Results 81 to 90 of about 135,346 (336)
Molecular Oncology, EarlyView.Cancer‐associated fibroblasts (CAFs) promote cancer growth, invasion (metastasis), and drug resistance. Here, we identified functional and diverse circulating CAFs (cCAFs) in patients with metastatic prostate cancer (mPCa). cCAFs were found in higher numbers and were functional and diverse in mPCa patients versus healthy individuals, suggesting their ...
Richell Booijink +6 more
wiley +1 more source
Robust Semi-Supervised Non-Negative Matrix Factorization With Structured Normalization
IEEE Access, 2019 Non-negative matrix factorization (NMF) approximates a non-negative data matrix with the product of two low-rank non-negative matrices by minimizing the cost of such approximation.
Liujing Wang +4 more
doaj +1 more source
New SVD based initialization strategy for Non-negative Matrix Factorization
, 2014 There are two problems need to be dealt with for Non-negative Matrix Factorization (NMF): choose a suitable rank of the factorization and provide a good initialization method for NMF algorithms.
Qiao, Hanli
core +1 more source
Infinite Non-Negative Matrix Factorization
, 2010 Publication in the conference proceedings of EUSIPCO, Aalborg, Denmark ...
Mørup, Morten, Schmidt, Mikkel
openaire +2 more sources
Non-negative Matrix Factorization for Binary Data
Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2015 We propose the Logistic Non-negative Matrix Factorization for decomposition of binary data. Binary data are frequently generated in e.g. text analysis, sensory data, market basket data etc. A common method for analysing non-negative data is the Non-negative Matrix Factorization, though this is in theory not appropriate for binary data, and thus we ...
Larsen, Jacob Søgaard +1 more
openaire +3 more sources
Non-Negative Matrix Factorizations for Multiplex Network Analysis [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 Networks have been a general tool for representing, analyzing, and modeling relational data arising in several domains. One of the most important aspect of network analysis is community detection or network clustering. Until recently, the major focus have been on discovering community structure in single (i.e., monoplex) networks.
Vladimir Gligorijevic +2 more
openaire +5 more sources
Molecular Oncology, EarlyView.We quantified and cultured circulating tumor cells (CTCs) of 62 patients with various cancer types and generated CTC‐derived tumoroid models from two salivary gland cancer patients. Cellular liquid biopsy‐derived information enabled molecular genetic assessment of systemic disease heterogeneity and functional testing for therapy selection in both ...
Nataša Stojanović Gužvić +31 more
wiley +1 more source
Frontiers in Neurorobotics, 2020 Microexpression is usually characterized by short duration and small action range, and the existing general expression recognition algorithms do not work well for microexpression.
Junli Gao +4 more
doaj +1 more source
Molecular Oncology, EarlyView.MET variants in the N‐lobe of the kinase domain, found in hereditary papillary renal cell carcinoma, require ligand stimulation to promote cell transformation, in contrast to other RTK variants. This suggests that HGF expression in the microenvironment is important for tumor growth in such patients. Their sensitivity to MET inhibitors opens the way for
Célia Guérin +14 more
wiley +1 more source
Multifrontal Non-negative Matrix Factorization
, 2020 Non-negative matrix factorization (Nmf) is an important tool in high-performance large scale data analytics with applications ranging from community detection, recommender system, feature detection and linear and non-linear unmixing. While traditional Nmf works well when the data set is relatively dense, however, it may not extract sufficient structure
Ramakrishnan Kannan, Piyush Sao
openaire +3 more sources