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Social data scientists use both digitized data [22] (e.g. old books that have been digitized) and natively digital data (e.g. social media posts). [23] Since such data often take the form of found data that were originally produced for other purposes (commercial, governance, etc.) than research, data scraping, cleaning and other forms of preprocessing and data mining occupy a substantial part ...
In a 2004 paper published in the journal Nature, the International Chicken Genome Sequencing Consortium found that although a chicken doesn't have as much DNA as a human, it has about the same ...
An untouched project in computational genomics is the analysis of intergenic regions, which comprise roughly 97% of the human genome. [19] Researchers are working to understand the functions of non-coding regions of the human genome through the development of computational and statistical methods and via large consortia projects such as ENCODE ...
This includes approaches from systems and control, information theory, string analysis and data mining. [44] Computational approaches will remain critical for research and teaching, especially when information science and genome biology is taught in conjunction. [45] Phylogenetic tree of descendant species and reconstructed ancestors.
The chicken embryo is a unique model that overcomes many limitations to studying the biology of cancer in vivo. The chorioallantoic membrane (CAM), a well-vascularized extra-embryonic tissue located underneath the eggshell, has a successful history as a biological platform for the molecular analysis of cancer including viral oncogenesis, [8] carcinogenesis, [9] tumor xenografting, [1] [10] [11 ...
Sociogenomics, also known as social genomics, is the field of research that examines why and how different social factors and processes (e.g., social stress, conflict, isolation, attachment, etc.) affect the activity of the genome.
The refinement of the Plus and Minus method resulted in the chain-termination, or Sanger method (see below), which formed the basis of the techniques of DNA sequencing, genome mapping, data storage, and bioinformatic analysis most widely used in the following quarter-century of research.
Computational genomics refers to the use of computational and statistical analysis to decipher biology from genome sequences and related data, [1] including both DNA and RNA sequence as well as other "post-genomic" data (i.e., experimental data obtained with technologies that require the genome sequence, such as genomic DNA microarrays).