【摘 要】
：
Big data,cloud computing and HPC are at the verge of convergence.Cloud computing is already playing an active part in big data processing with the help of big data frameworks like Hadoop and Spark.Rec
【出 处】
：
第二届中国计算机学会生物信息学会议
论文部分内容阅读
Big data,cloud computing and HPC are at the verge of convergence.Cloud computing is already playing an active part in big data processing with the help of big data frameworks like Hadoop and Spark.Recently,the upsurge of high performance computing in China provides extra possibilities and capacity to address the big data challenge.In this paper,we proposed Orion,a big data interface on the Tianhe-2 supercomputer,to enable big data applications to run on Tianhe-2 via a single command or a shell script.Orion supports multiple users and each user can launch multiple tasks.
其他文献
In this paper,a Hepatitis B virus(HBV)model with an incubation period,and delayed state and control variables is firstly proposed; furthermore the combination treatment is adopted in order to have a l
The prediction of residue solvent accessibility(RSA)can provide more information for analyzing protein structures and functions.Many computing methods have been proposed to predict it for better perfo
Simulating multi-scale dynamics of complex living systems is the major challenge in the researches of computational system biology.In this work,we propose a CUDA-based generic multi-cellular biologica
Ribosome stalling is manifested by the local accumulation of ribosomes at specific codon positions of mRNAs.Here,we present ROSE,a deep learning framework to analyze high-throughput ribosome profiling
Docker 应用容器引擎可实现打包生物信息数据流应用程序以及依赖包到一个可移植的容器中,然后部署到任何主流的 Linux 机器上。本实验室利用Docker 技术结合make 搭建面向RNA-Seq、全基因组重测序、Pacbio 三代全长转录组测序等生物信息分析软件工作流程的Docker 容器。产出的大型工作流可以实现RNA-Seq 表达差异分析及GO、KEGG 等相关注释分析,同时能实现对fus
Multi-view classification and feature selection have received considerable attention in recent years.In many real classification problems,the data in each view may have noise.The low-rank regression m
Defining informative features from complex and high dimensional biological data is of great importance in disease study,drug development,etc.Support vector machine-recursive feature elimination(SVM-RF
Practical live-cell super-resolution(SR)techniques are long-desired in many routine biological labs to image biomolecule dynamics.However,the current methods either require sophisticated optical setup
Graph canonization is a fundamental problem both in theoretical and practical computer science.However,it is still an open problem to study in graph theory.In this paper,we propose a new graph canoniz
图聚类算法可以用于发现社会网络中的社区结构、蛋白质互作用网络的功能模块等,是当前复杂网络研究的热点之一。合理度量网络中节点的相似性是设计有效图聚类算法的核心问题。针对此问题,本文提出了一种基于两点间短路径的节点相似性度量方法,并在此基础上给出了一种面向复杂网络的图聚类算法(A Graph Clustering Algorithm Based on Pathsbetween Nodes in Com