RNA Secondary Structures Forecast Base On Malkov Train

The research of RNA structure and function is now a very important topic for bioinformatics. and currently already obtained the enormous development to the RNA own function understanding and the study of it is also allowed to take in the research protein structure and the function as well as the DNA sequences the gene information breach..As the same with the protein, all kinds of function of RNA is tight connected with its specific structure, in order to further excavates,explores its multitudinous function. It is need to with the help of some secondarystructure, even tertiary structure. As regards of many non-coding RNA or structure RNA, its structure hidebound nature must be more than it in the sequence.Makes clear their concrete structure, not only can carefully understand each kind of RNA in the cell operation mechanism, but also may seek the new gene in the gene group.And it is also provides the help for enhance the accuracy of forecast protein structure. it is very difficult to determined the spatial structure of RNA molecule through x-ray crystal diffraction and the nuclear magnetic resonance (NMR) experiment method and so on, because RNA molecule is degeneration speed quickly and it is difficult to crystallize.Although the result obtained is quite precise and reliable, but facing the current magnanimous biological sequence, this method obviously cannot follow the request .Therefore, as the same with the protein structure research, with the help of to the computer and each mathematics technology forecast the spatial structure of RNA is a short cut to enhance knows of the RNA spatial structure efficiency a shortcut, also is the main dependence method.A very important method in bioinformatics study research is establishes the mathematical model, according to the biology data characteristic, in each kind of analysis data software at present, it is always use the Markov model, it is widely used in the database search, the sequence comparison, the protein prime field model establishment as well as the new gene search work, and has obtained the remarkable achievement.This article is about to apply Markov chain forecasting model to RNA secondary sequences treating processes, using Markov chain predicting model to induce some RNA sequence, it is not only enhanced the RNA predicting accuracy, but also keep the Markov nature, has achieved a quite ideal RNA level of sequences predicting result.The text bases a lot of RNA secondary structures forecast of arithmetic, comparative sequence analysis (pylogenetic methods), dynamic programming methods, combinatorial algorithms,some of intellectualized heuristicalgorithms (such as: the genetic algorithms, the neural network algorithms, the Monte Carlo sampling algorithms ect..). They are each to have a characteristics,these thoughts produced prominent influence toward bioinformatics development. When RNA secondary structure forecast, also can use of dynamic programming methods, Monte Carlo sampling algorithms, simulate- anneal methods etc.. we are not depiction.The text bring forward a new RNA secondary structures forecast of arithmetic bases on malkov train, this is simple mathematics forecast arithmetic. Order use of simple mathematics forecast arithmetic aim at RNA stair sequence to analyzed, validate else RNA secondary structures forecast of arithmetic, and aim at RNA mathematics character to analyzed, look for affiliation in sequence.The arithmetic of characteristic is think of a cover four elements of sequence toward a stair sequence. Compute its transition matrix, bases on the transition matrix, gain one or lot sequence accord with matrix, the sequence had build bases on the element of tag connection. For it has characteristic of stair sequence, and has characteristic of secondary structures. Then every elements of characteristic to rewrite, we use bracket polt.We use the sequence and know sequence structures compare, we discover the sequence can embodiment mostly base pair in structures, prove the arithmetic is usable, prove RNA sequences of component has associate. And mostly elements in the sequence infection secondary structures bring.The arithmetic has lack. When compute sequence of transition matrix, barely take into account one time step matrix, no take into account next. When pair, use of most length distance of route. And no take into account pseudo knots.