ArticleSource code for biology and medicine2013
The non-negative matrix factorization toolbox for biological data mining.
Article in Source code for biology and medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed.
- An Orthogonal Semi-Nonnegative Matrix Factorization Method for Dynamic Functional Connectivity Analysis and Its Application to Schizophrenia.IEEE journal of biomedical and health informatics · 2026Article
- Recovering missing features in nonnegative matrix factorization via generalized singular value decomposition.iScience · 2026Article
- Hyperspectral dark-field microscopy of human breast lumpectomy samples for tumor margin detection in breast-conserving surgery.Journal of biomedical optics · 2024Article
- Muscle Synergy Analysis as a Tool for Assessing the Effectiveness of Gait Rehabilitation Therapies: A Methodological Review and Perspective.Bioengineering (Basel, Switzerland) · 2024Review
- Crosstalk among proximal tubular cells, macrophages, and fibroblasts in acute kidney injury: single-cell profiling from the perspective of ferroptosis.Human cell · 2024Article
- Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles.iScience · 2024Article
- Dynamics of brain-muscle networks reveal effects of age and somatosensory function on gait.iScience · 2024Article
- Spatial lipidomics of coronary atherosclerotic plaque development in a familial hypercholesterolemia swine model.Journal of lipid research · 2024Article
- Open-ended movements structure sensorimotor information in early human development.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
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- Development of running is not related to time since onset of independent walking, a longitudinal case study.Frontiers in human neuroscience · 2023Article
- Label-free analytic histology of carotid atherosclerosis by mid-infrared optoacoustic microscopy.Photoacoustics · 2022Article
- Disentangling tau and brain atrophy cluster heterogeneity across the Alzheimer's disease continuum.Alzheimer's & dementia (New York, N. Y.) · 2022Article
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- Dissecting cascade computational components in spiking neural networks.PLoS computational biology · 2021Article
- Respiration modulates oscillatory neural network activity at rest.PLoS biology · 2021Article
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- Real-Time and Offline Evaluation of Myoelectric Pattern Recognition for the Decoding of Hand Movements.Sensors (Basel, Switzerland) · 2021Article
- Identification of Distinct Molecular Patterns and a Four-Gene Signature in Colon Cancer Based on Invasion-Related Genes.Frontiers in genetics · 2021Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNon-negative matrix factorization (NMF) has been introduced as an important method for mining biological data. Though there currently exists packages implemented in R and other programming languages, they either provide only a few optimization algorithms or focus on a specific application field. There does not exist a complete NMF package for the bioinformatics community, and in order to perform various data mining tasks on biological data.
resultsWe provide a convenient MATLAB toolbox containing both the implementations of various NMF techniques and a variety of NMF-based data mining approaches for analyzing biological data. Data mining approaches implemented within the toolbox include data clustering and bi-clustering, feature extraction and selection, sample classification, missing values imputation, data visualization, and statistical comparison.
conclusionsA series of analysis such as molecular pattern discovery, biological process identification, dimension reduction, disease prediction, visualization, and statistical comparison can be performed using this toolbox.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.