Poon H, Quirk C, DeZiel C, Heckerman D. Literome: PubMed-scale genomic knowledge base in the cloud Bioinformatics. 2014 Oct;30(19):2840-2. PMID: 24939151
--Genes in the interaction graph are connected by a number different types of -lines, with each type of line and the line properties themselves indicating -different levels of support from text mining and databases. -
-Here you can see nearly all of the different types of lines in a single -gene interaction graph centered around the ROBO3 gene:
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-Lines may include arrows showing the directionality of this interaction. In -these cases, the directionality is determined by majority support. For example, -imagine an interaction between protein A and protein B; two articles support -that A acts on B while a single article supports the opposite, B acting on A. -In this case, because there are more articles supporting A acting on B, then the -arrow will be drawn such that it starts at A and points to B. -
- --From the "Annotate Genes" drop-down, you can annotate genes based on GNF2 -average expression, drugability from DrugBank -entries, cancer type in the COSMIC Cancer Gene Census, and the number of non-silent -mutations identified by the PanCancer analysis -project. For the -GNF2 expression and PanCancer Mutation coloring, genes will be colored on a -sliding scale from light grey to black, with those items with the highest -expression or the largest number of non-silent mutations being colored the -darkest and those with lower expression or fewer mutations being colored grey. -Genes will be colored dark blue if there is no information in the database. -In this image, you can see a set of 14 genes that interact with TP53 -colored by their PanCancer Mutation number:
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-You can mouse-over items in the display to show more details about the gene -such as their product. If you've chosen to annotate genes with -one of the various databases, then it will display that information as well. -For example, hovering over the BAX gene in this exaple displays a description -of the gene product as wells as the number of Pan-Cancer mutations since that -option is selected: -
-You can mouse-over the connecting lines between genes to see more details about -the evidence that supports this connection. In this image, -you can see the details that pop-up when you mouse over such a line; information -displayed includes database support and text-mining support.
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-If you click on the line connecting two proteins, you can see a -SumBasic-selected -snippet of text from a Pubmed abstract and, if it is a curated interaction, the -supporting information from the pathway or interaction databases. This -example shows the text-mined support for an interaction between -CASP5 and HUNK:
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-Below the graph of gene interactions and pathways, there is table of less-supported -interactions. These are interactions which were mentioned only a few -times each in the literature.
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-The numbers shown on mouse-over for -each interaction represents the number of articles and number of databases that -support this interaction. -
- --You can export the currently displayed gene interaction graph in a variety of formats -including PDF, SVG, Cytoscape, and JSON. -
- --The gene interaction graph can be recentered around a new gene in a -few different ways: (1) clicking a gene in the existing interaction graph, (2) -clicking the triangle next to a gene in the table of minor interactions below -the graph, (3) searching for a gene name in the search box above the graph. -
- - - --Human protein interactions from the following databases were imported: -
- --The quantitative contribution of each database in terms of number of gene-pairs is available -here. -
- --For text mining, PubMed abstracts were downloaded from the National Library of Medicine (NLM) -website. The abstracts were then -tokenized and -parsed syntactically using the SPLAT toolkit. Protein -and Gene names were identified and normalized after which potential -interactions were extracted using the Microsoft Research NLP "Protein and Pathway -Extractors". The results were then mapped to the genome using their HGNC gene symbols. -Text-mining results supporting by only a single abstract are in the database tables but are -not shown in the user interface. -
- - --The raw data for these graphs can be accessed in multiple ways. They can be explored interactively -using the Table Browser, by selecting "group" - -"All Tables" -and "database" - "hgFixed". Under "table", select -"hgFixed.ggLink". You can then start to explore the -relationships between the database tables using the "describe table schema" button or -download tables with "get output". All database tables related to this viewer start with -the prefix "gg".
- --The database tables can also be accessed programmatically through our -public MariaDB server or downloaded from our -downloads server for local -processing. The database tables are: -
For more details about the tables and their fields, use the Table Browser's -"describe schema" button.
- --The annotations (GNF2 average expression, DrugBank, etc.) for genes are accessed as text files -for performance reasons and can be downloaded from our -downloads server. -
-Poon H, Quirk C, DeZiel C, Heckerman D. -Literome: PubMed-scale genomic knowledge base in the cloud -Bioinformatics. 2014 Oct;30(19):2840-2. -PMID: 24939151 -
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