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  2. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    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]

  3. Omics - Wikipedia

    en.wikipedia.org/wiki/Omics

    Cellomics: The quantitative cell analysis and study using bioimaging methods and bioinformatics. Tomomics: A combination of tomography and omics methods to understand tissue or cell biochemistry at high spatial resolution, typically using imaging mass spectrometry data. [26]

  4. RNA-Seq - Wikipedia

    en.wikipedia.org/wiki/RNA-Seq

    Data management: A single RNA-Seq experiment in humans is usually 1-5 Gb (compressed), or more when including intermediate files. [59] This large volume of data can pose storage issues. One solution is compressing the data using multi-purpose computational schemas (e.g., gzip) or genomics-specific schemas. The latter can be based on reference ...

  5. Bioinformatics - Wikipedia

    en.wikipedia.org/wiki/Bioinformatics

    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.

  6. Gene expression profiling - Wikipedia

    en.wikipedia.org/wiki/Gene_expression_profiling

    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.

  7. 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 ...

  8. Cellular deconvolution - Wikipedia

    en.wikipedia.org/wiki/Cellular_deconvolution

    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 ...

  9. Transcriptome - Wikipedia

    en.wikipedia.org/wiki/Transcriptome

    A pipeline using RNA-seq or gene array data can be used to track genetic changes occurring in stem and precursor cells and requires at least three independent gene expression data from the former cell type and mature cells. [30] Analysis of the transcriptomes of human oocytes and embryos is used to understand the molecular mechanisms and ...