A quantitative analysis of secondary RNA structure using domination based parameters on trees.
A quantitative analysis of secondary RNA structure using domination based parameters on trees.
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DOI：
10.1186/1471-2105-7-108
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发表时间：
2006-03-03
影响因子：
3
通讯作者：
Zou, Y
中科院分区：
文献类型：
--
作者：
Haynes, T;Knisley, D;Seier, E;Zou, Y
为了实现基因组学和蛋白质组学研究的新目标，一个全面的RNA基序数据库是必不可少的，这一点越来越明显。二级RNA结构经常被各种建模方法表示为图论树。使用图论作为建模工具，可以利用大量的图形不变量资源来数字识别次级RNA基序。图的支配数是一个图形不变量，它对树结构的微小变化都很敏感。本研究选取的不变量是图的支配数的变化。将这些图形不变量划分为两个类，并根据每个类定义两个参数。对所有小阶树计算这些参数，并对结果数据进行统计分析，以确定是否可以利用这些参数的值来识别哪些7阶和8阶树在结构上是rna样的。统计分析表明，基于支配的参数正确区分了代表天然结构的树和那些不太可能代表RNA的树。一些先前被确定为候选结构的树被发现“非常”像RNA，而另一些则不是，从而细化了可能被发现代表次级RNA结构的结构空间。搜索算法是可用的，以挖掘核苷酸序列数据库。然而，识别的基序数量可能相当大，使得进一步搜索相似基序的计算困难。生物信息学领域的大部分工作都是为了开发更好的算法来解决计算问题。另一方面，这项工作使用数学描述符更清楚地表征RNA基序，从而减少相应的搜索空间。这些初步发现表明，在计算机网络设计等领域中使用的图论量词作为基因组学和蛋白质组学的附加工具具有重要的前景。
It has become increasingly apparent that a comprehensive database of RNA motifs is essential in order to achieve new goals in genomic and proteomic research. Secondary RNA structures have frequently been represented by various modeling methods as graph-theoretic trees. Using graph theory as a modeling tool allows the vast resources of graphical invariants to be utilized to numerically identify secondary RNA motifs. The domination number of a graph is a graphical invariant that is sensitive to even a slight change in the structure of a tree. The invariants selected in this study are variations of the domination number of a graph. These graphical invariants are partitioned into two classes, and we define two parameters based on each of these classes. These parameters are calculated for all small order trees and a statistical analysis of the resulting data is conducted to determine if the values of these parameters can be utilized to identify which trees of orders seven and eight are RNA-like in structure. The statistical analysis shows that the domination based parameters correctly distinguish between the trees that represent native structures and those that are not likely candidates to represent RNA. Some of the trees previously identified as candidate structures are found to be "very" RNA like, while others are not, thereby refining the space of structures likely to be found as representing secondary RNA structure. Search algorithms are available that mine nucleotide sequence databases. However, the number of motifs identified can be quite large, making a further search for similar motif computationally difficult. Much of the work in the bioinformatics arena is toward the development of better algorithms to address the computational problem. This work, on the other hand, uses mathematical descriptors to more clearly characterize the RNA motifs and thereby reduce the corresponding search space. These preliminary findings demonstrate that graph-theoretic quantifiers utilized in fields such as computer network design hold significant promise as an added tool for genomics and proteomics.
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影响因子：
5.6
作者：
Kanna, N;Vishveshwara, S
通讯作者：
Vishveshwara, S
影响因子：
5.6
作者：
Samudrala, R;Moult, J
通讯作者：
Moult, J
影响因子：
0.5
作者：
Hartuv, E;Shamir, R
通讯作者：
Shamir, R
DOI：
10.1016/0010-4809(89)90039-6
发表时间：
1989-10-01
期刊：
COMPUTERS AND BIOMEDICAL RESEARCH
影响因子：
--
作者：
LE, SY;NUSSINOV, R;MAIZEL, JV
通讯作者：
MAIZEL, JV
影响因子：
5.8
作者：
Gan, HH;Fera, D;Schlick, T
通讯作者：
Schlick, T