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

2. 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.

3. Application one  Keyword search. Database Keyword

4. Application one cont.  Search results.

5. Application one cont.  XML document.

6. 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.

7. Application one cont.  Procedure.

8. 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.

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

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

11. Application one cont.  Getting related literatures.

12. Application one cont.  Results (XML file data)

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

14. 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

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

16. Application one cont.  Storing search results.

17. Application one cont.  MySQL data.

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

19. 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

20. Application one cont.  Definition.

21. Application one cont.  Query keyword tagging.

22. Application one cont.  Tagged results.

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

24. 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.

25. 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.

26. 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.

27. Application four  To construct TF-TF co-occurrence graph.  Using Graphviz tools.  http://www.graphviz.org/ http://www.graphviz.org/  TF-TF co-occurrence relations from established literatures.  操作示範  Practice.