Bioinformatics as a Queryable Knowledge Map: the Pygr Project
26:29
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1 year ago
(this talk was presented at the UCLA Bioinformatics IDP Retreat, 5/23/08)
The Python Graph Database Framework for bioinformatics (Pygr) provides:
1. Tools for sequence analysis and comparative genomics such as sequence databases, search methods such as BLAST, repeat-masking, megablast, etc., sequence annotation databases and annotation query, and sequence alignment datasets. It also provides unprecedented scalability and performance to work with terabyte-scale multigenome alignment databases.
2. An importable namespace for bioinformatics data resources and schemas. You assign a given resource a unique name that then becomes its universal handle for accessing it, no matter where you are (just as Python's import command provides a consistent name for accessing a given code resource, regardless of where you are). You save schema relationships between datasets via direct assignment statements to this namespace. Whenever data are accessed from this namespace (accessed via import pygr.Data), their dependencies and data relationships are automatically bound as object attributes, which are each loaded only when the user seeks to access it. All the user needs to know is the name of the initial dataset s/he wishes to work with, and the names of attributes that constitute its “object model”.
3. Easy data sharing and services: Pygr.Data includes transparent access over network protocols like XMLRPC. All a client has to do is import pygr.Data and start requesting desired data resource names; pygr.Data will figure out where (and how) to get them, obtaining data locally if possible, or from a server.
Pygr has extensive tutorials and documentation,
and runs on UNIX, Mac OS X, and Windows; see http://www.bioinformatics.ucla.edu/pygr for more details.(this talk was presented at the UCLA Bioinformatics IDP Retreat, 5/23/08)
The Python Graph Database Framework for bioinformatics (Pygr) p...all »(this talk was presented at the UCLA Bioinformatics IDP Retreat, 5/23/08)
The Python Graph Database Framework for bioinformatics (Pygr) provides:
1. Tools for sequence analysis and comparative genomics such as sequence databases, search methods such as BLAST, repeat-masking, megablast, etc., sequence annotation databases and annotation query, and sequence alignment datasets. It also provides unprecedented scalability and performance to work with terabyte-scale multigenome alignment databases.
2. An importable namespace for bioinformatics data resources and schemas. You assign a given resource a unique name that then becomes its universal handle for accessing it, no matter where you are (just as Python's import command provides a consistent name for accessing a given code resource, regardless of where you are). You save schema relationships between datasets via direct assignment statements to this namespace. Whenever data are accessed from this namespace (accessed via import pygr.Data), their dependencies and data relationships are automatically bound as object attributes, which are each loaded only when the user seeks to access it. All the user needs to know is the name of the initial dataset s/he wishes to work with, and the names of attributes that constitute its “object model”.
3. Easy data sharing and services: Pygr.Data includes transparent access over network protocols like XMLRPC. All a client has to do is import pygr.Data and start requesting desired data resource names; pygr.Data will figure out where (and how) to get them, obtaining data locally if possible, or from a server.
Pygr has extensive tutorials and documentation,
and runs on UNIX, Mac OS X, and Windows; see http://www.bioinformatics.ucla.edu/pygr for more details.«
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