RNABP COGEST: a resource for investigating functional RNAs
| Autor: | Sukanya Halder, Sohini Bhattacharya, Antarip Halder, S P Preethi, Abhijit Mitra, Purshotam Sharma, Rahul Paul, Shriyaa Mittal, Swati Panigrahi, Dhananjay Bhattacharyya |
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| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Genetics
Regulation of gene expression RNA Stability RNA Untranslated Base pair Stability (learning theory) RNA Computational Biology Computational biology Biology Non-coding RNA General Biochemistry Genetics and Molecular Biology Structural bioinformatics Nucleic Acid Conformation Original Article General Agricultural and Biological Sciences Databases Nucleic Acid Quantum Information Systems |
| Zdroj: | Database: The Journal of Biological Databases and Curation |
| ISSN: | 1758-0463 |
| Popis: | Structural bioinformatics of RNA has evolved mainly in response to the rapidly accumulating evidence that non-(protein)-coding RNAs (ncRNAs) play critical roles in gene regulation and development. The structures and functions of most ncRNAs are however still unknown. Most of the available RNA structural databases rely heavily on known 3D structures, and contextually correlate base pairing geometry with actual 3D RNA structures. None of the databases provide any direct information about stabilization energies. However, the intrinsic interaction energies of constituent base pairs can provide significant insights into their roles in the overall dynamics of RNA motifs and structures. Quantum mechanical (QM) computations provide the only approach toward their accurate quantification and characterization. ‘RNA Base Pair Count, Geometry and Stability’ (http://bioinf.iiit.ac.in/RNABPCOGEST) brings together information, extracted from literature data, regarding occurrence frequency, experimental and quantum chemically optimized geometries, and computed interaction energies, for non-canonical base pairs observed in a non-redundant dataset of functional RNA structures. The database is designed to enable the QM community, on the one hand, to identify appropriate biologically relevant model systems and also enable the biology community to easily sift through diverse computational results to gain theoretical insights which could promote hypothesis driven biological research. Database URL: http://bioinf.iiit.ac.in/RNABPCOGEST |
| Databáze: | OpenAIRE |
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