Bioinformatician's den
Arli Aditya Parikesit, Bioinformatics PhD Student at University of Leipzig
     

• Research Interest

Domain Cooccurence Distribution of Genetic Regulation Activation from an Evolutionary Perspective

(This Research is supported by DAAD fellowship).

     
Correlation of the protein domain number. Congruent abundances are obtained from Genscan prediction

The emergence multicellular organisms was facilitated by dramatic increases in the complexity of gene regulatory mechanism. At the level of transcriptional regulation, this can be clearly seen in the massive expansion of transcription factor families and the pervasive combinatorial control of genes by multiple transcription factors in higher organism. One other mechanism is the large and growing class of ~22 nucleotide-long non-coding RNA, known as microRNAs (miRNAs). Crystallography reveals, that the fundamental unit of protein structure is the domain. MiRNAs are of great interest, since translational regulation must have existed in the RNA world before the invention of DNA and transcription respectively. Transcription factors are interesting because all domains of life have at least parts of them and they are involved in many regulatory processes in the cell. The goal of this project is to elucidate how gene regulatory networks evolve and understand the basic principles that underly their evolution. Large-scale studies of the origins and evolution of regulatory mechanisms require quantitative estimates of the abundance and co-occurrence of functional protein domains in the genomes of very diverse organism. Current databases, such as SUPERFAMILY , are not able to provide such quantitative data because of species-specific differences and biases in the existing transcript and protein annotations on which they are based. Our objective is to show, that the combination of de novo gene predictors and subsequent HMM-based annotation of SCOP domains in the predicted peptides leads to consistent estimates with acceptable accuracy.

Selected Publications on this project:

  • Parikesit, Arli A. ;Stadler, Peter F.;Prohaska, Sonja J. 2011. "Evolution and Quantitative Comparison of Genome-Wide Protein Domain Distributions." Genes 2, no. 4: 912-924. [available online]

  • A.A. Parikesit , P. Stadler, and S. Prohaska. 26th German Conference on Bioinformatics 2011. 7-9 September 2011. Weihenstephan. Evolution of domain co-occurrences: some striking results. [available here]

  • Arli A. Parikesit , Peter Stadler & Sonja J. Prohaska. 25th German Conference on Bioinformatics 2010. Braunschweig, September 20th-22nd, 2010. Quantitative Comparison of Genomic-Wide Protein Domain Distributions. GCB2010 conference proceeding. Vol P-173: pp 93-102 [available here]

  • Parikesit, Arli Aditya . Stadler, Peter., Prohaska, Sonja. 2010. Detection of Protein Domains in Eukaryotic Genome Sequences. Proceedings of 5th Brazilian Symposium on Bioinformatics, BSB 2010, Rio de Janeiro, Brazil, August 31--September 3, 2010. Lecture Notes in Bioinformatics, Vol 6268. pp:71-74. [online journal]

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