Data Retrieval and Storage

From 2008.igem.org

(Difference between revisions)

Latest revision as of 02:22, 30 October 2008

Home	The Team	The Project	Notebook

Evolutionary Algorithm	Data Retrieval	Modeling	Graphical User Interface

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 needed to answer the following questions about each part:

If it is an enzyme, what reactions does it catalyze?
If it is a molecule, what is its molecular structure, and what are the synonyms for the molecule name?

The answers to these questions would allow EvoGEM to better distinguish between different compounds. 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 needed for retrieving and expanding EvoGEM's local database.

UniProt

If a protein makes up one of the parts retrieved from the iGEM database, the registry provides its amino acid sequence, which can be used to infer all other required information. Namely, the program sends this amino acid sequence 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 simple because molecules can be queried using synonyms. After a molecule is queried, ChemSpider produces information about the molecule such as its SMILES, which is a simplified molecular input line entry specification. As useful as this information can be, we needed something that is machine-readable and that could be used for comparisons of metabolic pathways. What is this machine readable format? It 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 retrieves one of the parts, recording 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 a reaction, the program searches for the catalzed compounds in ChemSpider. There, it retrieves more information, such as the InChi, in a local database. Consequently, we now have a large database ready for use for EvoGEM.

Data Retrieval Flow Chart

Navigation

Evolutionary Algorithm	Data Retrieval	Modeling	Graphical User Interface

Home	The Team	The Project	Notebook

@@ Line 8: / Line 8: @@
 !align="center"|[[Team:Calgary_Software/Team|The Team]]
 !align="center"|[[Team:Calgary_Software/Project|The Project]]
-!align="center"|[[Team:Calgary_Software/Modeling|Modeling]]
 !align="center"|[[Team:Calgary_Software/Notebook|Notebook]]
 |}
 {| style="background-color:#D1ECAA;" cellpadding="3" cellspacing="1" border="1" bordercolor="#416023" width="64%" align="center"
+!align="center"|[[Evolutionary Algorithm|Evolutionary Algorithm]]
 !align="center"|[[Data_Retrieval_and_Storage|Data Retrieval]]
 !align="center"|[[Modeling|Modeling]]
-!align="center"|[[Evolutionary Algorithm|Evolutionary Algorithm]]
 !align="center"|[[Team:Calgary_Software/Project/Graphical User Interface|Graphical User Interface]]
 |}
@@ Line 21: / Line 20: @@
 == Perl ==
-[[Image:Perl_logo.PNG‎|thumb|160px|right]]
+[[Image:Perl_logo.PNG‎||thumb|right|160px]]
-<div align=justify>The first major thing the software team worked on was finding a way to expand the database for EvoGEM. As of that moment, EvoGEM only had a small database of BioBrick parts, and all of those parts were added manually. Since the iGEM registry consisted of hundreds of parts, manually adding parts would not be practical. In addition, these parts were needed so that more sophisticated tests could made with EvoGEM. Also, we wanted to have some way of comparing the parts that were retrieved. 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 learn and distinguish different molecules and compounds better. How do we accomplish this, though? By creating a Perl script! </div>
+<div align=justify>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 needed to answer the following questions about each part:
+* If it is an enzyme, what reactions does it catalyze?
+* If it is a molecule, what is its molecular structure, and what are the synonyms for the molecule  name?
-<div align=justify>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. </div>
+The answers to these questions would allow EvoGEM to better distinguish between different compounds. How do we accomplish this, though? By creating a Perl script!  </div>
+<div align=justify>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 needed for retrieving and expanding EvoGEM's local database.</div>
 <br style="clear:both"/>
 == UniProt ==
-[[Image:UniProt.PNG|thumb|180px|left]]
+[[Image:UniProt.PNG|thumb|left|180px]]
 <div align=justify>
-If there is a protein that is existent in 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 used and queried by using something known as the Blast algorithm, which is a very powerful tool. When inputting the DNA or amino acid sequence, UniProt will give results that are closest to the initial search. Besides giving the name of the protein searched, UniProt will give the further products and reactants involved in this protein. All this information can be used for further use for EvoGEM and is stored in a local database. After going to the registry for the information of the parts. Go here [http://www.uniprot.com Uniprot] to see this database. </div>
+If a protein makes up one of the parts retrieved from the iGEM database, the registry provides its amino acid sequence, which can be used to infer all other required information.  Namely, the program sends this amino acid sequence 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. </div>
 <br style="clear:both"/>
@@ Line 42: / Line 45: @@
 <div align=justify>
-After results are gone through UniProt, if there are further molecules that are involved in the reaction that are not proteins, the search goes to ChemSpider. This large database is much like UniProt except that it is for chemistry. Searching and querying in ChemSpider is quite simple as things can be queried using synonyms of molecules. This makes it a very useful tool. After a molecule is queried, ChemSpider will produce 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:
+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  simple because molecules can be queried using synonyms.  After a molecule is queried, ChemSpider produces information about the molecule such as its SMILES, which is a simplified molecular input line entry specification. As useful as this information can be, we needed something that is machine-readable and that could be used for comparisons of metabolic pathways. What is this machine readable format? It 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, go here: [http://www.chemspider.com ChemSpider]
+To see this database, visit: [http://www.chemspider.com ChemSpider]
 <br style="clear:both"/>
@@ Line 52: / Line 55: @@
 == The Algorithm ==
-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 align=justify>
+The Perl script’s algorithm works in the following manner: First, the program goes to the iGEM registry and retrieves one of the parts, recording 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 a reaction, the program searches for the catalzed compounds in ChemSpider. There, it retrieves more information, such as the InChi, in a local database.  Consequently, we now have a large database ready for use for EvoGEM. </div>
+[[Image:Retrieval flow chart.PNG|thumb|center|200px| Data Retrieval Flow Chart]]
 == Navigation ==
@@ Line 58: / Line 66: @@
 {| style="background-color:#D1ECAA;" cellpadding="3" cellspacing="1" border="1" bordercolor="#416023" width="64%" align="center"
+!align="center"|[[Evolutionary Algorithm|Evolutionary Algorithm]]
 !align="center"|[[Data_Retrieval_and_Storage|Data Retrieval]]
 !align="center"|[[Modeling|Modeling]]
-!align="center"|[[Evolutionary Algorithm|Evolutionary Algorithm]]
 !align="center"|[[Team:Calgary_Software/Project/Graphical User Interface|Graphical User Interface]]
 |}
@@ Line 68: / Line 76: @@
 !align="center"|[[Team:Calgary_Software/Team|The Team]]
 !align="center"|[[Team:Calgary_Software/Project|The Project]]
-!align="center"|[[Team:Calgary_Software/Modeling|Modeling]]
 !align="center"|[[Team:Calgary_Software/Notebook|Notebook]]
 |}