Beijing Computing Center

Beijing, China

Beijing Computing Center

Beijing, China

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Pengjie S.,Beijing Computing Center | Fenlou Z.,Beijing Computing Center | Ru W.,Beijing Computing Center | Zhe L.,Beijing Computing Center
ACM International Conference Proceeding Series | Year: 2016

Based on the "abstract modeling" and "tag technique", a template which can achieve automatic simulation, modeling and calculation for the drawing process of wire drawing dies was developed in the present work. The template, featured by process automation, has a wider application scope than the customized development, and will greatly improve the efficiency of those simulation analyses involving many repetitive operations. The template has been integrated to the Web, through which users can download tag files. The next steps for them are to add tags to the simulation model and submit simulation parameters. Then computing will be executed at the cloud background. By virtue of this mode, the users no longer need to pay much for software and hardware resources, and it will be more accessible to the wire drawing die simulation analysis. Thus, the analysis based on computer aided engineering (CAE) can also be applied by the users unskilled in CAE software. © 2016 ACM.


PubMed | Chinese Academy of Sciences, CAS Beijing National Laboratory for Molecular, Beijing Computing Center, Guangxi Medical University and 2 more.
Type: | Journal: Journal of the American Society of Nephrology : JASN | Year: 2016

Epitopes of phospholipase A2 receptor (PLA2R), the target antigen in idiopathic membranous nephropathy (iMN), must be presented by the HLA-encoded MHC class II molecules to stimulate autoantibody production. A genome-wide association study identified risk alleles at HLA and PLA2R loci, with the top variant rs2187668 within HLA-DQA1 showing a risk effect greater than that of the top variant rs4664308 within PLA2R1. How the HLA risk alleles affect epitope presentation by MHC class II molecules in iMN is unknown. Here, we genotyped 261 patients with iMN and 599 healthy controls at the HLA-DRB1, HLA-DQA1, HLA-DQB1, and HLA-DPB1 loci with four-digit resolution and extracted the encoded amino acid sequences from the IMGT/HLA database. We predicted T cell epitopes of PLA2R and constructed MHC-DR molecule-PLA2R peptide-T cell receptor structures using Modeler. We identified DRB1*1501 (odds ratio, 4.65; 95% confidence interval [95% CI], 3.39 to 6.41; P<0.001) and DRB1*0301 (odds ratio, 3.96; 95% CI, 2.61 to 6.05; P<0.001) as independent risk alleles for iMN and associated with circulating anti-PLA2R antibodies. Strong gene-gene interaction was noted between rs4664308(AA) and HLA-DRB1*1501/DRB1*0301. Amino acid positions 13 (P<0.001) and 71 (P<0.001) in the MHC-DR1 chain independently associated with iMN. Structural models showed that arginine13 and alanine71, encoded by DRB1*1501, and lysine71, encoded by DRB1*0301, facilitate interactions with T cell epitopes of PLA2R. In conclusion, we identified two risk alleles of HLA class II genes and three amino acid residues on positions 13 and 71 of the MHC-DR1 chain that may confer susceptibility to iMN by presenting T cell epitopes on PLA2R.


Wang J.,Capital Normal University | Zeng Y.,Beijing Computing Center
Proceedings of the 2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2012 | Year: 2012

Large size cluster management is a complex and difficult task. In this paper, we firstly discuss distributed hierarchical autonomic management mechanisms including the framework of distributed hierarchical autonomic management system and functions of each its component. And then we design and realize a high-performance cluster management system DHAView. It has autonomic management features such as global information integration, global unified monitoring and management, alarm correlation inference base on autonomic element and local event association analysis. Now this DHAView system is successfully used to manage a real large size high performance cluster. © 2012 IEEE.


Zhao L.,Beijing Computing Center | Ren Y.,Beijing Institute of Technology | Yan B.,Beijing Institute of Technology
Proceedings - 2015 8th International Congress on Image and Signal Processing, CISP 2015 | Year: 2015

Nature language processing is an important part in data mining, which counts a lot in the internet age. Feature extraction effects the accuracy of text classification. This paper proposes a method of iterative feature space evolution to optimize the result. Adjusting the extended dictionary and the stop word list, we optimize the feature space time and again to get a better classifier model. The final result has a higher classification accuracy than the original experiment. © 2015 IEEE.


Zhao L.,Beijing Computing Center | Gao W.,CAS Institute of Computing Technology | Jin Y.,Beijing Computing Center
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2016

Benchmarking as yardsticks for system design and evaluation, has developed a long period and plays a pivotal role in many domains, such as database systems and high performance computing. Through prolonged and unremitting efforts, benchmarks on these domains have been reaching their maturity gradually. However, in terms of emerging scenarios of big data, its different properties in data volume, data types, data processing requirements and techniques, make that existing benchmarks are rarely appropriate for big data systems and further make us wonder how to define a good big data benchmark. In this paper, we revisit successful benchmarks in other domains from two perspectives: benchmarking principles which define fundamental rules, and methodologies which guide the benchmark constructions. Further, we conclude the benchmarking principle and methodology on big data benchmarking from a recent open-source effort – BigDataBench. © Springer International Publishing Switzerland 2016.


Wang J.,Capital Normal University | Zeng Y.,Beijing Computing Center
Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011 | Year: 2011

By considering different weights of items, weighted frequent pattern (WFP) mining can find more important frequent patterns. However previous WFP algorithms are not suitable for continuous, unbounded and high-speed data streams mining for they need multiple database scans. In this paper, we present an efficient algorithm DSWFP, which is based on sliding window and can discover important frequent pattern from the recent data. DSWFP has three new characters, including a new refined weight definition, a new proposed data structure and two pruning strategies. Experimental studies are performed to evaluate the good effectiveness of DSWFP. © 2011 IEEE.


Wang J.,Capital Normal University | Zeng Y.,Beijing Computing Center
ICSESS 2012 - Proceedings of 2012 IEEE 3rd International Conference on Software Engineering and Service Science | Year: 2012

Weighted frequent pattern mining is suggested to discover more important frequent pattern by considering different weights of each item, and closed frequent pattern mining can reduces the number of frequent patterns and keep sufficient result information. In this paper, we propose an efficient algorithm DS-CWFP to mine closed weighted frequent pattern mining over data streams. We present an efficient algorithm based on sliding window and can discover closed weighted frequent pattern from the recent data. A new efficient DS-CWFP data structure is used to dynamically maintain the information of transactions and also maintain the closed weighted frequent patterns has been found in the current sliding window. Three optimization strategies are present. The detail of the algorithm DS-CWFP is also discussed. Experimental studies are performed to evaluate the good effectiveness of DS-CWFP. © 2012 IEEE.


Jie W.,Capital Normal University | Yu Z.,Beijing Computing Center
ICSESS 2012 - Proceedings of 2012 IEEE 3rd International Conference on Software Engineering and Service Science | Year: 2012

In this paper, we design and realize a laboratory equipment management and failure prediction system based on Web Service. We use decision tree and time series algorithm to provide users with effective decision support and failure prediction of laboratory equipment. Our prediction modules and equipment management modules can increase the management flexibility greatly. This system can also be applied to different equipment management environment. The improved system can be further promoted to be used in colleges, universities and other units. © 2012 IEEE.


Xiao L.,Capital Normal University | Zhang L.,Capital Normal University | Yang G.,Capital Normal University | Zhu H.,Beijing Computing Center | He Y.,Capital Normal University
PLoS ONE | Year: 2012

Background: Differentiated plant cells can retain the capacity to be reprogrammed into pluripotent stem cells during regeneration. This capacity is associated with both cell cycle reactivation and acquisition of specific cellular characters. However, the molecular mechanisms underlying the reprogramming of protoplasts into stem cells remain largely unknown. Protoplasts of the moss Physcomitrella patens easily regenerate into protonema and therefore provide an ideal system to explore how differentiated cells can be reprogrammed to produce stem cells. Principal findings: We obtained genome-wide digital gene expression tag profiles within the first three days of P. patens protoplast reprogramming. At four time-points during protoplast reprogramming, the transcript levels of 4827 genes changed more than four-fold and their expression correlated with the reprogramming phase. Gene ontology (GO) and pathway enrichment analysis of differentially expressed genes (DEGs) identified a set of significantly enriched GO terms and pathways, most of which were associated with photosynthesis, protein synthesis and stress responses. DEGs were grouped into six clusters that showed specific expression patterns using a K-means clustering algorithm. An investigation of function and expression patterns of genes identified a number of key candidate genes and pathways in early stages of protoplast reprogramming, which provided important clues to reveal the molecular mechanisms responsible for protoplast reprogramming. Conclusions: We identified genes that show highly dynamic changes in expression during protoplast reprogramming into stem cells in P. patens. These genes are potential targets for further functional characterization and should be valuable for exploration of the mechanisms of stem cell reprogramming. In particular, our data provides evidence that protoplasts of P. patens are an ideal model system for elucidation of the molecular mechanisms underlying differentiated plant cell reprogramming. © 2012 Xiao et al.


PubMed | Beijing Computing Center
Type: Journal Article | Journal: Journal of molecular modeling | Year: 2016

As a member of the epidermal growth factor receptor family (EGFR) of receptor tyrosine kinases, ERBB3 plays an important role in mediating cellular growth and differentiation. Recent research works identified that CD74-NRG1 fusions lead to overexpression of the EGF-like domain of NRG1, and thus activate ERBB3 and PI3K-AKT signaling pathways. The fusion was detected in lung adenocarcinomas, and served as an important oncogenic factor for ERBB3 driven cancers. A sequential virtual screening strategy has been applied to ERBB3 crystal structure using databases of natural products and Chinese traditional medicine compounds, and led to identification of a group of small molecular compounds potentially capable of blocking ERBB3. Six small molecular compounds were selected for in vitro analysis. Five of these molecules significantly inhibited the growth of A549 cells. Among them, compound VS1 is the most promising one with IC50 values of 269.75M, comparing to the positive control of nimustine hydrochloride with IC50 values of 264.14M. With good specificity and predicted ADMET results, our results support the feasibility by using a pharmacophore of the compound VS1 for designing and optimization of ERBB3 inhibitors.

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