Ashok Reddy DINASARAPU
(Curriculum vitae) E-mail: firstname.lastname@example.orgMobile: +91 - 9849851374Office: +91- 40 - 23134668 C/o Prof. C. K. MitraDepartment of BiochemistryUniversity of HyderabadHyderabad-500 046, India
· Seeking a postdoctoral position with an organization that provides ample opportunities to learn and to contribute in the field of Computational Molecular / Evolutionary / Systems biology.
· Computational Molecular Biology · Evolutionary / Systems Biology
· University of Hyderabad, Hyderabad, India 2006 Ph.D., Biochemistry (submitted in October 2006) · Anna University, Chennai, India 2002 M.Tech., Biotechnology · University of Hyderabad, Hyderabad, India 2000 M.Sc., Biochemistry · Andhra Loyola College, Vijayawada, India 1997 B.Sc., Chemistry and Biology
· D Ashok Reddy, B V L S Prasad and Chanchal K Mitra. (2006) Comparative analysis of core promoter region: Information content from mono and dinucleotide substitution matrices. Computational Biology and Chemistry, 30, 58-62. · D Ashok Reddy, B V L S Prasad and Chanchal K Mitra. (2006) Functional classification of transcription factor binding sites: Information content as a metric. Journal of Integrative Bioinformatics, 3(1), 0020. · D Ashok Reddy and Chanchal K Mitra. (2006) Comparative analysis of transcription start site using mutual information. Genomics, Proteomics & Bioinformatics. 4(3), 183-195. · D Ashok Reddy Analysis of TATA+/- core promoters: the importance of plant promoter elements in transcription initiation. (Under preparation). · Prasanta K. Panigrahi, D Ashok Reddy, C Novodaya K. Reddy, Chanchal K. Mitra. Correlation, Base Cooperativity and pattern Identification in genome through Wavelets. (Under preparation)
· C / C++ and MySQL (LINUX). (The above work is done by developing a software in C++)
· Computational analysis of gene regulatory elements using mutual information (PhD thesis) · Molecular modeling studies on binding of fluorescent molecule with antibody molecule by using CERIUS-II software. · Analysis of genome sequences using wavelet transforms. Visiting student, Physical Research Laboratory, Ahmedabad, India. (31/8/2004 to 27/9/2004). · Identification of Wolbachia bacteria in patients with Bancroftian Filariasis by Polymerase Chain Reaction (PCR). (One full semester, M.Tech thesis). · Expression and Production of Filarial Recombinant Protein WbSXP. (M.Tech course work-Industrial training, 2 months).
· Gene construction, expression (Worked as a research associate in Monoclonal antibody division (6 months), Shantha Biotechnics Pvt. Ltd. Medchal, Hyderabad, India).
· Biochemical and molecular biological techniques (PCR, gene cloning and expression and Protein purification)
International Conferences / Poster presentation
· International conference on statistics and informatics in agricultural research. 27-30 December 2006. New Delhi, India. (Oral presentation) · International workshop on Systems Biology 2006, Hamilton Institute, National University of Ireland Maynooth, Ireland (17-19 July, 2006). · Wavelet and multifractal analysis 2004 summer school, Cargese, Corsica, France (19-31 July, 2004). · 5th ADNAT Convention on Perspectives in Genome Analysis, Center for Cellular and Molecular Biology, Hyderabad, India (23-24 February, 2001).
The different approaches (statistical/experimental) of systems biological study of gene regulatory network would be an interesting task for me. For a particular gene to be expressed, the promoter requires binding of cell/tissue specific proteins. The total or type of proteins required might vary depending on the situation (physical or physiological conditions or requirements) of the organism. This shows that the information needed to have a particular type or number of proteins is in the sequence of DNA itself and the interaction between protein-DNA, protein-protein. Once we know the nature of these regulatory elements, we can know the type of protein that is going to bind to a particular DNA binding site at particular physiological requirements. The computational knowledge of gene regulation will give a way of experimental approach to find a solution. By analyzing these individual elements within the promoter sites will enhance our understanding of promoter strength and regulation, thus increasing our understanding of gene expression. Another task is to correlate the regulatory elements involved transcriptional and post-transcription regulation at DNA sequence level. The ultimate goal is to create a detailed model of gene regulation.
Analysis of gene regulatory elements using mutual information
The present study involves three parts. First, we have studied the core promoter region in five sets (E.coli, Plants, Drosophila, Human and Mouse) of promoter sequences by calculating the average mutual information content. Here we have studied substitution matrices (both neighbor independent and neighbor dependent) for the core promoter region and calculated the information content from these substitution matrices to study the TSS-region, TATA-box, and downstream region. Neighbor independent substitutions will give 4×4 matrix and lack any preferences in other words, adjacent bases are considered independent. Next we see the formulae for the base pairs taken together, which correspond to a nearest neighbor preference. As we are considering a pair, there will be 16×16 matrix. These matrices include adjacent pair preferences explicitly. The results show that the TSS-region is likely to be 5-10 bases in size. We also notice that both in the case of mouse and humans, both TATA-box and TSS-region are likely to play important roles. However, in case of plant, the results showed the importance of TSS-region for transcriptional initiation compared to the TATA-box. Second, we also analyze the mitochondrial genome sequences for the transcription start sites with the information content. In this study, we concluded that the presence of short-range correlations within the TSS region is species dependent and is not universal. We further noticed that there are other variable regions in the mitochondrial control element apart from the TSS. The information content of the mitochondrial genome near the control element computed as a 5-nucleotide overlapping block. We also observed that effective comparisons can only be made on the blocks and single nucleotide comparisons does not give us any detectable signals. These results imply a similar regulatory structure in almost all organisms and have been conserved during evolution due to functional constraints. We know that there are well-established tools to locate conserved regions in DNA but looking for variability is also important. So we have found that information content may be useful to study the variable functional regions in genome in an efficient manner. Third, we present a new way of clustering to classify TFBS. The clustering of TFBS (JASPAR database) with information content suggests that any one of TF can bind to the any one of the corresponding clustered TFBS-class. Thus in JASPAR database, out of the 41 TFBS (in humans), perhaps only 5-10 TFs may be actually needed and in case of mouse instead of 13 TFs, there are approximately 5 TFs are needed for gene regulation. The experimental data of TFs of specific gene expression from Transcription Regulatory Regions Database (TRRD) also coincides with our computational results. This gives us a new way to look at the protein classification-not based on their structure or function of TFs but by the nature of their TFBS.
Identification of Wolbachia bacteria in patients with Bancroftian filariasis by Polymerase Chain Reaction
Wolbachia is an obligatory bacterium belongs to a2 sub-class of proteobacteria, gram-negative, and known to infect many arthropods and nematodes. Wolbachia have been detected in majority of filarial parasites studied so far, with electron microscopy, Immunohistology and PCR, have confirmed their presence. The presence of large number of endosymbionts throughout all stages of the pathogenic filariae of humans suggest, that the host will be exposed to wolbachia following death of the parasite or through the release of bacterial products. A simple, reproducible and very rapid protocol for extracting genomic DNA from patient’s whole blood and also from dried blood strips by slightly modified protocols of high salt method. Though high salt method did not yield pure DNA yet quality was good enough to carryout the PCR. PCR is a sensitive technique for identification of specific genes from extracted DNA sample. The study involved the screening for the homologue of HSP60/GroEL gene using gene specific primers. Most of the chronic pathology (CP) patients have demonstrated the presence of wolbachia products in their blood. This may be due to the adult worms which are dead in the lymphatics could have released the bacteria in to the human host. This study showed the patients with CP, which were positive for wolbachia are exhibiting significantly high levels of Brugia malayi aduly antigen apecific IgG1 antibodies, when compared to microfilaraemics (MF) and endemic normals (EN). Since IgG1 has long known to be involved in inflammatory responses and is known to be present in the CP individuals who exhibit damaged lymphatics with proof of adult worms blocking their lymphatic system
Chanchal K. Mitra, Ph.DDept. of BiochemistryUniversity of HyderabadHyderabad – 500 046, IndiaE-mail: email@example.com Prasantha K. Panigrahi, Ph.DQuantum Optics & Quantum Information Division Physical Research Laboratory (PRL)Ahmedabad - 380 009, IndiaE-mail: firstname.lastname@example.org B. V. L. S. Prasad, Ph.DHelix Genomics Pvt. LtdHabsiguda, UppalHyderabad-500007, India.E-mail: email@example.com