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non-negative matrix factorization nmf  (MathWorks Inc)


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    MathWorks Inc non-negative matrix factorization nmf
    Non Negative Matrix Factorization Nmf, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/non+negative+matrix+factorization/pm40347472-191-2-8
    Average 90 stars, based on 1 article reviews
    non-negative matrix factorization nmf - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Atypical cortical networks in children at high-genetic risk of psychiatric and neurodevelopmental disorders.
    Article Snippet: In order to reduce the dimensionality of these features before statistical analyses, we used a data-driven analysis of the principal components using non-negative matrix factorization (NNMF, Matlab: nnmf).

    Article Title: A left-lateralized dorsolateral prefrontal network for naming.
    Article Snippet: We used non-negative matrix factorization (NMF, nnmf function, MATLAB) as a soft clustering technique to cluster the neural data.

    Article Title: Common multi-day rhythms in smartphone behavior.
    Article Snippet: The non-negative matrix factorization (mexTrainDL, spams package for MATLAB, Inria) yielded two matrices: a meta-rhythms matrix W 2 RT 0 ́ Rand a meta-behavior matrix H 2 RR ́ 2500 where R is the optimal factorization rank.

    Article Title: Oxidation of retromer complex controls mitochondrial translation.
    Article Snippet: Junbing Zhang1,2,14 ✉, Md Yousuf Ali, Harrison Byron Chong, Pei-Chieh Tien, James Woods, Carolina Noble, Tristan Vornbäumen, Zehra Ordulu, Anthony P. Possemato, Stefan Harry, Jay Miguel Fonticella, Lina Fellah, Drew Harrison, Maolin Ge, Neha Khandelwal, Yingfei Huang, Maëva Chauvin, Anica Tamara Bischof, Grace Marie Hambelton, Magdy Farag Gohar, Siwen Zhang, MinGyu Choi, Sara Bouberhan, Esther Oliva, Mari Mino-Kenudson, Natalya N. Pavlova, Michael Lawrence, Justin F. Gainor, Sean A. Beausoleil, Nabeel Bardeesy, Raul Mostoslavsky, David Pépin, Christopher J. Ott, Brian Liau & Liron Bar-Peled1,7,10 ✉

    Article Title: Muscle Recruitment Strategies in a Redundant Task: Age Differences Through Network Analyses.
    Article Snippet: The overall analysis procedure was similar for the three methods: we concatenated the data of interest, filtered it to avoid high frequency oscillations created by concatenation, and performed the non-negative matrix factorization (nnmf code in Matlab).

    Article Title: Neuromuscular mechanisms of motor adaptation to repeated gait-slip perturbations in older adults
    Article Snippet: Muscle synergies were extracted from EMG matrices with unit variance for each condition (novel, early-, and late-adaptation) by non-negative matrix factorization using customized Matlab routines , which is a decomposition algorithm used extensively in muscle synergy analysis , , .

    Article Title: Cellular architecture of human brain metastases.
    Article Snippet: Identification of recurrent expression programs in human brain metastases with Non-Negative Matrix Factorization (NMF) For tumor cells in each sample, Non-Negative Matrix Factorization (Matlab nnmf function, with number of factors set to 10) was applied to the scaled and centered expression data (Seurat ScaleData function), after converting all negative values to zero.

    Article Title: Cellular architecture of human brain metastases.
    Article Snippet: As previously described in human data analysis, for both experimental models, Non-Negative Matrix Factorization (Matlab nnmf function, with number of factors set to 10) was applied to scaled and centered expression data (Seurat ScaleData function), after converting all negative values to zero.



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    Image Search Results


    ( a ) Surgical paradigm. In a TetO-GCaMP6s × CaMKII-tTa mouse, 9 AAV retro viruses are injected into downstream brain regions and gradient-index (GRIN) lens implanted into the target region. ( b ) Simultaneous recording of GCaMP6s (top) and behavior (bottom) during a social memory task. Scale bar = 100 µm ( c ) GCaMP6s recordings are processed. Constrained non-negative matrix factorization (CNMF)-defined ROIs (top) and ΔF/F traces (bottom) are exported. Scale bar = 100 µm. ( d ) Mice are head fixed and FOV under the GRIN lens imaged using the multiplexed lambda method. ( e ) Transformations are determined using anatomical background images to co-register the two imaging platforms. The transformations are applied to CNMF-defined ROIs. Scale bar = 100 µm. ( f ) Multispectral data are collected for each ROI (top) and an average spectral fingerprint for all ROIs is generated (bottom). Mean ±1.5 SD. Scale bar = 100 µm. ( g ) A linear unmixing model is applied to determine the fluorophore contribution for each ROI. Scale bar = 100 µm. ( i ) Neural activity is sorted by cell type. Scale bars = 20 ΔF/F (vertical), 20 s (horizontal).

    Journal: eLife

    Article Title: Functional imaging of nine distinct neuronal populations under a miniscope in freely behaving animals

    doi: 10.7554/eLife.110277

    Figure Lengend Snippet: ( a ) Surgical paradigm. In a TetO-GCaMP6s × CaMKII-tTa mouse, 9 AAV retro viruses are injected into downstream brain regions and gradient-index (GRIN) lens implanted into the target region. ( b ) Simultaneous recording of GCaMP6s (top) and behavior (bottom) during a social memory task. Scale bar = 100 µm ( c ) GCaMP6s recordings are processed. Constrained non-negative matrix factorization (CNMF)-defined ROIs (top) and ΔF/F traces (bottom) are exported. Scale bar = 100 µm. ( d ) Mice are head fixed and FOV under the GRIN lens imaged using the multiplexed lambda method. ( e ) Transformations are determined using anatomical background images to co-register the two imaging platforms. The transformations are applied to CNMF-defined ROIs. Scale bar = 100 µm. ( f ) Multispectral data are collected for each ROI (top) and an average spectral fingerprint for all ROIs is generated (bottom). Mean ±1.5 SD. Scale bar = 100 µm. ( g ) A linear unmixing model is applied to determine the fluorophore contribution for each ROI. Scale bar = 100 µm. ( i ) Neural activity is sorted by cell type. Scale bars = 20 ΔF/F (vertical), 20 s (horizontal).

    Article Snippet: We extracted spatial and temporal components of neuronal activity from miniscope videos using constrained non-negative matrix factorization for endoscopic data (CNMF-E) implemented through the Inscopix Data Processing Software.

    Techniques: Injection, Imaging, Generated, Activity Assay