Publications by authors named "Runxin Guo"

Article Synopsis
  • * Researchers identified 43 genes from the GRAS gene family in the Chinese fir's genome, classifying them into nine subfamilies and noting that most lack introns, with some featuring unique DELLA domains.
  • * Analysis of gene expression revealed these genes respond to light, hormones, and environmental stresses, suggesting they play a role in how Chinese fir copes with challenges and may inform future studies on DELLA protein regulatory networks.
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Aiming at the contradiction between the lubricating performance and mechanical performance of self-lubricating ceramic tools. CaF@Al(OH) particles were prepared by the heterogeneous nucleation method. An AlO/Ti(C,N) ceramic tool with CaF@Al(OH) particles and ZrO whiskers was prepared by hot press sintering (frittage).

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Background: Novel sequence motifs detection is becoming increasingly essential in computational biology. However, the high computational cost greatly constrains the efficiency of most motif discovery algorithms.

Results: In this paper, we accelerate MEME algorithm targeted on Intel Many Integrated Core (MIC) Architecture and present a parallel implementation of MEME called MIC-MEME base on hybrid CPU/MIC computing framework.

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With the rapid development of next-generation sequencing technology, ever-increasing quantities of genomic data pose a tremendous challenge to data processing. Therefore, there is an urgent need for highly scalable and powerful computational systems. Among the state-of-the-art parallel computing platforms, Apache Spark is a fast, general-purpose, in-memory, iterative computing framework for large-scale data processing that ensures high fault tolerance and high scalability by introducing the resilient distributed dataset abstraction.

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Background: Frequent subgraphs mining is a significant problem in many practical domains. The solution of this kind of problem can particularly used in some large-scale drug molecular or biological libraries to help us find drugs or core biological structures rapidly and predict toxicity of some unknown compounds. The main challenge is its efficiency, as (i) it is computationally intensive to test for graph isomorphisms, and (ii) the graph collection to be mined and mining results can be very large.

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