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  2. Microarray analysis techniques - Wikipedia

    en.wikipedia.org/wiki/Microarray_analysis_techniques

    Example of an approximately 40,000 probe spotted oligo microarray with enlarged inset to show detail. Microarray analysis techniques are used in interpreting the data generated from experiments on DNA (Gene chip analysis), RNA, and protein microarrays, which allow researchers to investigate the expression state of a large number of genes – in many cases, an organism's entire genome – in a ...

  3. Elbow method (clustering) - Wikipedia

    en.wikipedia.org/wiki/Elbow_method_(clustering)

    The method consists of plotting the explained variation as a function of the number of clusters and picking the elbow of the curve as the number of clusters to use. The same method can be used to choose the number of parameters in other data-driven models, such as the number of principal components to describe a data set.

  4. Determining the number of clusters in a data set - Wikipedia

    en.wikipedia.org/wiki/Determining_the_number_of...

    The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]

  5. Database index - Wikipedia

    en.wikipedia.org/wiki/Database_index

    The non-clustered index tree contains the index keys in sorted order, with the leaf level of the index containing the pointer to the record (page and the row number in the data page in page-organized engines; row offset in file-organized engines). In a non-clustered index, The physical order of the rows is not the same as the index order.

  6. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Mark cell ‘c’ as a new cluster; Calculate the density of all the neighbors of ‘c’ If the density of a neighboring cell is greater than threshold density then, add the cell in the cluster and repeat steps 4.2 and 4.3 till there is no neighbor with a density greater than threshold density. Repeat steps 2,3 and 4 till all the cells are ...

  7. BLOSUM - Wikipedia

    en.wikipedia.org/wiki/BLOSUM

    The genetic instructions of every replicating cell in a living organism are contained within its DNA. [2] Throughout the cell's lifetime, this information is transcribed and replicated by cellular mechanisms to produce proteins or to provide instructions for daughter cells during cell division, and the possibility exists that the DNA may be altered during these processes.

  8. Ward's method - Wikipedia

    en.wikipedia.org/wiki/Ward's_method

    Ward's minimum variance method is a special case of the objective function approach originally presented by Joe H. Ward, Jr. [1] Ward suggested a general agglomerative hierarchical clustering procedure, where the criterion for choosing the pair of clusters to merge at each step is based on the optimal value of an objective function. This ...

  9. Correlation clustering - Wikipedia

    en.wikipedia.org/wiki/Correlation_clustering

    But, in general a graph may not have a perfect clustering. For example, given nodes a,b,c such that a,b and a,c are similar while b,c are dissimilar, a perfect clustering is not possible. In such cases, the task is to find a clustering that maximizes the number of agreements (number of + edges inside clusters plus the number of − edges ...