Results 31 to 40 of about 379,758 (236)
Spectral dimensionality reduction for HMMs [PDF]
Hidden Markov Models (HMMs) can be accurately approximated using co-occurrence frequencies of pairs and triples of observations by using a fast spectral method in contrast to the usual slow methods like EM or Gibbs sampling.
Foster, Dean P. +2 more
core +2 more sources
Dimensionality reduction in translational noninvariant wave guides
A scheme to reduce translational noninvariant quasi-one-dimensional wave guides into singly or multiply connected one-dimensional (1D) lines is proposed.
Aeberhand +23 more
core +1 more source
ABSTRACT Background Kaposiform lymphangiomatosis (KLA) is an aggressive complex lymphatic anomaly. Patients exhibit malformed lymphatic vessels and often develop hemorrhagic effusions and elevated angiopoietin‐2 (Ang‐2) levels. A somatic NRAS p.Q61R (NRASQ61R) mutation has been associated with KLA.
C. Griffin McDaniel +3 more
wiley +1 more source
Background Dimensionality reduction is an indispensable analytic component for many areas of single-cell RNA sequencing (scRNA-seq) data analysis. Proper dimensionality reduction can allow for effective noise removal and facilitate many downstream ...
Shiquan Sun +3 more
doaj +1 more source
Overlap Removal of Dimensionality Reduction Scatterplot Layouts
Dimensionality Reduction (DR) scatterplot layouts have become a ubiquitous visualization tool for analyzing multidimensional data items with presence in different areas.
Eler, Danilo M. +4 more
core
Revealing the structure of land plant photosystem II: the journey from negative‐stain EM to cryo‐EM
Advances in cryo‐EM have revealed the detailed structure of Photosystem II, a key protein complex driving photosynthesis. This review traces the journey from early low‐resolution images to high‐resolution models, highlighting how these discoveries deepen our understanding of light harvesting and energy conversion in plants.
Roman Kouřil
wiley +1 more source
Linguistic Geometries for Unsupervised Dimensionality Reduction [PDF]
Text documents are complex high dimensional objects. To effectively visualize such data it is important to reduce its dimensionality and visualize the low dimensional embedding as a 2-D or 3-D scatter plot.
Balasubramanian, Krishnakumar +2 more
core
Organoids in pediatric cancer research
Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley +1 more source
The newfound relationship between extrachromosomal DNAs and excised signal circles
Extrachromosomal DNAs (ecDNAs) contribute to the progression of many human cancers. In addition, circular DNA by‐products of V(D)J recombination, excised signal circles (ESCs), have roles in cancer progression but have largely been overlooked. In this Review, we explore the roles of ecDNAs and ESCs in cancer development, and highlight why these ...
Dylan Casey, Zeqian Gao, Joan Boyes
wiley +1 more source
Nonlinear dimensionality reduction in climate data [PDF]
Linear methods of dimensionality reduction are useful tools for handling and interpreting high dimensional data. However, the cumulative variance explained by each of the subspaces in which the data space is decomposed may show a slow convergence that ...
A. J. Gámez +3 more
doaj

