Project titles for:
Project titles for: 2007-09
- Comparison of software for Analysis of Molecular Marker Data
- In silico Prediction of miRNA in Rice Genome
- Web Tools for Bioinformatics
- In silico Structure Prediction of enzyme Arsenite methyltransferase
- Comparison of various software for QTL Analysis
- QSAR studies of Tuberculosis Inhibitors
- Determination of common transcription factor binding site in promoter region of abiotic stress resistance gene in rice
- SNP Mining in Rice Genome
- Protein Modelling of Betaine Aldehyde Dehydrogenase-2 in Rice
- Data Mining of Chemical Substructures for Biological Efficacy
- Plant Disease Database mined from PubMed
- Comparison of Protein Structure Prediction Methods
- Virtual High Throughput Screening for Influenza Virus Inhibitors
- Combinatorial Libraries for Screening against Tuberculosis Inhibitors
MicroRNAs are one class of newly identified riboregulators of gene expression in many organisms. They vary in their length from 20-25 bases long. They play important roles in multiple biological and metabolic processes. Because of this reason, detection of miRNA and their targets is of great importance in research. Computational prediction of miRNAs and their targets saves a lot of time and money and thus gaining popularity. During the course of present investigation, complete gene sequence set of Oryza sativa were downloaded from NCBI Map Viewer. Using a script developed in Perl, the sequences were scanned for the presence of palindromic sequences, which can form stable stem-loop hairpin like structure. Further filtering was done by predicting secondary structure of the sequences by RNAfold. Structures with very low minimum free energy form the miRNAs, palindromic sequences with MFE lower than a threshold were then filtered. Threshold energy for this experiment was taken as -40Kcal/mol. Also 3 mismatches were allowed while finding the palindromic sequences along with the wobble base pairing, naturally occurring hairpin loops are not exactly symmetrical. After filtering, the sequence sets obtained were considered as potential candidate miRNA sequences. Among the candidate sequences, 71 of the known Oryza sativa miRNA sequences were verified, by aligning them with miRBase. Remaining sequences contained the homologues of known miRNA sequences and can be further studied to verify as a miRNA and to determine the regulatory roles. Two Perl scripts were written dealing with palindrome finding and energy filtering, source code given in Annexure 2 and 3 entitled “HPfinder” and “Filteration code”.