How to query cider
- Per default the search space includes all diseases and all types of data. Queries are not case-sensitive and search all database content that includes the query term (e.g. Mito is sufficient to find everything concerning mitochondria). This type of query is highly unspecific as it includes also information such as gene/protein name synonyms and authors names from referenced literature.
- The first box of the search options (Diseases) allows to restrict the search space for the disease/-s of interest.
- The second box of the search options (Field) allows searching within a specific type of data, e.g. only within genes/proteins, biological processes etc.
- Combined queries can be performed by using Refine query. By clicking on Refine query a second search field is opened. A drop-down menu allows combining the two queries with the Boolean operators AND, OR and NOT.
- The search space can be restricted by setting the search term into double quotes (e.g. "MAPK1" will not find MAPK14 which would happen without quotes)
- The character for wild-card is '%'. It can also be used in a double-quoted search term.
|cell cycle||Finds every term that contains the words 'cell' and 'cycle' anywhere (also synonyms!), i.e. you will retrieve 'cell cycle', 're-entry into mitotic cell cycle' but also 'pyridoxal phosphate biosynthetic process'. The latter is a GO term that includes the words 'cell' and 'cycle' in higher level GO terms (GO:0044249 : cellular biosynthetic process and GO:0046483 : heterocycle metabolic process)|
|"cell cycle"||Finds only exactly 'cell cycle' but not 're-entry into mitotic cell cycle' or 'pyridoxal phosphate biosynthetic process'|
|"%cell cycle"||Finds 'cell cycle' and 're-entry into mitotic cell cycle' but not 'pyridoxal phosphate biosynthetic process'. "%cell cycle%" would, in addition, find terms like 'cell cycle arrest' or all textual comments that include 'cell cycle'.|
Visualization of data
- Results of a query are initially shown as a list. On top of the list is a button named 'Graphical view'. By clicking that button a new window with a graphical representation of the search results appears.
- A legend on the right explains type and colours of the different disease elements (nodes) and their interactions (edges).
- Moving with the mouse cursor over an edge results in a pop-up window that displays the content of the respective interaction/-s.
- The graph can be moved by clicking and holding the left mouse button.
- The graph can be expanded for all interactions of an edge (e.g. protein, bioprocess etc.) by double-clicking on the respective node.
Origin of the data
Data in CIDeR are retrieved mostly from research articles and also from reviews. All interactions are manually annotated by experienced biocurators. All information from CIDeR is linked to the respective PubMed entries.
Curation of data
Information about disease-related interactions consists of three kinds of information.
- The central information is a structured interaction between two elements (e.g. protein A activates protein B). This is also known as subject-predicate-object structure. "Subjects" and "Objects" are linked/mapped to thesauri such as EntrezGene, KEGG, OMIM, miRBase, Gene Ontology, CORUM. If a term is not available in these vocabularies, we introduce suitable terms.
Additional information about conditions (Arg_Mod = mode) or locus (Arg_Loc) are also frequently presented.
- A textual comment allows to provide additional information about the experimental setup (e.g. concentration of a drug that was applied) and to present a more differentiated view than the structured information (e.g. the structured information is restricted to 'protein A increases_activity of protein B' whereas in the text we can specify that it is a 'significant' or a 'slight' increase of the protein activity).
- The general information consists of literature reference, organism, disease and if available tissue/cell line and gender. All information is linked to the PubMed content of the respective journal articles.
Information in CIDeR is given as entries and interactions. An entry comprises one or more result/-s (interactions) from one publication that was/were obtained under the same experimental conditions. A relation is part of an entry and describes an interaction between two elements (e.g. protein A increases_activity of protein B).
Dr. Andreas Ruepp
Institute of Bioinformatics and Systems Biology/MIPS