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Medical Scientific and Chemicals Inc mean square contingency coefficient
Mean Square Contingency Coefficient, supplied by Medical Scientific and Chemicals 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/mean+square+contingency+coefficient/mean+square+contingency+coefficient/pmc07007360-456-20-23
Average 90 stars, based on 1 article reviews
mean square contingency coefficient - by Bioz Stars, 2026-10
90/100 stars

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Expressing:

Article Title: A Genetic Model of the Connectome
Article Snippet: .. Similarity Metrics To quantify how similar is the expression pattern of two neurons, we use the mean square contingency coefficient (MSCC) which was shown ( Arnatkeviciūtė et al., 2018 ) to be less biased by sparse expression data than the Jaccard index or Yule’s Q: r φ = n 11 n 00 − n 10 n 01 n 1 ∗ n 0 ∗ n ∗ 0 n ∗ 1 . .. Here n xy enumerates possible binary pairings, such that n 01 = ∑ i δ x i ,0 δ y i ,1 and n 1* = ∑ i δ x i ,1 , where * stands for “or.” The MSCC is maximal ( r ϕ = 1) when two neurons express exactly the same set of genes and minimal ( r ϕ = −1) when the expression patterns of the two neurons mirror each other (i.e., one has 0 the other has 1).

Article Title: A Genetic Model of the Connectome
Article Snippet: .. To quantify how similar is the expression pattern of two neurons, we use the mean square contingency coefficient (MSCC) which was shown ( Arnatkeviciūtė et al., 2018 ) to be less biased by sparse expression data than the Jaccard index or Yule’s Q: r φ = n 11 n 00 − n 10 n 01 n 1 ∗ n 0 ∗ n ∗ 0 n ∗ 1 . .. Here n xy enumerates possible binary pairings, such that n 01 = ∑ i δ x i ,0 δ y i ,1 and n 1* = ∑ i δ x i ,1 , where * stands for “or.” The MSCC is maximal ( r ϕ = 1) when two neurons express exactly the same set of genes and minimal ( r ϕ = −1) when the expression patterns of the two neurons mirror each other (i.e., one has 0 the other has 1).

Article Title: A Genetic Model of the Connectome
Article Snippet: .. Gene Expression Patterns Similarity Metrics To quantify how similar is the expression pattern of two neurons, we use the mean square contingency coefficient (MSCC) which was shown ( Arnatkeviciūtė et al., 2018 ) to be less biased by sparse expression data than the Jaccard index or Yule’s Q: r φ = n 11 n 00 − n 10 n 01 n 1 ∗ n 0 ∗ n ∗ 0 n ∗ 1 . .. Here n xy enumerates possible binary pairings, such that n 01 = ∑ i δ x i ,0 δ y i ,1 and n 1* = ∑ i δ x i ,1 , where * stands for “or.” The MSCC is maximal ( r ϕ = 1) when two neurons express exactly the same set of genes and minimal ( r ϕ = −1) when the expression patterns of the two neurons mirror each other (i.e., one has 0 the other has 1).

Gene Expression:

Article Title: A Genetic Model of the Connectome
Article Snippet: .. Gene Expression Patterns Similarity Metrics To quantify how similar is the expression pattern of two neurons, we use the mean square contingency coefficient (MSCC) which was shown ( Arnatkeviciūtė et al., 2018 ) to be less biased by sparse expression data than the Jaccard index or Yule’s Q: r φ = n 11 n 00 − n 10 n 01 n 1 ∗ n 0 ∗ n ∗ 0 n ∗ 1 . .. Here n xy enumerates possible binary pairings, such that n 01 = ∑ i δ x i ,0 δ y i ,1 and n 1* = ∑ i δ x i ,1 , where * stands for “or.” The MSCC is maximal ( r ϕ = 1) when two neurons express exactly the same set of genes and minimal ( r ϕ = −1) when the expression patterns of the two neurons mirror each other (i.e., one has 0 the other has 1).



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