生物資訊程式語言應用 Part 5 Perl and MySQL Applications. Outline  Application one.  How to get related literature from PubMed?  To store search results in database.

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Presentation transcript:

生物資訊程式語言應用 Part 5 Perl and MySQL Applications

Outline  Application one.  How to get related literature from PubMed?  To store search results in database and find query keyword.  Application two.  How to establishment your own dictionary?  Application three.  How to search detail information, like TF-TF relations et al.  Application four.  To construct co-occurrence graph.

Application one  Keyword search. Database Keyword

Application one cont.  Search results.

Application one cont.  XML document.

Application one cont.  Practice.  To get related literature that you want to known in XML data format by using PubMed web service in NCBI website. (like E2F1, ERE et al.)  Advanced exercise.  To get sequence data from PubMed.  To establish sequence database by using Perl and MySQL.

Application one cont.  Procedure.

Application one cont.  What Perl language need?  Some Perl packages.  Known data (input data).  User query keyword, like “Estrogens”.  Information (output data).  Query results, like “Estrogens related candidate data”.  Knowledge (related data).  Data mining (extraction) from related candidate data.

Application one cont. User want to know Download online Service from PubMed Candidate related Literatures Output file of XML data

Application one cont.  Definition.  Packages and input data.

Application one cont.  Getting related literatures.

Application one cont.  Results (XML file data)

Application one cont.  Practice.  Using perl language to get related XML data.

Application one cont.  To store search results. XML format data of query results Data analysis for preparing to store data Query results in MySQL Database

Application one cont.  To store search results.  Definition.

Application one cont.  Storing search results.

Application one cont.  MySQL data.

Application one cont.  Practice.  To store obtained data into MySQL database.  PMID  Journal name  Article Title  Abstract  PubDate

Application one cont.  To find query keyword. Tagging keyword All Literatures in MySQL Database Tagging All Literatures According to Keyword Displaying Tagged Results by Web Page

Application one cont.  Definition.

Application one cont.  Query keyword tagging.

Application one cont.  Tagged results.

Application one cont.  Practice.  Tagging related abstracts from candidate literatures.  Gene name or protein name.  Action words.

Application one cont.  Challenge.  A tagging program that include two query words.  Query word one.  Tagged abstracts.  Un-tagged abstracts.  Query word two.  Tagged abstracts.  Un-tagged abstracts.  Complete data extraction system.

Application two  To establish transcription factor (TF) dictionary.  From EBI-SRS online resource.  To get TF text data from EBI-SRS.  Using Perl language to extract some data.  To store data into MySQL by Perl language.  操作示範  Practice.

Application three  To search TF-TF relations from established literatures.  Using TF dictionary.  Using Perl language to extract co-occurrence relations.  操作示範  Practice.

Application four  To construct TF-TF co-occurrence graph.  Using Graphviz tools.   TF-TF co-occurrence relations from established literatures.  操作示範  Practice.