The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (>95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and Starting in the mid-1980s, Carl Woese revolutionized the field of microbiology with his rRNA-based phylogenetic comparisons delineating the three main branches of life (28). Today, rRNA-based analysis remains a central method in microbiology, used not only to explore microbial diversity but also as a day-to-day method for bacterial identification. Identification methods are conceptually easier to interpret than molecular phylogenetic analyses and are often preferred when the groups are well understood. Most rRNA identification (classification) methods, as opposed to phylogenetic (clustering) methods, have been nearest-neighbor-based classification schemes (10, 18; however, see reference 4). In some part, this was due to the lack of a consistent, higher-level bacterial classification structure (taxonomy). Several recent events have helped change this situation. In 2002, an ad hoc committee for the reevaluation of species definition in bacteriology (24) advised that all new bacterial species descriptions include an rRNA sequence from the type strain, and in 2001, Bergey's Trust published a revised higher-order taxonomy attempting to reconcile bacterial taxonomy with rRNA-based phylogeny (12, 13).The naïve Bayesian classification method is simple yet can be extremely efficient. "Naïve" refers to the (naïve) assumption that data attributes are independent. Domingos and Pazzani (11) showed that the Bayesian method can still be optimal even when this attribute independency is violated. The method has also been reported to perform well on problems similar to the classification of sequence data, such as the classification of text documents, that have a high-dimensional feature space and sparse data (16).The Ribosomal Database Project II (RDP) provides data, tools, and services related to rRNA sequences to the rese...

The Ribosomal Database Project (RDP) provides researchers with quality-controlled bacterial and archaeal small subunit rRNA alignments and analysis tools. An improved alignment strategy uses the Infernal secondary structure aware aligner to provide a more consistent higher quality alignment and faster processing of user sequences. Substantial new analysis features include a new Pyrosequencing Pipeline that provides tools to support analysis of ultra high-throughput rRNA sequencing data. This pipeline offers a collection of tools that automate the data processing and simplify the computationally intensive analysis of large sequencing libraries. In addition, a new Taxomatic visualization tool allows rapid visualization of taxonomic inconsistencies and suggests corrections, and a new class Assignment Generator provides instructors with a lesson plan and individualized teaching materials. Details about RDP data and analytical functions can be found at http://rdp.cme.msu.edu/.

Ribosomal Database Project (RDP; http://rdp.cme.msu.edu/) provides the research community with aligned and annotated rRNA gene sequence data, along with tools to allow researchers to analyze their own rRNA gene sequences in the RDP framework. RDP data and tools are utilized in fields as diverse as human health, microbial ecology, environmental microbiology, nucleic acid chemistry, taxonomy and phylogenetics. In addition to aligned and annotated collections of bacterial and archaeal small subunit rRNA genes, RDP now includes a collection of fungal large subunit rRNA genes. RDP tools, including Classifier and Aligner, have been updated to work with this new fungal collection. The use of high-throughput sequencing to characterize environmental microbial populations has exploded in the past several years, and as sequence technologies have improved, the sizes of environmental datasets have increased. With release 11, RDP is providing an expanded set of tools to facilitate analysis of high-throughput data, including both single-stranded and paired-end reads. In addition, most tools are now available as open source packages for download and local use by researchers with high-volume needs or who would like to develop custom analysis pipelines.

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Covalent organic frameworks (COFs) are crystalline porous solids with well-defined two- or three-dimensional molecular structures. Although the structural regularity provides this new type of porous material with high potentials in catalysis, no example has been presented so far. Herein, we report the first application of a new COF material, COF-LZU1, for highly efficient catalysis. The easily prepared imine-linked COF-LZU1 possesses a two-dimensional eclipsed layered-sheet structure, making its incorporation with metal ions feasible. Via a simple post-treatment, a Pd(II)-containing COF, Pd/COF-LZU1, was accordingly synthesized, which showed excellent catalytic activity in catalyzing the Suzuki-Miyaura coupling reaction. The superior utility of Pd/COF-LZU1 in catalysis was elucidated by the broad scope of the reactants and the excellent yields (96-98%) of the reaction products, together with the high stability and easy recyclability of the catalyst. We expect that our approach will further boost research on designing and employing functional COF materials for catalysis.

The Ribosomal Database Project (RDP-II) provides the research community with aligned and annotated rRNA gene sequences, along with analysis services and a phylogenetically consistent taxonomic framework for these data. Updated monthly, these services are made available through the RDP-II website (http://rdp.cme.msu.edu/). RDP-II release 9.21 (August 2004) contains 101 632 bacterial small subunit rRNA gene sequences in aligned and annotated format. High-throughput tools for initial taxonomic placement, identification of related sequences, probe and primer testing, data navigation and subalignment download are provided. The RDP-II email address for questions or comments is rdpstaff@msu.edu.

These data show that apatinib treatment significantly improved OS and PFS with an acceptable safety profile in patients with advanced gastric cancer refractory to two or more lines of prior chemotherapy.

Allotetraploid cotton is an economically important natural-fiber-producing crop worldwide. After polyploidization, Gossypium hirsutum L. evolved to produce a higher fiber yield and to better survive harsh environments than Gossypium barbadense, which produces superior-quality fibers. The global genetic and molecular bases for these interspecies divergences were unknown. Here we report high-quality de novo-assembled genomes for these two cultivated allotetraploid species with pronounced improvement in repetitive-DNA-enriched centromeric regions. Whole-genome comparative analyses revealed that speciesspecific alterations in gene expression, structural variations and expanded gene families were responsible for speciation and the evolutionary history of these species. These findings help to elucidate the evolution of cotton genomes and their domestication history. The information generated not only should enable breeders to improve fiber quality and resilience to ever-changing environmental conditions but also can be translated to other crops for better understanding of their domestication history and use in improvement.