生物資訊程式語言應用 Part 5
E N D
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. • http://www.graphviz.org/ • TF-TF co-occurrence relations from established literatures. • 操作示範 • Practice.