My goal is to generate a GO-terms netwerk in cytoscape containing all "biological processes" relevant for human cells. I am aware of the cytoscape gene ontology plugins like BinGO, Pingo and others but I think they all don't fit my requirements.

To get the network in Cytoscape, I need to get the GO-data from somewhere. My approach is to download a table of gene ontology terms (from homo sapiens, if that is possible :-S ) with their name and gene ontology accessions (GO:[0-9]+). Additionally I would like to download a table showing the relations between each go-term.

Though their might be a better/easier way to do this, I was trying to query the "go" database from ucsc. This database includes the tables "term" and "term2term". I believe these tables include the information I am looking for:

mysql --user=genome --host=genome-mysql.cse.ucsc.edu -A -D go -e 'select * from term limit 5'

+----+-----------------------+--------------+----------------+-------------+---------+
| id | name                  | term_type    | acc            | is_obsolete | is_root |
+----+-----------------------+--------------+----------------+-------------+---------+
|  1 | all                   | universal    | all            |           0 |       1 |
|  2 | is_a                  | relationship | is_a           |           0 |       0 |
|  3 | Candida GO slim       | subset       | goslim_candida |           0 |       0 |
|  4 | Generic GO slim       | subset       | goslim_generic |           0 |       0 |
|  5 | GOA and proteome slim | subset       | goslim_goa     |           0 |       0 |
+----+-----------------------+--------------+----------------+-------------+---------+

mysql --user=genome --host=genome-mysql.cse.ucsc.edu -A -D go -e 'select * from term2term limit 5' 

+----+----------------------+----------+----------+----------+
| id | relationship_type_id | term1_id | term2_id | complete |
+----+----------------------+----------+----------+----------+
|  1 |                    2 |       17 |       16 |        0 |
|  2 |                    2 |       17 |       20 |        0 |
|  3 |                    2 |       34 |       33 |        0 |
|  4 |                    2 |       17 |       50 |        0 |
|  5 |                    2 |       17 |       57 |        0 |
+----+----------------------+----------+----------+----------+

Next to these 2 tables there is also a species table:

mysql --user=genome --host=genome-mysql.cse.ucsc.edu -A -D go -e 'select * from species limit 5' 
+----+--------------+-------------+----------------+----------------+----------------------+-----------+------------+-------------+----------------+
| id | ncbi_taxa_id | common_name | lineage_string | genus          | species              | parent_id | left_value | right_value | taxonomic_rank |
+----+--------------+-------------+----------------+----------------+----------------------+-----------+------------+-------------+----------------+
|  1 |       127219 | NULL        | NULL           | Tellervini     |                      |      NULL |       NULL |        NULL | NULL           |
|  2 |        58017 | NULL        | NULL           | Hirondellea    |                      |      NULL |       NULL |        NULL | NULL           |
|  3 |        44919 | NULL        | NULL           | unidentified   | soil organism R6-143 |      NULL |       NULL |        NULL | NULL           |
|  4 |       342596 | NULL        | NULL           | unclassified   | Cytomegalovirus      |      NULL |       NULL |        NULL | NULL           |
|  5 |        55548 | NULL        | NULL           | Dermatemydidae |                      |      NULL |       NULL |        NULL | NULL           |
+----+--------------+-------------+----------------+----------------+----------------------+-----------+------------+-------------+----------------+

However, I don't see how the species table can be linked to the GO-terms.

My question is, how can I download go terms that:

• have term_type=biological_process
• Are derived from / relate to human

And how to subset the term2term table by the GO-terms found in the previous query?