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Anti-AMACR antibody [ABT-AMACR]

Catalog No : V0006
  • Applications
    IHC, WB
  • Host Species
    Mouse
  • Reactivity
    Human
  • Size
    50ul
  • Price
    $175.00
Details
  • Product Name
    Anti-AMACR antibody [ABT-AMACR]
  • Catalog No
    V0006
  • Description
    Mouse monoclonal [ABT-AMACR] antibody to AMACR
  • Applications
    IHC, WB
  • Clonality
    Monoclonal
  • Host Species
    Mouse
  • Reactivity
    Human
  • ABT Clone ID
    ABT-AMACR
  • Antigen Retrieval
    Heat-induced epitope retrieval (HIER)
  • Dilution
    1:50-200
  • Entrez Gene ID (NCBI)
    23600
  • IHC Recommended control
    Prostatic adenocarcinoma
  • IHC Target Name
    AMACR
  • Immunogen
    Synthetic peptide
  • Localization
    Cytoplasmic
  • OMIM
    604489
  • Purification
    Immunogen affinity purified
  • Research
    Prostate carcinoma, nephrogenic adenoma, colon adenocarcinoma, prostate adenocarcinoma
  • Retrieval buffer
    TRIS-EDTA of pH8.0
  • Source/Ig Isotype
    Mouse IgG
  • Storage/Stablility
    -20°C/1 year
  • Synonyms
    Alpha-methylacyl-CoA racemase, 2-methylacyl-CoA racemase, P504s
  • UniProt Gene Name
    AMACR
  • UniProtKB
    Q9UHK6
Application Images
Image 1 Immunohistochemistry analysis of Formalin-fixed, paraffin-embedded Human Prostatic carcinoma using AMACR antibody.
Image 2 Immunohistochemistry analysis of Formalin-fixed, paraffin-embedded Human Prostatic carcinoma-high magnification using AMACR antibody.
Image 3 Immunohistochemistry analysis of Formalin-fixed, paraffin-embedded Human Prostatic carcinoma using AMACR antibody.
Image 4 Immunohistochemistry analysis of Formalin-fixed, paraffin-embedded Human Prostatic carcinoma-high magnification using AMACR antibody.
Image 5 Immunohistochemistry analysis of Formalin-fixed, paraffin-embedded Human Prostatic carcinoma using AMACR antibody.
Image 6 Immunohistochemistry analysis of Formalin-fixed, paraffin-embedded Human rostatic carcinoma-high magnification using AMACR antibody.
  • 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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