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Actin-pan Colorimetric Cell-Based ELISA Kit

Catalog No : CB5019
  • Reactivity
    Human, Mouse, Rat
  • Assay Type
    Cell-Based
  • Size
    1 Kit
  • Price
    $380.00
Details
  • Product Name
    Actin-pan Colorimetric Cell-Based ELISA Kit
  • Catalog No
    CB5019
  • Detection Method
    Colorimetric 450 nm
  • Dynamic Range
    > 5000 Cells
  • Storage/Stability
    4°C/6 Months
  • Reactivity
    Human, Mouse, Rat
  • Assay Type
    Cell-Based
  • Database Links
    Gene ID: 58/70/71/72, UniProt ID: P60709/Q9BYX7/P63261, OMIM #: 102540/612098/612794/613424/102560/604717/102610/161800/255310, Unigene #: Hs.118127/Hs.514581/Hs.1288
  • Format
    96-Well Microplate
  • Manual (PDF)
  • NCBI Gene Symbol
    ACTC1
  • Sub Type
    None
  • Synonyms
    ACTA, ACTA1, ACTS, Actin, alpha skeletal muscle, Alpha-actin 1, ACTB, Actin cytoplasmic 1, Beta-actin, ACTG, ACTG1, actin cytoplasmic 2, gamma-actin
  • TargetName
    Actin-pan
Application Images
Image 1
  • Xiang, F., Neal, P.: Efficient MCMC for temporal epidemics via parameter reduction. Comput. Stat. Data Anal.
  • Xiang, F., Neal, P.: Efficient MCMC for temporal epidemics via parameter reduction. Comput. Stat. Data Anal.
  • Xiang, F., Neal, P.: Efficient MCMC for temporal epidemics via parameter reduction. Comput. Stat. Data Anal.
  • Xiang, F., Neal, P.: Efficient MCMC for temporal epidemics via parameter reduction. Comput. Stat. Data Anal.
  • Xiang, F., Neal, P.: Efficient MCMC for temporal epidemics via parameter reduction. Comput. Stat. Data Anal.
For the process of attaching edges to nodes, it is straightforward to compute the likelihood using (2). However, because of the nature of weighted sampling without replacement, we have to, for each i, calculate the probability conditi onal on each of the Xi!Xi! permutations of the selected nodes and then aver age over all Xi!Xi! probabilities to arrive at the likelihood. As calculating the exact likelihood in this way is not computationally feasible because the factorial grows faster than the exponential function, we approximate the likelihood based on one permutation of weighted sampling without replacement instead. The contribution by the new edges brought by node i is
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