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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] |
Nucleic Acid Secondary Structure
Nucleic acid secondary structure is the basepairing interactions within a single nucleic acid polymer or between two polymers. It can be represented as a list of bases which are paired in a nucleic acid molecule. The secondary structures of biological DNAs and RNAs tend to be different: biological DNA mostly exists as fully base paired double helices, while biological RNA is single stranded and often forms complex and intricate base-pairing interactions due to its increased ability to form hydrogen bonds stemming from the extra hydroxyl group in the ribose sugar. In a non-biological context, secondary structure is a vital consideration in the nucleic acid design of nucleic acid structures for DNA nanotechnology and DNA computing, since the pattern of basepairing ultimately determines the overall structure of the molecules. Fundamental concepts Base pairing In molecular biology, two nucleotides on opposite complementary DNA or RNA strands that are connected via hydrogen b ... [...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] |
Pseudoknot 1YMO
__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 suf ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
RNA Tertiary Structure
Nucleic acid tertiary structure is the Biomolecular structure#Tertiary structure, three-dimensional shape of a nucleic acid polymer. RNA and DNA molecules are capable of diverse functions ranging from molecular recognition to catalysis. Such functions require a precise three-dimensional structure. While such structures are diverse and seemingly complex, they are composed of recurring, easily recognizable tertiary structural motifs that serve as molecular building blocks. Some of the most common motifs for RNA and DNA tertiary structure are described below, but this information is based on a limited number of solved structures. Many more tertiary structural motifs will be revealed as new RNA and DNA molecules are structurally characterized. Helical structures Double helix The double helix is the dominant tertiary structure for biological DNA, and is also a possible structure for RNA. Three DNA conformations are believed to be found in nature, A-DNA, B-DNA, and Z-DNA. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
NP-complete
In computational complexity theory, a problem is NP-complete when: # it is a problem for which the correctness of each solution can be verified quickly (namely, in polynomial time) and a brute-force search algorithm can find a solution by trying all possible solutions. # the problem can be used to simulate every other problem for which we can verify quickly that a solution is correct. In this sense, NP-complete problems are the hardest of the problems to which solutions can be verified quickly. If we could find solutions of some NP-complete problem quickly, we could quickly find the solutions of every other problem to which a given solution can be easily verified. The name "NP-complete" is short for "nondeterministic polynomial-time complete". In this name, "nondeterministic" refers to nondeterministic Turing machines, a way of mathematically formalizing the idea of a brute-force search algorithm. Polynomial time refers to an amount of time that is considered "quick" for a de ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Telomerase RNA Component
Telomerase RNA component, also known as TR, TER or TERC, is an ncRNA found in eukaryotes that is a component of telomerase, the enzyme used to extend telomeres. TERC serves as a template for telomere replication ( reverse transcription) by telomerase. Telomerase RNAs differ greatly in sequence and structure between vertebrates, ciliates and yeasts, but they share a 5' pseudoknot structure close to the template sequence. The vertebrate telomerase RNAs have a 3' H/ACA snoRNA-like domain. Structure TERC is a Long non-coding RNA (lncRNA) ranging in length from ~150nt in ciliates to 400-600nt in vertebrates, and 1,300nt in yeast (Alnafakh). Mature human TERC (hTR) is 451nt in length. TERC has extensive secondary structural features over 4 principal conserved domains. The core domain, the largest domain at the 5’ end of TERC, contains the CUAAC Telomere template sequence. Its secondary structure consists of a large loop containing the template sequence, a P1 loop-closing heli ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
RNase P
Ribonuclease P (, ''RNase P'') is a type of ribonuclease which cleaves RNA. RNase P is unique from other RNases in that it is a ribozyme – a ribonucleic acid that acts as a catalyst in the same way that a protein-based enzyme would. Its function is to cleave off an extra, or precursor, sequence of RNA on tRNA molecules. Further, RNase P is one of two known multiple turnover ribozymes in nature (the other being the ribosome), the discovery of which earned Sidney Altman and Thomas Cech the Nobel Prize in Chemistry in 1989: in the 1970s, Altman discovered the existence of precursor tRNA with flanking sequences and was the first to characterize RNase P and its activity in processing of the 5' leader sequence of precursor tRNA. Recent findings also reveal that RNase P has a new function. It has been shown that human nuclear RNase P is required for the normal and efficient transcription of various small noncoding RNAs, such as tRNA, 5S rRNA, SRP RNA and U6 snRNA genes, which a ... [...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] |
Stochastic Context-free Grammar
Grammar theory to model symbol strings originated from work in computational linguistics aiming to understand the structure of natural languages. Probabilistic context free grammars (PCFGs) have been applied in probabilistic modeling of RNA structures almost 40 years after they were introduced in computational linguistics. PCFGs extend context-free grammars similar to how hidden Markov models extend regular grammars. Each production is assigned a probability. The probability of a derivation (parse) is the product of the probabilities of the productions used in that derivation. These probabilities can be viewed as parameters of the model, and for large problems it is convenient to learn these parameters via machine learning. A probabilistic grammar's validity is constrained by context of its training dataset. PCFGs have application in areas as diverse as natural language processing to the study the structure of RNA molecules and design of programming languages. Designing efficient PC ... [...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] |
