Feature analysis for classification of trace fluorescent labeled protein crystallization images
作者: Madhav SigdelImren DincMadhu S. SigdelSemih DincMarc L. PuseyRamazan S. Aygun
作者单位: 1University of Alabama in Huntsville
2Troy University
3iXpressGenes, Inc.
刊名: BioData Mining, 2017, Vol.10 (1)
来源数据库: Springer Nature Journal
DOI: 10.1186/s13040-017-0133-9
关键词: Protein crystallizationImage classificationFeature analysisTrace-fluorescent labeling
英文摘要: Large number of features are extracted from protein crystallization trial images to improve the accuracy of classifiers for predicting the presence of crystals or phases of the crystallization process. The excessive number of features and computationally intensive image processing methods to extract these features make utilization of automated classification tools on stand-alone computing systems inconvenient due to the required time to complete the classification tasks. Combinations of image feature sets, feature reduction and classification techniques for crystallization images benefiting from trace fluorescence labeling are investigated.
原始语种摘要: Large number of features are extracted from protein crystallization trial images to improve the accuracy of classifiers for predicting the presence of crystals or phases of the crystallization process. The excessive number of features and computationally intensive image processing methods to extract these features make utilization of automated classification tools on stand-alone computing systems inconvenient due to the required time to complete the classification tasks. Combinations of image feature sets, feature reduction and classification techniques for crystallization images benefiting from trace fluorescence labeling are investigated.
全文获取路径: Springer Nature  (合作)
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关键词翻译
关键词翻译
  • fluorescent 萤光的
  • features 特征
  • classification 分类
  • analysis 分析
  • protein 蛋白质
  • image 
  • processing 加工
  • tools 工具
  • excessive 过度
  • inconvenient 不方便的