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Nussinov Algorithm
The Nussinov algorithm is a nucleic acid structure prediction algorithm used in computational biology to predict the folding of an RNA molecule that makes use of dynamic programming principles. The algorithm was developed by Ruth Nussinov in the late 1970s. Background RNA origami RNA origami is the nanoscale folding of RNA, enabling the RNA to create particular shapes to organize these molecules. It is a new method that was developed by researchers from Aarhus University and California Institute of Technology. RNA origami ... occurs when an RNA molecule "folds" and binds to itself. This folding often determines the function of the RNA molecule. RNA folds at different levels, this algorithm predicts the secondary structure of the RNA. Algorithm Scoring We score a solution by counting the total number of paired bases. Thus, attempting to maximize the score that maximizes the total number of bonds between bases. Motivation Consider an RNA sequence S whose elements are t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Nucleic Acid Structure Prediction
Nucleic acid structure prediction is a computational method to determine ''secondary'' and ''tertiary'' nucleic acid structure from its sequence. Secondary structure can be predicted from one or several nucleic acid sequences. Tertiary structure can be predicted from the sequence, or by comparative modeling (when the structure of a homologous sequence is known). The problem of predicting nucleic acid secondary structure is dependent mainly on base pairing and base stacking interactions; many molecules have several possible three-dimensional structures, so predicting these structures remains out of reach unless obvious sequence and functional similarity to a known class of nucleic acid molecules, such as transfer RNA (tRNA) or microRNA (miRNA), is observed. Many secondary structure prediction methods rely on variations of dynamic programming and therefore are unable to efficiently identify pseudoknots. While the methods are similar, there are slight differences in the approaches ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computational Biology
Computational biology refers to the use of data analysis, mathematical modeling and computational simulations to understand biological systems and relationships. An intersection of computer science, biology, and big data, the field also has foundations in applied mathematics, chemistry, and genetics. It differs from biological computing, a subfield of computer engineering which uses bioengineering to build computers. History Bioinformatics, the analysis of informatics processes in biological systems, began in the early 1970s. At this time, research in artificial intelligence was using network models of the human brain in order to generate new algorithms. This use of biological data pushed biological researchers to use computers to evaluate and compare large data sets in their own field. By 1982, researchers shared information via punch cards. The amount of data grew exponentially by the end of the 1980s, requiring new computational methods for quickly interpreting ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dynamic Programming
Dynamic programming is both a mathematical optimization method and a computer programming method. The method was developed by Richard Bellman in the 1950s and has found applications in numerous fields, from aerospace engineering to economics. In both contexts it refers to simplifying a complicated problem by breaking it down into simpler sub-problems in a recursive manner. While some decision problems cannot be taken apart this way, decisions that span several points in time do often break apart recursively. Likewise, in computer science, if a problem can be solved optimally by breaking it into sub-problems and then recursively finding the optimal solutions to the sub-problems, then it is said to have ''optimal substructure''. If sub-problems can be nested recursively inside larger problems, so that dynamic programming methods are applicable, then there is a relation between the value of the larger problem and the values of the sub-problems.Cormen, T. H.; Leiserson, C. E.; Rives ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ruth Nussinov
Ruth Nussinov (Hebrew: פרופסור רות נוסינוב) is an Israeli-American biologist who works as a Professor in the Department of Human Genetics, School of Medicine at Tel Aviv University and is the Senior Principal Scientist and Principal Investigator at the National Cancer Institute, National Institutes of Health. Nussinov is also the Editor in Chief for the journal '' PLOS Computational Biology''. Nussinov proposed the first dynamic programming approach for nucleic acid secondary structure prediction, this method is now known as the Nussinov algorithm. Career Ruth Nussinov received her B.Sc in Microbiology from University of Washington in 1966, her M.Sc in Biochemistry from Rutgers University in 1967 and her Ph.D. in Biochemistry from Rutgers in 1977. Her thesis was titled ''Secondary structure analysis of nucleic acids''. She was a fellow at the Weizmann Institute and worked as a visiting scientist at Berkeley and at Harvard. She took a position at Tel Aviv Univ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
RNA Origami
RNA origami is the nanoscale folding of RNA, enabling the RNA to create particular shapes to organize these molecules. It is a new method that was developed by researchers from Aarhus University and California Institute of Technology. RNA origami is synthesized by enzymes that fold RNA into particular shapes. The folding of the RNA occurs in living cells under natural conditions. RNA origami is represented as a DNA gene, which within cells can be transcribed into RNA by RNA polymerase. Many computer algorithms are present to help with RNA folding, but none can fully predict the folding of RNA of a singular sequence. Overview In nucleic acids nanotechnology, artificial nucleic acids are designed to form molecular components that can self-assemble into stable structures for use ranging from targeted drug delivery to programmable biomaterials. DNA nanotechnology uses DNA motifs to build target shapes and arrangements. It has been used in a variety of situations, including nan ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Pseudoknot
__NOTOC__ A pseudoknot is a nucleic acid secondary structure containing at least two stem-loop structures in which half of one stem is intercalated between the two halves of another stem. The pseudoknot was first recognized in the turnip yellow mosaic virus in 1982. Pseudoknots fold into knot-shaped three-dimensional conformations but are not true topological knots. Prediction and identification The structural configuration of pseudoknots does not lend itself well to bio-computational detection due to its context-sensitivity or "overlapping" nature. The base pairing in pseudoknots is not well nested; that is, base pairs occur that "overlap" one another in sequence position. This makes the presence of pseudoknots in RNA sequences more difficult to predict by the standard method of dynamic programming, which use a recursive scoring system to identify paired stems and consequently, most cannot detect non-nested base pairs. The newer method of stochastic context-free grammars su ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stem Loop
Stem-loop intramolecular base pairing is a pattern that can occur in single-stranded RNA. The structure is also known as a hairpin or hairpin loop. It occurs when two regions of the same strand, usually complementary in nucleotide sequence when read in opposite directions, base-pair to form a double helix that ends in an unpaired loop. The resulting structure is a key building block of many RNA secondary structures. As an important secondary structure of RNA, it can direct RNA folding, protect structural stability for messenger RNA (mRNA), provide recognition sites for RNA binding proteins, and serve as a substrate for enzymatic reactions. Formation and stability The formation of a stem-loop structure is dependent on the stability of the resulting helix and loop regions. The first prerequisite is the presence of a sequence that can fold back on itself to form a paired double helix. The stability of this helix is determined by its length, the number of mismatches or bulges it co ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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