Table of Contents

1.Autobiographical Information

• Name: Susan Chen
• Email: susan_chen@berkeley.edu
• Interests:

1. modular design
2. genetic devices
3. biochemistry
4. reading
5. skating
6. eating at new places
7. playing board games

I take particular delight in climbing large things (statues, for example), and in anything that involves cold creaminess (liquid Nitrogen ice cream, for instance).

• Talents that I harbor:
  • moving my ears
  • turning 720 in the air
  • putting my foot above my head
  • eating enormous amounts of ice cream in one sitting

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2. Auto-add a link from your page to any one of the following:

• the Wikipedia page describing the development of Poliovirus vaccines by Salk and Sabin
• the Pubmed record for the 2002 Science paper by Wimmer et al, describing a synthetic biology approach to building live poliovirus
• any Genbank record for the Poliovirus genome

Cello J, Paul AV, Wimmer E.  Chemical synthesis of poliovirus cDNA: generation of infectious virus in the absence of natural template.  Science. 2002 Aug 9;297(5583):1016-8. Epub 2002 Jul 11.

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3. One Pubmed paper relating to polio of interest

Synopsis: The article gives a broad overview of the history of the polio virus especially in relation to the research and discovery of elements of polio pathogenesis.

Reference: Racaniello VR.  One hundred years of poliovirus pathogenesis.  Virology. 2006 Jan 5;344(1):9-16.

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4. Give two example of how computational biology is relevant to synthetic biology.

Example1

Synthetic Biology relies on the large volume of sequence and protein information available in the research literature to construct parts with novel functions. In order to accomplish this, it requires computational biology to create tools and databases that will organize information. Even more importantly, computational biology is useful in creating algorithms to compare and analyze information. Some of these tools include BLAST, GeneDesign, and others.

Example2

Synthetic biology seeks to construct heterologous synthetic parts and systems from existing biological parts. To undertake such an effort of making something de novo, (and despite the efforts of rational design, in which computational biology also occupies a main role. see rosetta) requires the construction of a large number of constructs for assaying. Computational biology, in this context, provides the algorithms and standardization required for synthetic biology to be a practical implementation. Clotho, is a software program developed by the 2008 iGEM computational team, that exemplifies the crucial role computational biology plays. The Clotho software designs algorithms for "optimal assembly." By optimal assembly, we mean an algorithm for finding the least number of steps to build the said parts. Assembly trees can be built that gives the synthetic biologist a physical framework to build parts from. Using software like Clotho, the biologist doing wetlab will be able to save thousands on reagents by virtue of having to construct less unncessary parts.

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5. Option 1: What is the difference between a virus and a transposon? Give a technological application of each. Discuss possible physical limitations on the design of modified viruses and/or transposons.

Name	what are they?	technological application	physical limitations on design
Virus	An infectious agent that can colonize new cells. A typical virus consists of nucleic acid material, protein coat, and some also have an envelop of fat. Viruses can survive outside the cell. The essential difference between a virus and transposon is the env gene which allows the virus to breach the wall of host cells.	Viruses are used for vectors for gene therapy. They can be used to target and destroy cancer cells.	Unlike the transposon, a virus can invade cells. There are components of the virus that must be present for the virus to infect other cells and propagate. For example, the HIV virus has an env gene that codes for gp160 which cleaves into two surface proteins that are essential for infecting CD4 T cells. In modifying a virus, the nucleic acid as well as some protein elements need to be conserved.
Transposon	A piece of DNA/RNA that hops around within the genome of a host cell. The mechanism of movement is "cut and paste". An example of a transposon is the mariner.	Transposons such as P-element, are used to genetically mutate model organisms.	Transposons are usually very versatile. However, there needs to be a delicate balance between the replication and suppression of their activity. Too much expression of replication would result in jeopardizing the integrity of the host. Hence, transposons also have comparatively inefficient transposions, which is somewhat beneficial to the cell, for the reason just listed. (1)

For more information: See: Wikipedia:Transposon and See: Wikipedia:Virus

(1) Martin SL, Garfinkel DJ.  Survival strategies for transposons and genomes.  Genome Biol. 2003;4(4):313. Epub 2003 Mar 28.

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6. Write a short description of the following type of tool:

• Protein structure prediction - Ab initio protein structure prediction software vs comparative protein structure modeling software
  • The purpose of protein structure prediction is to predict the three-dimensional structure of a protein from its amino acid sequence. Comparative protein structure modeling assumes that a particular protein adopts a structure reasonable close to the structure of another known protein. This prunes the search space and make the search easier. Ab initio protein structure prediction, however, does not make this assumption. Instead, this latter mode of structure prediction takes a de novo approach by predicting structure based on physical principles rather than on previously solved structures. It requires using stochastic methods to search for solutions, and requires vast computational powers. The value of ab initio prediction is that it provides valuable information in structural genomics. In general, both types of software predicts the structure of a protein, but via different methods. (2)

• gene function - controlled vocabularies for gene/enzyme function ("EC numbers" or the "Gene Ontology") vs Biochemical pathway databases
  • Gene function prediction is the prediction of the function of a protein encoded by the gene, and the storage of that data in a database. The Gene Ontology project seeks to standardize the descriptions and terms used to describe gene products. GO establishes certain terms that other collaborating databases uses, so that when a person searches for a particular term, related material can be more easily found (see Gene Ontology). The Biochemical pathway databases, on the other hand, contains complete metabolic pathways that are found when a particular compound/metabolite is typed into the search tool (see [[http://www.genome.jp/kegg/pathway.html][KEGG]). This sort of database does not emphasize standardization. Both are databases containing information on the characteristics and function of genes.

• structure analysis - Protein/protein docking software vs protein/small-molecule docking software
  • Docking is a general computational method to predict the optimal orientation of one molecule in reference to another when the two are bound in a stable complex. Both Protein-protein and Protein-small molecule docking provides a detailed atomistic understanding of the interactions between proteins, the spatial configuration adopted by proteins, and the strength and specificity of protein interactions; for this to work, however, the 3-D structure of the interacting proteins are required. One prominent application of docking is in the pharmaceutical industry where the small molecule drug binding to its target for the rational design and development of drugs. Another application of docking is in bioremediation, where protein-ligand docking predictions are made for enzymes and the pollutants that they degrade. Protein-protein docking provides a detailed atomistic understanding of the interactions between proteins, the spatial configuration adopted by proteins, and the strength and specificity of protein interactions; for this to work, however, the 3-D structure of the interacting proteins are required. The differences between the two types of docking is that the protein-protein docking requires more computational power since proteins-protein interactions are often more complex.

• sequence analysis - sequence assembly software vs gene-finding software
  • Sequence analysis refers to subjecting DNA or peptide sequence to sequence alignment, sequence databses, repeated sequence searches, and other bioinfomatics methods on a computer. One application of sequence analysis is to study new organisms; comparing sequences with known functions with new sequences from uncharacterized organisms allows scientists to find homology between the organisms and to better characterize the new organism's function. Sequence assembly refers to aligning and merging fragments of much longer DNA sequence in order to reconstruct the original sequence. This is important because DNA sequencing technology cannot read whole genomes but can only piece small pieces together. Gene finding usually refers to algorithmically identifying stretches of sequences that are biologically functional. It is an important way of understanding the genome of a species once it is known. Both of these programs uses the genome of an organism to better characterize it, but sequence assembly pieces the genes together while gene finding software does more downstream work of annotating the genes for function.

• RNA structure - RNA folding software vs RNA design software
  • RNA folding software predicts RNA structure based on nucleic acid sequence. Most RNA algorithms predict secondary structure, tertiary structure. RNA design software such as RNAsoft, generates the nucleic acid sequence given a particular secondary structure as the input. A main application of RNA design software is in the rational design of targeted nucleic acids. For example, siRNA, which has various medical applications in treating conditions such as macular degeneration and respiratory syncytial virus, is an active target, as well as trans-cleaving ribozymes that are used in gene knock-down studies. RNA folding and design software both use RNA folding algorithms, but one is the prediction of RNA structure based on the nucleic acid sequence, while the other is the design of a nucleic acid sequence with a particular secondary structure in mind.

category	examples
Protein Structure Prediction	ab initio - rosetta@home, abalone, Bhageerath
	comparative structure modeling - MODELLER, SWISS-MODEL, RAPTOR, I-TASSER
Gene Function	controlled vocabularies - GeneOntology
	Biochemical pathway databases - Reactome, KEGG
Structure Analysis	Protein-protein docking - RosettaDock, 3D-Dock suite, BIGGER (for more tools, see protein docking software)
	Protein-ligand docking - Affinity, AutoDock, CombiBUILD
Sequence Analysis	sequence assembly - GeneDesign, DNA Baser
	gene finder - BLAST, GeneMark, Glimmer (3)
RNA Structure	Sfold, RNAfold, RNAsoft, Foldalign, Dynalign (4)

(2) Wikipedia:Protein_structure_prediction

(3) For more gene finder programs, click here

(4) Wikipedia:List_of_RNA_structure_prediction_software

- %TEACHINGWEB%.SusanChen - 07 Sep 2009