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標(biāo)題: Titlebook: Microarray Bioinformatics; Verónica Bolón-Canedo,Amparo Alonso-Betanzos Book 2019 Springer Science+Business Media, LLC, part of Springer N [打印本頁]

作者: deduce    時間: 2025-3-21 17:44
書目名稱Microarray Bioinformatics影響因子(影響力)




書目名稱Microarray Bioinformatics影響因子(影響力)學(xué)科排名




書目名稱Microarray Bioinformatics網(wǎng)絡(luò)公開度




書目名稱Microarray Bioinformatics網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Microarray Bioinformatics被引頻次




書目名稱Microarray Bioinformatics被引頻次學(xué)科排名




書目名稱Microarray Bioinformatics年度引用




書目名稱Microarray Bioinformatics年度引用學(xué)科排名




書目名稱Microarray Bioinformatics讀者反饋




書目名稱Microarray Bioinformatics讀者反饋學(xué)科排名





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Methods in Molecular Biologyhttp://image.papertrans.cn/m/image/632844.jpg
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978-1-4939-9444-1Springer Science+Business Media, LLC, part of Springer Nature 2019
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Microarray Bioinformatics978-1-4939-9442-7Series ISSN 1064-3745 Series E-ISSN 1940-6029
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作者: 消音器    時間: 2025-3-23 02:32
Computer Tools to Analyze Microarray Data,e associated with the activity of particular genes affecting biological functions (e.g., a particular drug response), or involved in the development of complex diseases. The object of this chapter is to provide a review of software tools that are easy to use even for nonexperts of the domain, and th
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im demokratischen Rechtsstaat sowie die aktuelle Diskrepanz zwischen der medial propagierten .Rückkehr des Religi?sen. und dem faktischen institutionellen Bedeutungsverlust der Religion in Deutschland und Europa..978-3-531-18344-2978-3-531-94181-3Series ISSN 2510-4748 Series E-ISSN 2510-4756
作者: 表狀態(tài)    時間: 2025-3-23 11:11
Dilara Ayyildiz,Silvano Piazza im demokratischen Rechtsstaat sowie die aktuelle Diskrepanz zwischen der medial propagierten .Rückkehr des Religi?sen. und dem faktischen institutionellen Bedeutungsverlust der Religion in Deutschland und Europa..978-3-531-18344-2978-3-531-94181-3Series ISSN 2510-4748 Series E-ISSN 2510-4756
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Kathleen M. Eyster im demokratischen Rechtsstaat sowie die aktuelle Diskrepanz zwischen der medial propagierten .Rückkehr des Religi?sen. und dem faktischen institutionellen Bedeutungsverlust der Religion in Deutschland und Europa..978-3-531-18344-2978-3-531-94181-3Series ISSN 2510-4748 Series E-ISSN 2510-4756
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Amparo Alonso-Betanzos,Verónica Bolón-Canedo,Laura Morán-Fernández,Borja Seijo-Pardo
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Kohbalan Moorthy,Aws Naser Jaber,Mohd Arfian Ismail,Ferda Ernawan,Mohd Saberi Mohamad,Safaai Deris
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Ricardo Cao,Ignacio López-de-Ullibarri historical points “where the movement of life itself, especially in its greatest crisis, elevates itself above itself and becomes aware of its own limits” ., pointing out that the historical course of social life is not located in a more or less homogenous, equally distributed social time and that
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Protocol for DNA Microarrays on Glass Slides,oncoding RNAs to specific pathologies, as well as many others. This chapter describes the protocol for DNA microarray analysis of differential gene expression using DNA sequences spotted on microscope slides.
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Data Warehousing with TargetMine for Omics Data Analysis,is chapter aims to provide a user guide to data querying, analysis, and visualization with TargetMine and the associated auxiliary toolkit. We have also discussed some of the commonly used data queries for the researchers who are interested in gene set analysis within a data warehouse framework. Ove
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作者: 比目魚    時間: 2025-3-27 02:44
Statistical Analysis of Microarray Data, analysis of microarray data can be done in different ways using different tools. In this chapter a typical workflow for analyzing microarray data using R and Bioconductor packages is presented. The workflow starts with the raw data—binary files obtained from the hybridization process—and goes throu
作者: 不透明性    時間: 2025-3-27 07:58
Feature Selection Applied to Microarray Data,usually less than 100. In the context of microarray classification, this poses a challenge for machine learning methods, which can suffer overfitting and thus degradation in their performance. A common solution is to apply a dimensionality reduction technique before classification, to reduce the num
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Cluster Analysis of Microarray Data,phenomena have revived a great interest in cluster analysis due in part to the large amount of microarray data. Traditional clustering algorithms show, apart from the need of user-defined parameters, clear limitations to handle microarray data owing to its inherent characteristics: high-dimensional-
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ROC Curves for the Statistical Analysis of Microarray Data,s discrimination threshold. This chapter is an overview on the use of ROC curves for microarray data. The notion of ROC curve and its motivation is introduced in Subheading 1. Relevant scientific contributions concerning the use of ROC curves for microarray data are briefly reviewed in Subheading 2.
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Computer Tools to Analyze Microarray Data,single experiment. Different kinds of microarrays are available which are identifiable by characteristics such as the type of probes, the surface used as support, and the method used for target detection. Although microarrays have been applied in many biological areas, their management, and investig
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Classification of Microarray Data,balanced data and missing of data. To conclude, we present an exhaustive review of the main scientific works in journals to show the most successful techniques applied in this discipline as well as the most used datasets to verify their effectiveness.
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1064-3745 expertsThis book provides a comprehensive, interdisciplinary collection of the main, up-to-date methods, tools, and techniques for microarray data analysis, covering the necessary steps for the acquisition of the data, its preprocessing, and its posterior analysis. Featuring perspectives from biolo
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A Review of Microarray Datasets: Where to Find Them and Specific Characteristics,res and the small sample sizes. This chapter is devoted to reviewing the microarray databases most frequently used in the literature. We also make the interested reader aware of the problematic of data characteristics in this domain, such as the imbalance of the data, their complexity, and the so-called dataset shift.




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