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Network Biology, Sequence, Pathway and Ontology Informatics

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Genome Data Analysis

Part of the book series: Learning Materials in Biosciences ((LMB))

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Abstract

Genome data analysis includes not only analytical methodology and algorithms but also extensive knowledge about life sciences. In this chapter, a short sequence analysis that includes sequence motif analysis, phylogenetic tree analysis, and the importance of visualization will be practiced in order to do a high valued analysis of genomic data. Biological pathway and gene ontology (GO), which are extensively used techniques for analyzing genomic data, will be explained in general terms. Biomedical knowledge-based text mining techniques and fundamental background of biological network analysis will be studied.

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Notes

  1. 1.

    Homology means similar DNA or protein sequences of an individual of the same or different species. It is used to infer sequence function by searching for a highly homologous sequence with a sequence of interest or to predict evolutionary correlation between sequences.

  2. 2.

    ► https://www.ncbi.nlm.nih.gov/pubmed/. More than 27 million MEDLINE references can be searched by using the PubMed system. Also, it is possible to retrieve the full text from 25 academic journals from the website in the PubMed system.

  3. 3.

    ► https://genome.ucsc.edu/

  4. 4.

    ► http://www.ncbi.nlm.nih.gov/projects/mapview

  5. 5.

    ► http://www.geneontology.org/Go.evidence.shtml

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Authors and Affiliations

  1. Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul, South Korea

    Ju Han Kim

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  1. Ju Han Kim
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Kim, J.H. (2019). Network Biology, Sequence, Pathway and Ontology Informatics. In: Genome Data Analysis. Learning Materials in Biosciences. Springer, Singapore. https://doi.org/10.1007/978-981-13-1942-6_10

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