Results 81 to 90 of about 55,457 (295)
, 2016 Nonnegative Matrix Factorization(NMF) is a common used technique in machine learning to extract features out of data such as text documents and images thanks to its natural clustering properties. In particular, it is popular in image processing since it can decompose several pictures and recognize common parts if they're located in the same position ...
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PAIR: Reconstructing Single‐Cell Open‐Chromatin Landscapes for Transcription Factor Regulome Mapping
Advanced Science, EarlyView.scATAC‐seq analysis is often constrained by limited sequencing depth, extreme sparsity, and pervasive technical missingness. PAIR is a probabilistic framework that restores scATAC‐seq accessibility profiles by directly modeling the native cell–peak bipartite structure of chromatin accessibility.
Yanchi Su +7 more
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A flexible R package for nonnegative matrix factorization
BMC Bioinformatics, 2010 Background Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face recognition and text mining. Recent applications of NMF in bioinformatics have
Seoighe Cathal, Gaujoux Renaud
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Frontiers in Genetics, 2023 Early diagnosis and treatment of glaucoma are challenging. The discovery of glaucoma biomarkers based on gene expression data could potentially provide new insights for early diagnosis, monitoring, and treatment options of glaucoma.
Xiaoqin Huang +8 more
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Topic supervised non-negative matrix factorization [PDF]
, 2017 Topic models have been extensively used to organize and interpret the contents of large, unstructured corpora of text documents. Although topic models often perform well on traditional training vs.
MacMillan, Kelsey, Wilson, James D.
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Solving the inverse Ising problem by mean-field methods in a clustered phase space with many states [PDF]
, 2016 In this work we explain how to properly use mean-field methods to solve the inverse Ising problem when the phase space is clustered, that is many states are present. The clustering of the phase space can occur for many reasons, e.g.
Decelle, Aurélien +1 more
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Advanced Science, EarlyView.Through a systematic and comprehensive analysis of the environmental impacts for the emerging MXene synthesis pathways, this study presents process transformation and optimization opportunities for low‐carbon MXene production from laboratory to industrial scales.
Yushuai Huang +6 more
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EJNMMI Physics, 2023 Background Kinetic modeling in positron emission tomography (PET) requires measurement of the tracer plasma activity in the absence of a suitable reference region.
Alan Miranda +3 more
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Transformation-invariant representation and NMF [PDF]
2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541), 2005 Non-negative matrix factorization (NMF) is a method for the decomposition of multivariate data into strictly positive activations and basis vectors. Here, instead of using unstructured data vectors, we assume that something is known in advance about the type of transformations that either the input data or the basis vectors may undergo.
J. Eggert, H. Wersing, E. Korner
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Advanced Science, EarlyView.The weakly‐solvating TFMSPyr electrolyte tailors the Li+ solvation structure by suppressing solvent coordination and promoting anion‐dominated solvation. This unique solvation environment induces preferential anion decomposition at electrode interfaces, forming robust inorganic rich S/CEI.
Bishnu P. Thapaliya +11 more
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