Data Retrieval and Storage

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Revision as of 23:36, 28 October 2008

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Perl

Our first challenge was finding a way to expand the database for EvoGEM. Last year, EvoGEM only had a small database of BioBrick parts, all of which were added manually. Since the iGEM registry consisted of hundreds of parts, manually adding parts was not practical. In addition, more parts were needed to make more sophisticated tests with EvoGEM. Also, we wanted to have some way of comparing the retrieved parts. We answered the following questions about each part:

- If they were enzymes, what reactions were they catalyzing? - If they were molecules, what were the molecular structures or other synonyms for these compounds?

The answers to these questions would allow EvoGEM to distinguish between different compounds better. How do we accomplish this, though? By creating a Perl script! Perl is a programming language that is powerful in text processing facilities. Since it effectively uses string matching, it is an ideal language for searching text and manipulating text files, which is exactly what we need for retrieving and expanding EvoGEM's local database.

Perl is a programming language that is powerful in text processing facilities. Since it uses string matching so well, it is an ideal language for searching text and manipulating text files, which is exactly what is needed for retrieving and expanding the local database for EvoGEM.

UniProt

IIf a protein makes up one of the parts retrieved from the iGEM database, that result is sent to UniProt. UniProt is a large database of proteins and enzymes. This database can be queried by a Blast algorithm, which is a very powerful programming tool. When inputting the DNA or amino acid sequence, UniProt gives results that are closest to the initial search. Besides giving the name of the protein searched, UniProt will give the reagents from the reaction that the protein catalyzes. All this information is useful for EvoGEM and is stored in a local database. Visit [http://www.uniprot.com Uniprot] to see this database.

ChemSpider

The reagents from the reaction that the protein catalyzes are put through ChemSpider. This large database is much like UniProt except that it is for chemistry. Searching and querying in ChemSpider is quite simple because molecules can be queried using synonyms. After a molecule is queried, ChemSpider produces information about the molecule such as synonyms and SMILES, which is a simplified molecular input line entry specification. As useful as this information can be, the reason for coming for this database is to get something that is machine readable and can be used for comparisons of metabolic pathways. What is this machine readable format? This machine readable format is known as the IUPAC International Chemical Identifier (InChI). This InChi is a unique "fingerprint" of the molecule that is not ambiguous like SMILES and is supplied only by IUPAC. An example of an InChi would look like this:

1/C6H8O6/c7-1-2(8)5-3(9)4(10)6(11)12-5/h2,5,7-8,10-11H,1H2/t2-,5+/m0/s1

To see this database, visit: [http://www.chemspider.com ChemSpider]

The Algorithm

The Perl script’s algorithm works in the following manner. First, the program goes to the iGEM registry and takes one of the parts, where it records its name, type, and sequence. Then, if the part is a protein, it sends the information to Uniprot, where it undergoes the Blast algorithm. From there, it extracts the names of reactants and products and stores them in a file for EvoGEM's local database. Afterwards, if the protein catalyzes molecules, the program searches for these compounds in ChemSpider. There, it stores more information, such as the InChi, in the local database for further use. Consequently, we now have a large database ready for use for EvoGEM.

Data Retrieval Flow Chart

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 <div align=justify>
-The Perl script’s algorithm works in the following manner. First, it goes to the iGEM registry and takes one of the parts, where it records its name, type, and sequence. Then, if the part happens to be a protein, the information would be sent to Uniprot, where it will go through the Blast algorithm. From there, the names of reactants and products are extracted and stored into a file for the local database of EvoGEM. Afterwards, if there are molecules involved in the reaction of proteins, these compounds are searched in ChemSpider. There, more information such as the InChi is also stored into the local database for further use. (See Figure 2.0) Consequently, we now have a large database ready for use for EvoGEM. </div>
+The Perl script’s algorithm works in the following manner. First, the program goes to the iGEM registry and takes one of the parts, where it records its name, type, and sequence. Then, if the part is a protein, it sends the information to Uniprot, where it undergoes the Blast algorithm. From there, it extracts the names of reactants and products and stores them in a file for EvoGEM's local database. Afterwards, if the protein catalyzes molecules, the program searches for these compounds in ChemSpider. There, it stores more information, such as the InChi, in the local database for further use.  Consequently, we now have a large database ready for use for EvoGEM. </div>
-[[Image:Retrieval flow chart.PNG|thumb|center|200px|Figure 2.0 - Data Retrieval Flow Chart]]
+[[Image:Retrieval flow chart.PNG|thumb|center|200px| Data Retrieval Flow Chart]]
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