Do a research on gene RASA1.  Read the instruction to know what is required

Introduction

Your final project will center around the gene that you chose, and use bioinformatics tools to study these genes. Your theme of the final paper is exactly the same as the course: use bioinformatics to add biological knowledge.

Outline of your paper:

1. Introduce the biology of your gene/protein. You can discuss genetics, evolution and conservation, intron-exon structure, splice variants, and isoforms, phenotypes (if known) such as human diseases or developmental defects, and the biochemical protein function (receptor, kinase, signaling molecule, motor protein, etc). This information will come from NCBI Books, OMIM, review papers, and primary research literature. Be sure to cite and reference your sources just like in any other university course.

2. The core of the paper is your bioinformatic analysis of these genes. You need to include the following:

(a) BLAST to find orthologs and paralogs. Discuss the evolutionary history of your gene/protein.

(b) Do a T-COFFEE/MUSCLE/MAFFT/CLUSTAL/etc multiple global alignment over homologues, and analyze the results.

(c) Analyze the conserved domains in your protein (CDD, SMART).

(d) Produce a phylogenetic tree of homologues, including an outgroup. Analyze the resulting phylogeny.

(e) Study the three-dimensional protein domain structure based on existing crystal structures (in PDB) and/or homology modeling (Phyre). If there are known important mutations in that domain (e.g., from OMIM), show those loci in the figure. Similarly, if there are some highly conserved loci in that protein, definitely show them in the figure.

(f) Analyze microarray data and protein-protein interaction networks.

Feel free to use and include additional bioinformatics tools you find on your own.
For these analyses, fully document how you performed the analysis. For example, include the following for each type of analysis:
- Web site and tool used to perform the analysis
- Parameter settings, for example, BLAST algorithm, database, substitution matrix, etc.

3. Finally, and most importantly, explain how your bioinformatic results add biological
knowledge to the story. Be sure to address uncertainties such as incorrectly inferring homology from sequence similarity, and how a follow-up study could increase the strength of your evidence.

4. References.

5. Bioinformatics tool outputs. Put text and images from bioinformatics tools here.

Attachment:- Outline and sample.rar