is created for exploring dimensionality reduction quality through visualization. An associated toolkit is implemented in R. The toolkit includes scatter plots, heat
arxiv
Classification of acute myeloid leukemia based on multi‐omics and prognosis prediction value
Molecular Oncology, EarlyView.The Unsupervised AML Multi‐Omics Classification System (UAMOCS) integrates genomic, methylation, and transcriptomic data to categorize AML patients into three subtypes (UAMOCS1‐3). This classification reveals clinical relevance, highlighting immune and chromosomal characteristics, prognosis, and therapeutic vulnerabilities.
Yang Song +13 more
wiley +1 more source
Editorial: Statistical methods for analyzing multiple environmental quantitative genomic data
Frontiers in Genetics, 2023 Zitong Li, Lucia Gutierrez
doaj +1 more source
Reduction of Dimensionality for Classification
, 2017 We present an algorithm for the reduction of dimensionality useful in statistical classification problems where observations from two multivariate normal distributions are discriminated. It is based on Principal Components Analysis and consists of a simultaneous diagonalization of two covariance matrices.
Cuevas Covarrubias,C, RICCOMAGNO, EVA
openaire +3 more sources
Molecular Oncology, EarlyView.Presurgery 72‐h fasting in GB patients leads to adaptations of plasma lipids and polar metabolites. Fasting reduces lysophosphatidylcholines and increases free fatty acids, shifts triglycerides toward long‐chain TGs and increases branched‐chain amino acids, alpha aminobutyric acid, and uric acid.
Iris Divé +7 more
wiley +1 more source