NMF: Non-negtive matrix factorization

NMF: Non-negtive matrix factorization

video instroctrions:

• Non-Negative Matrix Factorization (NMF) | Multiplicative Update Rules By Lee And Seung; 2020; Youtube
• Non-negative Matrix Factorization (NMF) Implementation; 2020; Youtube

Blog and Papers:

Github codes:

• ahmadvh; 2019
• QColeman97; 2019
  Bacground
• non-negtive matrix factorization (NMF) is an unsupervised machine learning technique created by Lee & Seung in 1999.
• It is a verstile algorithm
  • Makes a parts-based-representation ofits input data
  • Non-nectivity of input data allows this

Uses

• Dimensionality reduction
• Data compression and approximation
• Audio source separation
• Text topic extraction

All input data should be positive numbers

Nonnegative Matrix Factorization: An Analytical and Interpretive Tool in Computational Biology^[1]

This paper reviewed the principle algorithm of the NMF and both its advantage and disadvantage in the biology data.

• Molecular pattern discovery

  • In cell level:
    • In the gene and protein expresion profile → expressoin pattern
    • find functional biological groups
  • gene level
    • A group of functional gene: functional cell group
  • Sequence level:
  • Sequence pattern among proteins.
  • Cancer type clustering, subclustering searching.
  • genomic hybridization data: patient subgroup

• Class comprision and prediction

  • Supevised learning framewaork
  • Identify differential expression gene with ANOVA.
  • Classification methods or protein folding recognision.

• Cross-Platform and Cross-Species Characterization

  • reduce noise
  • capturing invariant biological features
  • use of prior knowledge basd on existing datasets and generate new data

• Biomedical Information

  • NPL
  • PS: NPL: Topic modelling using NMF^[2]

• Functional Characterization of Genes
  • find the homogeneous functional group by the Gene ontology batabase
  • This methodology is implemented in the program called GENERATOR (GENElist Aimed Theme- discovery execuTOR).

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1. Devarajan, Karthik. “Nonnegative matrix factorization: an analytical and interpretive tool in computational biology.” PLoS computational biology 4.7 (2008): e1000029. ↩︎

2. CHIRA GOYAL; Part 15: Step by Step Guide to Master NLP – Topic Modelling using NMF; 2021(https://www.analyticsvidhya.com/blog/2021/06/part-15-step-by-step-guide-to-master-nlp-topic-modelling-using-nmf/) ↩︎