標(biāo)題: Titlebook: Data Mining in Bioinformatics; Xindong Wu,Lakhmi Jain,Dennis Shasha Book 2005 Springer-Verlag London 2005 Alignment.Markov chain.XML.bioin [打印本頁(yè)] 作者: SPIR 時(shí)間: 2025-3-21 19:31
書(shū)目名稱(chēng)Data Mining in Bioinformatics影響因子(影響力)
書(shū)目名稱(chēng)Data Mining in Bioinformatics影響因子(影響力)學(xué)科排名
書(shū)目名稱(chēng)Data Mining in Bioinformatics網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱(chēng)Data Mining in Bioinformatics網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱(chēng)Data Mining in Bioinformatics被引頻次
書(shū)目名稱(chēng)Data Mining in Bioinformatics被引頻次學(xué)科排名
書(shū)目名稱(chēng)Data Mining in Bioinformatics年度引用
書(shū)目名稱(chēng)Data Mining in Bioinformatics年度引用學(xué)科排名
書(shū)目名稱(chēng)Data Mining in Bioinformatics讀者反饋
書(shū)目名稱(chēng)Data Mining in Bioinformatics讀者反饋學(xué)科排名
作者: HEAVY 時(shí)間: 2025-3-21 23:13 作者: 橢圓 時(shí)間: 2025-3-22 03:22
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.作者: 輕浮思想 時(shí)間: 2025-3-22 06:06
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 作者: patriot 時(shí)間: 2025-3-22 12:45
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作者: 記成螞蟻 時(shí)間: 2025-3-22 14:47
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作者: 記成螞蟻 時(shí)間: 2025-3-22 19:31 作者: 無(wú)法解釋 時(shí)間: 2025-3-22 21:19 作者: 外星人 時(shí)間: 2025-3-23 01:50 作者: 座右銘 時(shí)間: 2025-3-23 06:04
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.作者: commensurate 時(shí)間: 2025-3-23 12:37
https://doi.org/10.1007/b138131Alignment; Markov chain; XML; bioinformatics; biology; calculus; classification; clustering; computer; data a作者: Mosaic 時(shí)間: 2025-3-23 17:09
978-1-84996-894-2Springer-Verlag London 2005作者: Palpitation 時(shí)間: 2025-3-23 21:35
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 b作者: Erythropoietin 時(shí)間: 2025-3-24 00:00 作者: 鎮(zhèn)壓 時(shí)間: 2025-3-24 04:14
https://doi.org/10.1007/978-3-031-41837-2 homologous sequences belonging to classes generated by some clustering algorithm and then continuing the alignment process in a bottom-up way along a suitable tree structure. The final result is then read at the root of the tree. Multiple sequence alignment in each cluster makes use of progressive 作者: Euphonious 時(shí)間: 2025-3-24 06:31
https://doi.org/10.1007/978-3-031-41837-2e or a base pair in the RNA molecule. With this structural representation scheme, we give efficient algorithms for computing the distance and alignment between two RNA secondary structures based on edit operations and on the assumptions in which either no bond-breaking operation is allowed or bond-b作者: 帽子 時(shí)間: 2025-3-24 11:20
https://doi.org/10.1007/978-3-031-41837-2ethod provides posterior distributions on the number of segments in the data and thus gives a much broader view on the potential data than do methods (such as dynamic programming) that aim only at finding a single optimal solution. On the other hand, MCMC methods can be more difficult to implement t作者: Nebulizer 時(shí)間: 2025-3-24 17:02 作者: addict 時(shí)間: 2025-3-24 20:04 作者: Colonnade 時(shí)間: 2025-3-24 23:21 作者: thwart 時(shí)間: 2025-3-25 04:30
Commingled and Disarticulated Human Remainss the substructure discovery process from the classification model construction and uses frequent subgraph discovery algorithms to find all topological and geometric substructures present in the dataset. The advantage of this approach is that during classification model construction, all relevant su作者: folliculitis 時(shí)間: 2025-3-25 11:33 作者: Constituent 時(shí)間: 2025-3-25 14:09
https://doi.org/10.1007/978-1-4614-7560-6and awkward tools for querying biological datasets. This work highlights a specific problem involving searching large volumes of protein datasets based on their secondary structure. In this chapter we define an intuitive query language that can be used to express queries on secondary structure and d作者: Inculcate 時(shí)間: 2025-3-25 17:18
The Politics of ‘Contemporary Islamic Art’ical systems. For this promise to come to fruition, new query algorithms, data models, and data management techniques need to be developed that can provide access to the varied kinds and large amounts of biological data. This chapter presents scalable index structures for DNA/protein sequences, prot作者: myriad 時(shí)間: 2025-3-25 23:54
Xindong Wu,Lakhmi Jain,Dennis ShashaNo known book on this area.First book containing the work of key researchers in biological data mining.Presents new techniques on (a) gene expression data mining, (b) gene mapping for disease detectio作者: Ballad 時(shí)間: 2025-3-26 01:18
Advanced Information and Knowledge Processinghttp://image.papertrans.cn/d/image/262960.jpg作者: 突變 時(shí)間: 2025-3-26 07:22 作者: 天氣 時(shí)間: 2025-3-26 12:07 作者: 民間傳說(shuō) 時(shí)間: 2025-3-26 16:14
Survey of Biodata Analysis from a Data Mining Perspectiveds in-depth analysis. On the other hand, recent progress in data mining research has led to the development of numerous efficient and scalable methods for mining interesting patterns in large databases. The question becomes how to bridge the two fields, . and ., for successful mining of biological d作者: 消瘦 時(shí)間: 2025-3-26 19:46
AntiClustAl: Multiple Sequence Alignment by Antipole Clustering homologous sequences belonging to classes generated by some clustering algorithm and then continuing the alignment process in a bottom-up way along a suitable tree structure. The final result is then read at the root of the tree. Multiple sequence alignment in each cluster makes use of progressive 作者: 侵略 時(shí)間: 2025-3-26 21:43
RNA Structure Comparison and Alignmente or a base pair in the RNA molecule. With this structural representation scheme, we give efficient algorithms for computing the distance and alignment between two RNA secondary structures based on edit operations and on the assumptions in which either no bond-breaking operation is allowed or bond-b作者: Flounder 時(shí)間: 2025-3-27 04:28
Piecewise Constant Modeling of Sequential Data Using Reversible Jump Markov Chain Monte Carloethod provides posterior distributions on the number of segments in the data and thus gives a much broader view on the potential data than do methods (such as dynamic programming) that aim only at finding a single optimal solution. On the other hand, MCMC methods can be more difficult to implement t作者: frozen-shoulder 時(shí)間: 2025-3-27 05:59 作者: meritorious 時(shí)間: 2025-3-27 09:29 作者: Genome 時(shí)間: 2025-3-27 14:46 作者: 針葉樹(shù) 時(shí)間: 2025-3-27 18:17 作者: Calculus 時(shí)間: 2025-3-28 00:15 作者: 睨視 時(shí)間: 2025-3-28 05:11 作者: Misgiving 時(shí)間: 2025-3-28 08:01 作者: 一再煩擾 時(shí)間: 2025-3-28 12:59
1610-3947 xpression data mining, (b) gene mapping for disease detectio8. 1. 1 Protein Subcellular Location The life sciences have entered the post-genome era where the focus of biologicalresearchhasshiftedfromgenomesequencestoproteinfunctionality. Withwhole-genomedraftsofmouseandhumaninhand,scientistsareputti作者: progestogen 時(shí)間: 2025-3-28 17:05
Survey of Biodata Analysis from a Data Mining Perspectiveata. In this chapter, we present an overview of the data mining methods that help biodata analysis. Moreover, we outline some research problems that may motivate the further development of data mining tools for the analysis of various kinds of biological data.作者: FIN 時(shí)間: 2025-3-28 19:15
RNA Structure Comparison and Alignmentreaking activities are considered. The techniques provide a foundation for developing solutions to the hard problems concerning RNA tertiary structure comparisons. Some experimental results based on real-world RNA data are also reported.作者: enormous 時(shí)間: 2025-3-29 00:46 作者: Cpap155 時(shí)間: 2025-3-29 04:20 作者: 影響帶來(lái) 時(shí)間: 2025-3-29 09:51 作者: 狂怒 時(shí)間: 2025-3-29 11:52
Scalable Index Structures for Biological Dataein structures, and pathways. After a brief discussion of sequences and structures, the focus shifts to pathways. Modeling of pathways along with their qualitative and quantitative characteristics is considered. Techniques that allow comparison and querying of static and dynamic aspects of pathways are presented.作者: Creatinine-Test 時(shí)間: 2025-3-29 18:01 作者: MUTE 時(shí)間: 2025-3-29 20:50
Gene Mapping by Pattern Discoveryhods and present a novel instance, HPM-G, suitable for directly analyzing phase-unknown genotype data. Obtaining haplotypes is more costly than obtaining phase-unknown genotypes, and our experiments show that although larger samples are needed with HPMG, it is still in many cases more cost-effective than analysis with haplotype data.作者: Cultivate 時(shí)間: 2025-3-30 03:03
