The recent advent of DNA sequencing technologies facilitates the use of genome sequencing data that provide means for more informative and precise classification and identification of members of the ...Bacteria and Archaea. Because the current species definition is based on the comparison of genome sequences between type and other strains in a given species, building a genome database with correct taxonomic information is of paramount need to enhance our efforts in exploring prokaryotic diversity and discovering novel species as well as for routine identifications. Here we introduce an integrated database, called EzBioCloud, that holds the taxonomic hierarchy of the Bacteria and Archaea, which is represented by quality-controlled 16S rRNA gene and genome sequences. Whole-genome assemblies in the NCBI Assembly Database were screened for low quality and subjected to a composite identification bioinformatics pipeline that employs gene-based searches followed by the calculation of average nucleotide identity. As a result, the database is made of 61 700 species/phylotypes, including 13 132 with validly published names, and 62 362 whole-genome assemblies that were identified taxonomically at the genus, species and subspecies levels. Genomic properties, such as genome size and DNA G+C content, and the occurrence in human microbiome data were calculated for each genus or higher taxa. This united database of taxonomy, 16S rRNA gene and genome sequences, with accompanying bioinformatics tools, should accelerate genome-based classification and identification of members of the Bacteria and Archaea. The database and related search tools are available at www.ezbiocloud.net/.
Average nucleotide identity (ANI) is a category of computational analysis that can be used to define species boundaries of Archaea and Bacteria. Calculating ANI usually involves the fragmentation of ...genome sequences, followed by nucleotide sequence search, alignment, and identity calculation. The original algorithm to calculate ANI used the BLAST program as its search engine. An improved ANI algorithm, called OrthoANI, was developed to accommodate the concept of orthology. Here, we compared four algorithms to compute ANI, namely ANIb (ANI algorithm using BLAST), ANIm (ANI using MUMmer), OrthoANIb (OrthoANI using BLAST) and OrthoANIu (OrthoANI using USEARCH) using >100,000 pairs of genomes with various genome sizes. By comparing values to the ANIb that is considered a standard, OrthoANIb and OrthoANIu exhibited good correlation in the whole range of ANI values. ANIm showed poor correlation for ANI of <90%. ANIm and OrthoANIu runs faster than ANIb by an order of magnitude. When genomes that are larger than 7 Mbp were analysed, the run-times of ANIm and OrthoANIu were shorter than that of ANIb by 53- and 22-fold, respectively. In conclusion, ANI calculation can be greatly sped up by the OrthoANIu method without losing accuracy. A web-service that can be used to calculate OrthoANIu between a pair of genome sequences is available at
http://www.ezbiocloud.net/tools/ani
. For large-scale calculation and integration in bioinformatics pipelines, a standalone JAVA program is available for download at
http://www.ezbiocloud.net/tools/orthoaniu
.
This study describes a systematic approach of TiO
2
/carbon black nanoparticles with respect to the loading amount in order to optimize the catalytic ability of triiodide reduction for dye-sensitized ...solar cells. In particular, the cell using an optimized TiO
2
and carbon black electrode presents an energy conversion efficiency of 7.4% with a 5:1 ratio of a 40-nm TiO
2
to carbon black. Based on the electrochemical analysis, the charge-transfer resistance of the carbon counter electrode changed based on the carbon black powder content. Electrochemical impedance spectroscopy and cyclic voltammetry study show lower resistance compared to the Pt counter electrode. The obtained nanostructures and photo electrochemical study were characterized.
The disruption of the human gut microbiota has been linked to host health conditions, including various diseases. However, no reliable index for measuring and predicting a healthy microbiome is ...currently available. Here, the sequencing data of 1,663 Koreans were obtained from three independent studies. Furthermore, we pooled 3,490 samples from public databases and analyzed a total of 5,153 fecal samples. First, we analyzed Korean gut microbiome covariates to determine the influence of lifestyle on variation in the gut microbiota. Next, patterns of microbiota variations across geographical locations and disease statuses were confirmed using a global cohort and di-sease data. Based on comprehensive comparative analysis, we were able to define three enterotypes among Korean cohorts, namely,
Prevotella
type,
Bacteroides
type, and outlier type. By a thorough categorization of dysbiosis and the evaluation of microbial characteristics using multiple datasets, we identified a wide spectrum of accuracy levels in classifying health and disease states. Using the observed microbiome patterns, we devised an index named the gut microbiome index (GMI) that could consistently predict health conditions from human gut microbiome data. Compared to ecological metrics, the microbial marker index, and machine learning approaches, GMI distinguished between healthy and non-healthy individuals with a higher accuracy across various datasets. Thus, this study proposes a potential index to measure health status of gut microbiome that is verified from multiethnic data of various diseases, and we expect this model to facilitate further clinical application of gut microbiota data in future.
Studies of the interaction between hydrogen and graphene have been increasingly required due to the indispensable modulation of the electronic structure of graphene for device applications and the ...possibility of using graphene as a hydrogen storage material. Here, we report on the behaviour of molecular hydrogen on graphene using the gate voltage-dependent resistance of single-, bi-, and multi-layer graphene sheets as a function of H₂ gas pressure up to 24 bar from 300 K to 345 K. Upon H₂ exposure, the charge neutrality point shifts toward the negative gate voltage region, indicating n-type doping, and distinct Raman signature changes, increases in the interlayer distance of multi-layer graphene, and a decrease in the d-spacing occur, as determined by TEM. These results demonstrate the occurrence of dissociative H₂ adsorption due to the existence of vacancy defects on graphene.
Deep learning (DL)-based recommendation models play an important role in many real-world applications. However, an embedding layer, which is a key part of the DL-based recommendation models, requires ...sparse memory accesses to a very large memory space followed by the pooling operations (i.e., reduction operations). It makes the system overprovision memory capacity for model deployment. Moreover, with conventional CPU-based architecture, it is difficult to exploit the locality, causing a huge burden for data transfer between the CPU and memory. To resolve this problem, we propose an embedding vector element quantization and compression method to reduce the memory footprint (capacity) required by the embedding tables. In addition, to reduce the amount of data transfer and memory access, we propose near-memory acceleration hardware with an SRAM buffer that stores the frequently accessed embedding vectors. Our quantization and compression method results in compression ratios of 3.95-4.14 for embedding tables in widely used datasets while negligibly affecting the inference accuracy. Our acceleration technique with 3D stacked DRAM memories, which facilitates the near-memory processing in the logic die with high DRAM bandwidth, leads to 4.9×-5.4× embedding layer speedup as compared to the 8-core CPU-based execution while reducing the memory energy consumption by 5.9×-12.1×, on average.
We report the fabrication of silicon/carbon core/shell nanowire arrays using a two-step process, involving electroless metal deposition and chemical vapor deposition. In general, foreign shell ...materials that sheath core materials change the inherent characteristics of the core materials. The carbon coating functionalized the silicon nanowire arrays, which subsequently showed electrocatalytic activities for the reduction of iodide/triiodide. This was verified by cyclic voltammetry and electrochemical impedance spectroscopy. We employed the carbon-coated silicon nanowire arrays in dye-sensitized solar cells as counter electrodes. We optimized the carbon shells to maximize the photovoltaic performance of the resulting devices, and subsequently, a peak power conversion efficiency of 9.22% was achieved.
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