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Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
Databases can contain both empirical data (obtained directly from experiments) and predicted data (obtained from analysis of existing data). They may be specific to a particular organism, pathway or molecule of interest. Alternatively, they can incorporate data compiled from multiple other databases.
Stem cell genomics: Helps in stem cell biology. Aim is to establish stem cells as a leading model system for understanding human biology and disease states and ultimately to accelerate progress toward clinical translation. Connectomics: The study of the connectome, the totality of the neural connections in the brain.
Cellular deconvolution algorithms have been applied to a variety of samples collected from saliva, [5] buccal, [5] cervical, [5] PBMC, [6] brain, [2] kidney, [1] and pancreatic cells, [1] and many studies have shown that estimating and incorporating the proportions of cell types into various analyses improves the interpretability of high ...
The human genome contains on the order of 20,000 genes which work in concert to produce roughly 1,000,000 distinct proteins. This is due to alternative splicing, and also because cells make important changes to proteins through posttranslational modification after they first construct them, so a given gene serves as the basis for many possible versions of a particular protein.
ADT data analysis [2] [7] [10] [11] (based on the developer's guidelines): CITE-seq-Count is a Python package from CITE-Seq developers that can be used to obtain raw counts. Seurat package from Satija lab further allows combining of the protein and RNA counts and performing clustering on both measurements, as well as doing differential ...
Insights based on single-cell data analysis assume that the input is a matrix of normalised gene expression counts, generated by the approaches outlined above, and can provide opportunities that are not obtainable by bulk. Three main insights provided: [18] Identification and characterization of cell types and their spatial organisation in time
However, the analysis of relative mRNA expression levels can be complicated by the fact that relatively small changes in mRNA expression can produce large changes in the total amount of the corresponding protein present in the cell. One analysis method, known as gene set enrichment analysis, identifies coregulated gene networks rather than ...