Abstract
The National Genomics Data Center (NGDC) provides a suite of database resources to support worldwide research activities in both academia and industry. With the rapid advancements in ...higher-throughput and lower-cost sequencing technologies and accordingly the huge volume of multi-omics data generated at exponential scales and rates, NGDC is continually expanding, updating and enriching its core database resources through big data integration and value-added curation. In the past year, efforts for update have been mainly devoted to BioProject, BioSample, GSA, GWH, GVM, NONCODE, LncBook, EWAS Atlas and IC4R. Newly released resources include three human genome databases (PGG.SNV, PGG.Han and CGVD), eLMSG, EWAS Data Hub, GWAS Atlas, iSheep and PADS Arsenal. In addition, four web services, namely, eGPS Cloud, BIG Search, BIG Submission and BIG SSO, have been significantly improved and enhanced. All of these resources along with their services are publicly accessible at https://bigd.big.ac.cn.
With the rapid increase of applications in 5G and Internet of Things, mobile edge computing (MEC) has been proposed to reduce the burden of central cloud and decrease the users request delay by ...deploying edge servers and edge services close to users. Due to resources constraint of edge servers and disadvantage of standalone placement optimization of edge servers or edge services, the discussion focusing on the combining optimization of server placement and service placement has engendered. At present, the placement combination is studied with strict assumption constrains, such as homogeneous service and server with unlimited resources, which are not suitable for the reality scenarios. This paper proposes Placement Combination between Heterogeneous Services and heterogeneous capacitated Servers (PCHSS). PCHSS aims to minimize the delay in computation and transmission as well as to balance resources in edge servers. Because the placement combination optimization is a NP-hard problem, we propose two solution algorithms named FHPC and IUPC. Both algorithms have a two-layer iterative optimization structure with different convergence time and result performances. FHPC can converge to a good result quickly, and IUPC can achieve better results with a relatively higher computational complexity. Then we prove that both algorithms can converge in polynomial time. Extensive simulations demonstrate the significant effectiveness of the placement combination, and our algorithms can reduce the user request delay by up to 51% compared with baseline algorithms.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Abstract
Real-time quantitative PCR (RT-qPCR) has become a widely used method for accurate expression profiling of targeted mRNA and ncRNA. Selection of appropriate internal control genes for RT-qPCR ...normalization is an elementary prerequisite for reliable expression measurement. Here, we present ICG (http://icg.big.ac.cn), a wiki-driven knowledgebase for community curation of experimentally validated internal control genes as well as their associated experimental conditions. Unlike extant related databases that focus on qPCR primers in model organisms (mainly human and mouse), ICG features harnessing collective intelligence in community integration of internal control genes for a variety of species. Specifically, it integrates a comprehensive collection of more than 750 internal control genes for 73 animals, 115 plants, 12 fungi and 9 bacteria, and incorporates detailed information on recommended application scenarios corresponding to specific experimental conditions, which, collectively, are of great help for researchers to adopt appropriate internal control genes for their own experiments. Taken together, ICG serves as a publicly editable and open-content encyclopaedia of internal control genes and accordingly bears broad utility for reliable RT-qPCR normalization and gene expression characterization in both model and non-model organisms.
Mobile Edge Computing (MEC) offloads service functionalities from central cloud to edge network and process user requests there, which reduces service latency and alleviates cloud burden. Only ...partial services can run on edge nodes with limited resource capacity. Both time varying and heterogeneity of services users requesting introduce great challenges for the resource utilization of edge nodes and user quality of service (QoS). Edge cooperation with joint optimization emerges to cope with this problem for MEC service provider. Recent researches focus on the non-cooperation or partial cooperation among edge nodes in local area network (LAN), their benefits are only explored on a small scale, and the users still face with resources waste and high service. This paper jointly optimizes service placing and task scheduling in MEC based on edge utility maximization and full cooperation of edge nodes in LAN. Edge full cooperation can place as many types of services as possible and capture more user requests in edge network so as to reduce the overall delay and edge energy consumption. Further considering the individual user QoS, we formularize the rewards in the edge utility to promote the local processing of user tasks. The joint optimization is a mixed integer nonlinear program problem which is NP-hard with high computational complexity. Therefore, we design a two-layer iterative strategy (TI-ST) based on Gibbs sampling and linear programming, which has polynomial computation complexity and has provably near optimal performance. Experimental results demonstrate the effectiveness of the proposed scheme when compared with the benchmark schemes.
Abstract
RNA editing, as an essential co-/post-transcriptional RNA modification type, plays critical roles in many biological processes and involves with a variety of human diseases. Although several ...databases have been developed to collect RNA editing data in both model and non-model animals, there still lacks a resource integrating associations between editome and human disease. In this study, we present Editome-Disease Knowledgebase (EDK; http://bigd.big.ac.cn/edk), an integrated knowledgebase of RNA editome-disease associations manually curated from published literatures. In the current version, EDK incorporates 61 diseases associated with 248 experimentally validated abnormal editing events located in 32 mRNAs, 16 miRNAs, 1 lncRNA and 11 viruses, and 44 aberrant activities involved with 6 editing enzymes, which together are curated from more than 200 publications. In addition, to facilitate standardization of editome-disease knowledge integration, we propose a data curation model in EDK, factoring an abundance of relevant information to fully capture the context of editome-disease associations. Taken together, EDK is a comprehensive collection of editome-disease associations and bears the great utility in aid of better understanding the RNA editing machinery and complex molecular mechanisms associated with human diseases.
Abstract
The BIG Data Center at Beijing Institute of Genomics (BIG) of the Chinese Academy of Sciences provides a suite of database resources in support of worldwide research activities in both ...academia and industry. With the vast amounts of multi-omics data generated at unprecedented scales and rates, the BIG Data Center is continually expanding, updating and enriching its core database resources through big data integration and value-added curation. Resources with significant updates in the past year include BioProject (a biological project library), BioSample (a biological sample library), Genome Sequence Archive (GSA, a data repository for archiving raw sequence reads), Genome Warehouse (GWH, a centralized resource housing genome-scale data), Genome Variation Map (GVM, a public repository of genome variations), Science Wikis (a catalog of biological knowledge wikis for community annotations) and IC4R (Information Commons for Rice). Newly released resources include EWAS Atlas (a knowledgebase of epigenome-wide association studies), iDog (an integrated omics data resource for dog) and RNA editing resources (for editome-disease associations and plant RNA editosome, respectively). To promote biodiversity and health big data sharing around the world, the Open Biodiversity and Health Big Data (BHBD) initiative is introduced. All of these resources are publicly accessible at http://bigd.big.ac.cn.
Virome: the next hotspot in microbiome research Zhang, Yuqing; Cao, Jiabao; Zhao, Na ...
Sheng wu gong cheng xue bao = Chinese journal of biotechnology,
2020-Dec-25, Volume:
36, Issue:
12
Journal Article
Virome is the collective term for the viral collection or viral metagenomes that are distributed in various environments. Viruses can be found in bodies of water, glaciers, plants, animals, and even ...some viruses, which are classified as eukaryotes, prokaryotes and subviruses. Viruses play very important role in maintaining environmental homeostasis and ecosystem balance, and are especially closely related to human health. In recent years, with the advancement of sequencing technology and data analysis, we are able to gain more insights into the virome and explore its potential role in the ecological niche by metagenomic sequencing. A large amount of viral data have been obtained from glaciers, oceans, and various plants and animals, and numerous unknown viruses have been discovered. Virome has been studied mainly through metagenomic data mining, as well as virus-like particles separation and enrichment. To date, several different methods for viral isolation and enrichment exist, and numerous bioinformatic ana
The present study was carried out to produce a high quality puffed infant rice cereal from rice and mung bean through extrusion technology. Experiments were designed using 3 independent variables ...(i. e. 14–18% feed moisture, 400–550 r/min screw speed and 125–175 °C barrel temperature) and 3 response variables (i. e. bulk density, water solubility index and degree of gelatinisation) at five different levels of central composite rotatable design (CCRD). The results of optimization demonstrated that 14% feed moisture, 400 r/min screw speed and 175 °C barrel temperature could generate rice-mungbean extrudates with desirable functional properties. The selected extrudate samples were further examined using scanning electron microscope (SEM), rapid viscosity analyzer (RVA), Fourier transform infrared spectrometer (FTIR), X-ray diffraction (XRD) analysis,
digestibility and fundamental nutrient analysis. Notably, the initial oval-shaped particle structure of starch in the raw materials disappeared, the surface debris and roughness increased, and the density decreased. The time required for the gelatinization of puffed infant rice cereal was the shortest, which was in agreement with the positioning of ready-to-eat weaning food for infants. Moreover, the puffed infant rice cereal displayed higher peak viscosity and breakdown value, smaller retrogradation value and greater top taste value compared to the commercial infant rice cereal. Besides maintaining the initial characteristic peak of starch, the puffed infant rice cereal demonstrated characteristic absorption peaks of COO- in the vicinity of 1546 cm
and 1437 cm
, indicating the formation of carboxylate during extrusion. In addition, the puffed infant rice cereal exhibited firm diffraction peaks at the diffraction angles of 7.4°, 12.5° and 20.5°, indicating that a certain amount of starch changed from type A to type V. Furthermore, the digestive rate of puffed infant rice cereal was higher than that of commercial infant cereal (90.21 versus 86.96%, respectively;
< 0.05). Altogether, our findings reveal that the developed puffed infant rice cereal meets the standards set by the Codex Alimentarius Commission (CAC; 74-1981).
An optimum transmission range is presented to prolong the network lifetime for underwater acoustic sensor networks (UASNs). This study is based on the different definitions of the network lifetime ...and the character of underwater acoustic sensor. The formulation of the optimum transmission range is proposed by the tradeoff between minimizing the energy consumption in network and minimizing the maximum energy consumption in sensor node. Therefore, it provides not only a gauge for performance evaluation of UASNs but also a guideline for the design of UASNs protocols. The predicted results are compared with the measured data and the good agreement is reported.
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