Titlebook: Data Mining in Bioinformatics; Xindong Wu,Lakhmi Jain,Dennis Shasha Book 2005 Springer-Verlag London 2005 Alignment.Markov chain.XML.bioin

SPIR

书目名称Data Mining in Bioinformatics影响因子(影响力)




书目名称Data Mining in Bioinformatics影响因子(影响力)学科排名




书目名称Data Mining in Bioinformatics网络公开度




书目名称Data Mining in Bioinformatics网络公开度学科排名




书目名称Data Mining in Bioinformatics被引频次




书目名称Data Mining in Bioinformatics被引频次学科排名




书目名称Data Mining in Bioinformatics年度引用




书目名称Data Mining in Bioinformatics年度引用学科排名




书目名称Data Mining in Bioinformatics读者反馈




书目名称Data Mining in Bioinformatics读者反馈学科排名

HEAVY

椭圆

https://doi.org/10.1007/978-1-4614-7560-6ies and for accurately estimating the costs of the various query evaluation plans. Our performance studies show that the proposed techniques are very efficient and can provide scientists with interactive secondary structure querying options even on large protein datasets.

轻浮思想

Book 2005ly involved in intracellular tra?cking and support. The context of protein functionality is well represented by protein subcellular location. Proteins have various subcellular location patterns [250]. One major category of proteins is synthesized on free ribosomes in the cytoplasm. Soluble proteins

patriot

AntiClustAl: Multiple Sequence Alignment by Antipole Clusteringces. In particular, a clustering data structure called antipole tree and an approximate linear 1-median computation are used. Our algorithm enjoys a better running time with equivalent alignment quality compared with ClustalW, a widely used tool for multiple sequence alignment. A successful biologic

记成蚂蚁

Data Mining Methods for a Systematics of Protein Subcellular Locationom the fluorescence microscope images. By selecting the most discriminative features from the entire feature set and recruiting various state-of-the-art classifiers, the system is able to outperform human experts in distinguishing protein patterns. The discriminative features can also be used for ro

记成蚂蚁

无法解释

外星人

座右铭

https://doi.org/10.1007/978-3-031-41837-2d on them to make new discoveries on his or her own. The book contains twelve chapters in four parts, namely, overview, sequence and structure alignment, biological data mining, and biological data management. This chapter provides an introduction to the field and describes how the chapters in the book relate to one another.