LVTree Viewer: An Interactive Display for the All-Species Living Tree Incorporating Automatic Comparison with Prokaryotic Systematics

نویسندگان

  • Guanghong Zuo
  • Xiaoyang Zhi
  • Zhao Xu
  • Bailin Hao
چکیده

We describe an interactive viewer for the All-Species Living Tree (LVTree). The viewer incorporates treeing and lineage information from the ARB-SILVA website. It allows collapsing the tree branches at different taxonomic ranks and expanding the collapsed branches as well, keeping the overall topology of the tree unchanged. It also enables the user to observe the consequence of trial lineage modifications by re-collapsing the tree. The system reports taxon statistics at all ranks automatically after each collapsing and re-collapsing. These features greatly facilitate the comparison of the 16S rRNA sequence phylogeny with prokaryotic taxonomy in a taxon by taxon manner. In view of the fact that the present prokaryotic systematics is largely based on 16S rRNA sequence analysis, the current viewer may help reveal discrepancies between phylogeny and taxonomy. As an application, we show that in the latest release of LVTree, based on 11,939 rRNA sequences, as few as 24 lineage modifications are enough to bring all but two phyla (Proteobacteria and Firmicutes) to monophyletic clusters.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

On monospecific genera in prokaryotic taxonomy

A monospecific genus contains a single species ever since it was proposed. Though formally more than half of the known prokaryotic genera are monospecific, we pick up those which actually raise taxonomic problems by violating monophyly of the taxon within which it resides. Taking monophyly as a guiding principle, our arguments are based on simultaneous support from 16S rRNA sequence analysis an...

متن کامل

Object-Based Classification of UltraCamD Imagery for Identification of Tree Species in the Mixed Planted Forest

This study is a contribution to assess the high resolution digital aerial imagery for semi-automatic analysis of tree species identification. To maximize the benefit of such data, the object-based classification was conducted in a mixed forest plantation. Two subsets of an UltraCam D image were geometrically corrected using aero-triangulation method. Some appropriate transformations were perfor...

متن کامل

Comparison of Machine Learning Algorithms for Broad Leaf Species Classification Using UAV-RGB Images

Abstract: Knowing the tree species combination of forests provides valuable information for studying the forest’s economic value, fire risk assessment, biodiversity monitoring, and wildlife habitat improvement. Fieldwork is often time-consuming and labor-required, free satellite data are available in coarse resolution and the use of manned aircraft is relatively costly. Recently, unmanned aeria...

متن کامل

CVTree3 Web Server for Whole-genome-based and Alignment-free Prokaryotic Phylogeny and Taxonomy

A faithful phylogeny and an objective taxonomy for prokaryotes should agree with each other and ultimately follow the genome data. With the number of sequenced genomes reaching tens of thousands, both tree inference and detailed comparison with taxonomy are great challenges. We now provide one solution in the latest Release 3.0 of the alignment-free and whole-genome-based web server CVTree3. Th...

متن کامل

Bayes Networks and Fault Tree Analysis Application in Reliability Estimation (Case Study: Automatic Water Sprinkler System)

In this study, the application of Bayes networks and fault tree analysis in reliability estimation have been investigated. Fault tree analysis is one of the most widely used methods for estimating reliability. In recent years, a method called "Bayes Network" has been used, which is a dynamic method, and information about the probable failure of the system components will be updated according to...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره 14  شماره 

صفحات  -

تاریخ انتشار 2016