Homework1
Question 2.
- Methods developed by computational biology can serve to test hypothesis and to model behavior that is predicted by scientists working in synthetic biology. For example, to test one of the relevant complicated biological pathways that supposedly occurs in human body but was derived from some other mammalian.
- Using computational biology, model the optimal conditions for gene expression that was identified by scientists in synthetic biology.
Question 3. Difference between transposon and virus:
| Virus | Transposon |
|---|---|
| is classified as independent class | is a part of genome in spicy |
| can lyse the cell by secreting certain compounds | |
| change hosts | more often stay in the same home host genome |
| similar to retroviruses by the way they transpose, but not to the other majority of viruses | |
| Technological Application | |
| vaccination | knocking-out a gene |
| Limitations of the Applications | |
| the modified virus can become invasive and cause another strain of the same disease | might insert itself in some other place in genome, might not stay in one place |
Question 5.
- protein structure prediction - the prediction is based on the lower energy state obtained by the protein when folding
- Ab initio protein structure prediction software - this method seeks to predict protein structure from scratch, is not based on the previously solved structures, thus, it is most effective in predicting short sequence peptide folding (computational resources: Blue Gene, the Human Genome Folding Project, etc.)
- Comparative protein structure modeling software - this process is based on the previously solved structures (which constitute about 3% of the total number) however, there are only about 2000 protein folds known to occur in nature, and this method assumes that homologous proteins have similar structure, and the scan is performed through the database of proteins looking for the similar primary protein structure (computational resources: CABS, PSI-BLAST, etc.)
- gene function - is a collaborative bioinformatics database of the specific functions of identified genes, together with their chromosomal location.
- Controlled vocabularies for gene/enzyme function (e.g. "EC numbers" or the "Gene Ontology") - gathers information from different sources and makes sure that different names which are the same terms will represent the same entities in all occasions of use; GO - gene and gene annotation vocabularies for shared use in the different domains of biology (EpoDB).
- Biochemical pathway databases - databases with related genes, enzymes and metabolites; can be used for prediction of other pathways with similar parts(BioPath, SWISS)
- structure analysis - prediction of secondary and tertiary structure of a protein, and its function based on 3D structure
- Protein/protein docking software - predicts nature of interaction, spartial configuration, strength and specificity of interacting proteins based on their known 3D structure (GRAMM-X)
- Protein/small-molecule docking software - predicts affinity and orientation binding between protein and small molecule, based on known 3D structure of both (Monte Carlo Method)
- sequence analysis - automated examination of characteristical fragments for DNA and peptides
- Sequence assembly software - sequencing of the same gene or fragment many times in order to determine polymorphism (STARS).
- Gene-finding software - finding genes in DNA, identifies coding regions and distinguish them from non-coding ones (Glimmer).
- RNA structure - RNA functional structure
- RNA folding software - most of this algorithm predict only secondary structure (Mfold)
- RNA design software - software designs an RNA sequence that folds to a given input secondary structure(siDirect)
http://biowiki.org/edit/Fall08/NinaHomeWork1?time=035658
http://www.cbil.upenn.edu/EpoDB/release/version_2.2/controlled.vocab.html
http://accelrys.com/industry/pharma-biotech/target-identification/protein-docking.html
http://www.rnasoft.ca/
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