標(biāo)題: Titlebook: Computational Life Sciences; Data Engineering and Jens D?rpinghaus,Vera Weil,Alexander Apke Book 2022 The Editor(s) (if applicable) and The [打印本頁(yè)] 作者: 多話 時(shí)間: 2025-3-21 17:03
書目名稱Computational Life Sciences影響因子(影響力)
書目名稱Computational Life Sciences影響因子(影響力)學(xué)科排名
書目名稱Computational Life Sciences網(wǎng)絡(luò)公開度
書目名稱Computational Life Sciences網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Computational Life Sciences被引頻次
書目名稱Computational Life Sciences被引頻次學(xué)科排名
書目名稱Computational Life Sciences年度引用
書目名稱Computational Life Sciences年度引用學(xué)科排名
書目名稱Computational Life Sciences讀者反饋
書目名稱Computational Life Sciences讀者反饋學(xué)科排名
作者: myocardium 時(shí)間: 2025-3-21 20:51
Studies in Big Datahttp://image.papertrans.cn/c/image/232579.jpg作者: Observe 時(shí)間: 2025-3-22 00:41 作者: Vulnerary 時(shí)間: 2025-3-22 05:04 作者: hemophilia 時(shí)間: 2025-3-22 10:41 作者: Mere僅僅 時(shí)間: 2025-3-22 13:15
Network Analysis: Bringing Graphs to Javaprotein interaction networks. In this chapter, we introduce the analysis of graph structures with Java. In particular, we discuss directed and undirected graphs, random graphs and interaction networks.作者: Mere僅僅 時(shí)間: 2025-3-22 19:46 作者: Dignant 時(shí)間: 2025-3-22 22:05
https://doi.org/10.1007/978-3-531-91030-7lds of Life Sciences ranging from epidemiology to genetics, from simulations to image processing..We cannot give a detailed introduction into each language, but rather provide some context and small examples to to wet your appetite and make you aware of all the beautiful and powerful tools available作者: 和藹 時(shí)間: 2025-3-23 03:58 作者: Obloquy 時(shí)間: 2025-3-23 08:07
https://doi.org/10.1007/978-3-322-97341-2first six describe dynamic processes with changes over time, so it seems only natural that working with longitudinal data is at the very core of life sciences. In this chapter, we want to explore some core ideas of longitudinal data analysis from math to programming and applications.作者: 沙文主義 時(shí)間: 2025-3-23 13:12
https://doi.org/10.1007/978-3-642-61619-8protein interaction networks. In this chapter, we introduce the analysis of graph structures with Java. In particular, we discuss directed and undirected graphs, random graphs and interaction networks.作者: Mortal 時(shí)間: 2025-3-23 17:41
Systematik und Grundlagen zu BIM im FM,This chapter is a principal introduction to the Java programming language, treating the setup of an adequate environment, basics and the integration of external libraries. Beyond, it provides information of using collaborative tools like Git. This quick start guide to Java is designed to be application-oriented, supporting an easy start.作者: 不在灌木叢中 時(shí)間: 2025-3-23 22:01
https://doi.org/10.1007/978-3-658-30830-8This chapter comes in hand with the second chapter, to provide the reader with more information about Java. In particular it focuses on Basic Data Processing. Amongst other topics, common data structures and their usage as well as aspects of the object-orientied programming paradigm are introduced作者: 雪白 時(shí)間: 2025-3-23 23:39
Introduction to JavaThis chapter is a principal introduction to the Java programming language, treating the setup of an adequate environment, basics and the integration of external libraries. Beyond, it provides information of using collaborative tools like Git. This quick start guide to Java is designed to be application-oriented, supporting an easy start.作者: 治愈 時(shí)間: 2025-3-24 06:01 作者: Infinitesimal 時(shí)間: 2025-3-24 10:06
https://doi.org/10.1007/978-3-031-08411-9Data Engineering; Data Mining; Life Science Informatics; Bioinformatics; Knowledge Discovery作者: 最高峰 時(shí)間: 2025-3-24 12:13 作者: Keratectomy 時(shí)間: 2025-3-24 17:31 作者: HUMID 時(shí)間: 2025-3-24 21:47
https://doi.org/10.1007/978-3-322-97143-2be modeled in a way that an algorithm can understand and solve it. Further, we introduce the Big O Notation as a concept for quantifying the efficiency of algorithms. We will know the difference between the complexity classes P and NP and discover some very important basic paradigms in designing eff作者: 尊嚴(yán) 時(shí)間: 2025-3-25 03:03
Margret Schencking,Friedrich-Wilhelm D?rgeisciplinary field, touching economics (how efficient and expensive is the solution?), psychology (does one use this solution in a way that was intended?) and, of course, informatics. This chapter offers a theoretical overview on Data and Knowledge Management and thus provides a theoretic foundation 作者: 擋泥板 時(shí)間: 2025-3-25 04:39 作者: antedate 時(shí)間: 2025-3-25 10:13 作者: mucous-membrane 時(shí)間: 2025-3-25 13:20 作者: noxious 時(shí)間: 2025-3-25 17:24
Strukturprobleme der ?kumenischen Konzilien by a centre and the computing power requested by the users of the centre, both in terms of capacity and performance. Replacing old hardware by new, more powerful one could only close the gap for a limited time since new capabilities also lead to new software developments making use of the new capab作者: BRACE 時(shí)間: 2025-3-25 22:03 作者: 仇恨 時(shí)間: 2025-3-26 01:08 作者: 膠狀 時(shí)間: 2025-3-26 07:35
https://doi.org/10.1007/978-3-642-61619-8protein interaction networks. In this chapter, we introduce the analysis of graph structures with Java. In particular, we discuss directed and undirected graphs, random graphs and interaction networks.作者: 證實(shí) 時(shí)間: 2025-3-26 11:29
https://doi.org/10.1007/978-3-642-52771-5linear and combinatorial optimization problems. Accompanied by some illustrative problems arising from various applications in Life Sciences, we learn how to model these problems in a mathematical way. We will further discuss general approaches in tackling these problems, discover some widely known 作者: 無(wú)意 時(shí)間: 2025-3-26 16:02
https://doi.org/10.1007/978-3-642-52771-5echnologies lead to an increasing number of digital images for medical biological diagnostics. Though microscopy is still an important topic, computed tomography (CT) and magnetic resonance imaging (MRI) follow up the analogue technologies like endoscopy or radiography. There are lots of application作者: 知識(shí) 時(shí)間: 2025-3-26 20:47 作者: 擁擠前 時(shí)間: 2025-3-27 00:36 作者: 設(shè)施 時(shí)間: 2025-3-27 01:58
Von der Globalsteuerung zur Strukturpolitikcan only scratch the surface of it and give a short introduction with focus on implementing software using databases with Java. In this chapter, we will not only discuss some relational databases, but also knowledge graphs, and graph databases. In particular, we will also discuss link prediction in knowledge graphs.作者: 駭人 時(shí)間: 2025-3-27 06:18
Umweltschutz als Wirtschaftsfaktor, and methods to be used in this context. We will discuss Knowledge representation, e.g. with XML and JSON, introduce some AI approaches, and finally discuss the impact on personalized medicine as an example use case within life sciences.作者: interference 時(shí)間: 2025-3-27 13:30 作者: 命令變成大炮 時(shí)間: 2025-3-27 15:39 作者: Carcinogenesis 時(shí)間: 2025-3-27 19:11
Knowledge Discovery and?AI Approaches for?the?Life Sciences and methods to be used in this context. We will discuss Knowledge representation, e.g. with XML and JSON, introduce some AI approaches, and finally discuss the impact on personalized medicine as an example use case within life sciences.作者: Emasculate 時(shí)間: 2025-3-27 22:06
Optimization how to model these problems in a mathematical way. We will further discuss general approaches in tackling these problems, discover some widely known solving algorithms and have a closer look at their exemplary implementations in Java.作者: magnanimity 時(shí)間: 2025-3-28 05:11
Data and?Knowledge Managementfor the following parts of this book. Moreover, if you implement or plan a solution in the field of data mining or data engineering, carefully consider the information given here. In other words: Besides the theory, this chapter provides a technical blueprint.作者: 粗魯?shù)娜?nbsp; 時(shí)間: 2025-3-28 06:58
Image Processing and Manipulatings: quantities and localization of signaling proteins, dynamic changes of cell structures, tracking cancer cells in time-lapse recordings, and much more. In this chapter, we present a primer on image processing and manipulating using ImageJ in Java.作者: PLUMP 時(shí)間: 2025-3-28 13:58 作者: 截?cái)?nbsp; 時(shí)間: 2025-3-28 17:04 作者: 種族被根除 時(shí)間: 2025-3-28 18:46
Margret Schencking,Friedrich-Wilhelm D?rgefor the following parts of this book. Moreover, if you implement or plan a solution in the field of data mining or data engineering, carefully consider the information given here. In other words: Besides the theory, this chapter provides a technical blueprint.作者: Isometric 時(shí)間: 2025-3-29 02:56
https://doi.org/10.1007/978-3-642-52771-5s: quantities and localization of signaling proteins, dynamic changes of cell structures, tracking cancer cells in time-lapse recordings, and much more. In this chapter, we present a primer on image processing and manipulating using ImageJ in Java.作者: 迫擊炮 時(shí)間: 2025-3-29 06:32
Wolfgang Stegmüller,Matthias Varga von Kibédion-oriented topics treat database searches as well as the underlying sequence alignment algorithms. While we concentrate on the classical FASTA format for demonstration reasons, Next-Generation Sequencing (NGS) data and principles are addressed as well. The chapter closes on relating to contemporary developments in applications and technologies.作者: MINT 時(shí)間: 2025-3-29 10:05 作者: Matrimony 時(shí)間: 2025-3-29 11:30
Computational Gridsduring the day-to-day business. Frequent updates of the infrastructure to cope with increasing load are both difficult, leading, e.g. to service interruption, and expensive. In the environment of research centres a first approach to overcome the problems was making use of external resources from other research centres for peak loads.作者: vibrant 時(shí)間: 2025-3-29 18:18 作者: 鄙視讀作 時(shí)間: 2025-3-29 20:43
Interesting Programming Languages Used in Life Scienceslds of Life Sciences ranging from epidemiology to genetics, from simulations to image processing..We cannot give a detailed introduction into each language, but rather provide some context and small examples to to wet your appetite and make you aware of all the beautiful and powerful tools available作者: dissent 時(shí)間: 2025-3-30 02:50
Algorithm Designbe modeled in a way that an algorithm can understand and solve it. Further, we introduce the Big O Notation as a concept for quantifying the efficiency of algorithms. We will know the difference between the complexity classes P and NP and discover some very important basic paradigms in designing eff作者: Genteel 時(shí)間: 2025-3-30 05:21 作者: 勤勉 時(shí)間: 2025-3-30 10:04
Databases and?Knowledge Graphsen several paradigm shifts, for example from SQL to NoSQL databases. Hosting database systems, their design and management is a complex topic, and we can only scratch the surface of it and give a short introduction with focus on implementing software using databases with Java. In this chapter, we wi作者: 戰(zhàn)勝 時(shí)間: 2025-3-30 16:15 作者: 沐浴 時(shí)間: 2025-3-30 17:09
Longitudinal Datafirst six describe dynamic processes with changes over time, so it seems only natural that working with longitudinal data is at the very core of life sciences. In this chapter, we want to explore some core ideas of longitudinal data analysis from math to programming and applications.作者: Conclave 時(shí)間: 2025-3-30 21:47 作者: 輪流 時(shí)間: 2025-3-31 03:08 作者: osteocytes 時(shí)間: 2025-3-31 08:31
