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We also investigated the homogeneity of gene expression profiles and topological connectivity of modules generated by three different methods using average Pearson correlation as well as average clustering coefficient [ 29] of genes within the same module.
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DNA fingerprints were analyzed with GelCompar software, using the unweighted-pair group method using average linkages and Dice coefficients [ 68].
Clustering was carried out subsequently by the unweighted-pair group method using average linkages (UPGMA), to calculate a similarity matrix.
Similarity analysis was performed with Dice's coefficient, and clustering was done by using the unweighted-pair group method using average linkages (UPGMA) method.
Using FPQuest Software Bio-Radd Laboratories InCA HercUSAsimilarity), similandty and cluster analyses were performed with Dice coefficients of similarity and an unweighted pair group method using average linkage, respectively.
The dendrogram was generated using a distance matrix calculated with the categorical coefficient and the unweighted-pair group method using average linkages as previously described [ 14].
For the cluster analysis of the PhP-data, the unweighted-pair group method using average linkages (UPGMA) by the PhP-software (PhPlate Microplate Techniques AB) was used.
Concatenated sequences were aligned and used to construct unweighted pair group method using average linkages trees in MEGA4 software (www.megasoftware.net/mega4/mega.html).html
Clustering analyses were performed with a hierarchical method using average linkage and Euclidean distance metric to illustrate relationships between the different patients and cell lines.
Data classification involved a hierarchical clustering method using average linkage and Euclidean distance metric, and was visualized with TIGR's MeV (Multiple Experimental Viewer; Institute for Genomic Research).
Relative expression was determined using a version of the comparative threshold cycle (Ct) method using average amplification efficiency for each primer pair, determined using LinReg (Hårdstedt et al., 2005).
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