37498905
Discovering Common Structural Motifs of Ribosomal Rna Secondary Structures in Prokaryotes
Certain structural motifs, like tetra-loops, in ribosomal RNA are known to functionally implicate in virtually every aspect of protein synthesis. Ribosomal RNA molecules were also widely used as a tool in molecular evolutionary studies because of their ubiquity, size and low evolutionary rate. In this study, we adapt a data mining approach to discover common structural motifs, and then we use a machine learning approach to identify discriminating CSMs from groups of organisms. Finally, we construct phylogeneitc trees to investigate the evolution of ribosomal RNA by serving the CSMs discovered as targets, which are used to estimate the evolutionary relatedness between organisms. The aim of this study is to discover common structural motifs (CSMs), i.e., those single-strain regions shared in ribosomal RNA secondary structures by several organisms, which are related to specific domains or functions. We discover a set of common structural motifs from several data sets of Archaea and Bacteria. Significant CSMs are then induced by a decision tree. Furthermore, phylogenetic trees are constructed based on CSMs and primary sequences of SSU 16 S ribosomal RNA.
31128018
The Repetitive Sequence Database and Mining Putative Regulatory Elements in Gene Promoter Regions
At least 43% of the human genome is occupied by repetitive elements. Moreover, around 51% of the rice genome is occupied by repetitive elements. The analysis of repetitive elements reveals that repetitive elements in our genome may have been very important in the evolutionary genomics. The first part of this study is to describe a database of repetitive elements - RSDB. The RSDB database contains repetitive elements, which are classified into the following categories: exact, tandem, and similar. The interfaces needed to query and show the results and statistical data, such as the relationship between repetitive elements and genes, cross-references of repetitive elements among different organisms, and so on, are provided. The second part of this study then attempts to mine the putative binding site for information on how combinations of the known regulatory sites and overrepresented repetitive elements in RSDB are distributed in the promoter regions of groups of functionally related genes. The overrepresented repetitive elements appearing in the associations are possible transcription factor binding sites. Our proposed approach is applied to Saccharomyces cerevisiae and the promoter regions of Yeast ORFs. The complete contents of RSDB and partial putative binding sites are available to the public at www.rsdb.csie.ncu.edu.tw. The readers may download partial query results.
31598462
A computationally efficient method for nonlinear mixed-effects models with nonignorable missing data in time-varying covariates
Nonlinear mixed-effects (NLME) models are widely used for longitudinal data analyses. Time-dependent covariates are often introduced to partially explain inter-individual variation. These covariates often have missing data, and the missingness may be nonignorable. Likelihood inference for NLME models with nonignorable missing data in time-varying covariates can be computationally very intensive and may even offer computational difficulties such as nonconvergence. We propose a computationally very efficient method for approximate likelihood inference. The method is illustrated using a real data example.
16119407
Supporting Web Collaboration for Cooperative Software Development
With the rapid growth of web technology, more and more software development projects use web collaborations to facilitate the development process. However, web collaboration activity is a complex orchestration. It involves many people work together without the barrier of time and space difference. Therefore, how to efficiently monitor and control web collaboration activity becomes a critical issue in a web-based collaborative software development project. In this paper, we present a novel approach to tackle this difficult problem by means of monitoring collaboration task progress. In addition, we also provide solutions to automate the dynamic control of cooperation, thus to improve the web collaboration performance.
15154017
Coping with legacy system migration complexity
During the last three decades, a considerable amount of software has been developed based on obsolete technologies (such as using procedural languages). This type of systems has undergone severe code revisions during a long time period. As a consequence, the high level of entropy combined with imprecise documentation about the design and architecture make the maintenance more difficult, time consuming, and costly. On the other hand, these systems have important economical value; many of them are crucial to their owners (Bennett, 1995). For the high cost of lost former investment and business knowledge that embedded in those systems, in many cases, simply abandon legacy systems and re-develop new systems based on new technology is not the choice. Migrating legacy system toward new emerging technology is an appropriate solution. However, migrating legacy system towards new technology is a complex system engineering work. In this paper, we propose a novel approach to reduce the migration complexity. We apply dynamic program analysis, software visualization, knowledge recovery, and divide-and-conquer techniques to cope with the complexity issue in legacy software migration project.