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Pathways

Pathways

Is a tutorial on how to use RiceCyc available?

Yes, we have a RiceCyc Tutorial available at http://www.gramene.org/tutorials/pathways.html.

What can RiceCyc do for me?

You can use RiceCyc to further your understanding of your chosen gene's role in biochemical pathways, to find out about any metabolic reactions that it may be a part of, and to see if it is associated with any known protein complexes.

How was the data in RiceCyc generated?

All the data that you see in RiceCyc is generated computationally by use of the Pathway Tools program developed at SRI international by Peter Karps group.

What version of Pathway Tools does RiceCyc use?

RiceCyc is currently based on version 9.5 of Pathway Tools. We are aware that newer versions of pathway tools are available; we like to thoroughly test the latest versions of RiceCyc and Pathway Tools before making them available to the public.

Is RiceCyc manually curated?

At the present time most data you see on RiceCyc has been created computationally. We have been manually curating RiceCyc since August 2006. The manual curation of RiceCyc is an ongoing process and there will be regular updates.

Where can I find further information about biochemical pathways and reactions?

There is a list of informative links on the RiceCyc entry page (http://www.gramene.org/pathway/). These include links to Brenda, KEGG and BioCyc amongst others.

What species does RiceCyc have information on?

RiceCyc has datasets for Rice, Arabidopsis and E. coli. The information for Arabidopsis and E. coli makes use of information from TAIR and SRI Research. Click on the following links for the latest versions of AraCyc http://www.arabidopsis.org/tools/aracyc/ and EcoCyc http://www.ecocyc.org .

What form should I have my data in when I upload to the Omics viewer?

You should upload your data as a tab delimited text file.

I have uploaded data to the Omics viewer but nothing seems to be happening!

The time taken to get results from the Omics viewer is dependent upon the number of genes that you enter. If you enter a small number of genes it generally takes from 5 to 10 minutes until you see the results. If using 50,000 genes it can take up to an hour to calculate and display the results. For those who wish to upload large sets of data it is suggested that you try a pilot run with a subset of your data to ensure that you have it in the right form. For faster results it is recommend that you first filter your microarray results so as to only map genes that are differentially regulated.

What do the different colours represent in the RiceCyc schematics?

Blue lines represent reactions. Red represents compound. Orange represents enzymes. Purple represents Gene name. Dark Blue represents EC number.

In the Omics viewer I get the error message [ " " is not a valid integer]. What does this message mean?

I have a feeling that this error is due to you not entering a number in the " ata column (numerator in ratios):" (see slide 29 of the tutorial). Generally the first column (that contains the LOC identifier) is known as column 0, and the first data column will be 1, the second column 2, etc. Hopefully be entering the number(s) of the column that you wish to view in the data column, you will overcome this problem.

Where may I get the RiceCyc data?

You may get the data from Gramene's ricecyc ftp site ftp://ftp.gramene.org/pub/gramene/ricecyc/

Using my data in the pathways module, a certain pathways are painted in red (upregulated). Further, the details analysis revealed that some of the genes of the pathway are down regulated . Please explain this contradiction.

When there are multiple genes involved in a single step, the software makes a decision whether to display a pathway as being up or down regulated based upon a weighted average of all the known data. Any choice made will be misleading in some set of circumstances. As Omics viewer chooses the color based on the value that has the greatest deviation from zero, the discrepancy in your results can be explained by the fact that the seven-fold upregulation of one of the genes overwhelms the four-fold downregulation of the other three genes.