Results 51 to 60 of about 24,084 (265)
Tensor Factorization via Matrix Factorization
CoRR, 2015 Tensor factorization arises in many machine learning applications, such knowledge base modeling and parameter estimation in latent variable models. However, numerical methods for tensor factorization have not reached the level of maturity of matrix factorization methods.
Volodymyr Kuleshov +2 more
openaire +3 more sources
Organoids in pediatric cancer research
FEBS Letters, EarlyView.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
Reciprocal control of viral infection and phosphoinositide dynamics
FEBS Letters, EarlyView.Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley +1 more source
Factorization of Matrix Polynomials with Symmetries [PDF]
SIAM Journal on Matrix Analysis and Applications, 1994 This paper presents a detailed study of the factorizations of matrix polynomials with symmetries. It begins with defining the key properties of matrix polynomials to be discussed: selfadjoint, symmetric, general rank, generally invertible, etc. Then representations of factorizations of various matrix polynomials are presented in detail.
André C. M. Ran, Leiba Rodman
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Network Embedding Using Deep Robust Nonnegative Matrix Factorization
IEEE Access, 2020 As an effective technique to learn low-dimensional node features in complicated network environment, network embedding has become a promising research direction in the field of network analysis.
Chaobo He +5 more
doaj +1 more source
FEBS Letters, EarlyView.Fluorescent probes allow dynamic visualization of phosphoinositides in living cells (left), whereas mass spectrometry provides high‐sensitivity, isomer‐resolved quantitation (right). Their synergistic use captures complementary aspects of lipid signaling. This review illustrates how these approaches reveal the spatiotemporal regulation and quantitative
Hiroaki Kajiho +3 more
wiley +1 more source
FEBS Letters, EarlyView.Embryo‐like structures (stembryos) are an innovative tool, but they are hindered by experimental variability and limited developmental potential. DNA methylation is crucial for mammalian development, but its status in stembryo models is poorly characterized.
Sara Canil +4 more
wiley +1 more source
Quantized nonnegative matrix factorization [PDF]
2014 19th International Conference on Digital Signal Processing, 2014 Even though Nonnegative Matrix Factorization (NMF) in its original form performs rank reduction and signal compaction implicitly, it does not explicitly consider storage or transmission constraints. We propose a Frobenius-norm Quantized Nonnegative Matrix Factorization algorithm that is 1) almost as precise as traditional NMF for decomposition ranks of
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FEBS Letters, EarlyView.Septin 9 polybasic domains couple phosphoinositide‐rich membrane binding to centrosome positioning, Golgi organization, and microtubule acetylation to control epithelial polarity. Their loss disrupts this axis, causing centrosome mispositioning, Golgi fragmentation, reduced microtubule acetylation, and polarity inversion via upregulation of the ...
Ting ting Cai +4 more
wiley +1 more source
FEBS Letters, EarlyView.This study reveals that the small GTPase Rab14 is necessary for human papillomavirus (HPV) infection and plays an essential role in the transport of virions to the trans‐Golgi network (TGN). HPV in the early endosome (EE), which harbors GTP‐bound Rab14, is transported to the TGN through the switch of Rab14 from its GTP‐bound to GDP‐bound form.
Yoshiyuki Ishii, Iwao Kukimoto
wiley +1 more source