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
Rice is a staple food in much of the world and hence increasing its production is of special interest. Its productivity is severely affected by soil salinity, drought, low and high temperature and other abiotic stress condition. Nucleotide sequence of 80 genes which are responsible for abiotic stress tolerance in rice were retrieved from Map Viewer and ENTREZ nucleotide database of NCBI and other rice database. Transcription factor binding sites are the short conserved sequence elements located upstream of the transcriptional start site and act as a binding sites for transcription factors that regulate a group of gene involved in a similar cellular function. Transcription factors could be discovered computationally by local alignment of upstream region from the co-regulated genes. Various methods and algorithms used for finding transcription factor binding sites are Scoring method position specific scoring matrix (PSSM), positon specific probability matrix (PSPM), Expectation maximization algorithm, Gibbs sampling method and genetic algorithm. The goal of predicting transcription factor binding sites is to understand the process of gene regulation of abiotic stress resistance gene. Software commonly used for predicting transcription factor binding site or motifs are MEME, TOUCAN, Matinspector, OSIRIS. The most commonly used software is Matinspector that provide a core similarity value, matrix similarity value of each motif and also provide functional description of each motif family and overlapping motifs present in sequence which are not provided by other software. OSIRIS software is best for rice.