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Numerical Mathematics and Advanced Applications ENUMATH 2019 ; European Conference, Egmond aan Zee, The Netherlands, September 30 - October 4
It contians basic aspects and new trends in numerical mathematics and scientific and industrial applications, all examined at the highest level of international expertise.
New trends in computational vision and bio-inspired computing : Selected works presented at the ICCVBIC 2018, Coimbatore, India
Gathers selected, peer-reviewed original contributions presented at the International Conference on Computational Vision and Bio-inspired Computing (ICCVBIC) conference which was held in Coimbatore, India, on November 29-30, 2018. The works included here offer a rich and diverse sampling of recent developments in the fields of Computational Vision, Fuzzy, Image Processing and Bio-inspired Computing. The topics covered include computer vision; cryptography and digital privacy; machine learning and artificial neural networks; genetic algorithms and computational intelligence; the Internet of Things; and biometric systems, to name but a few. The applications discussed range from security, healthcare and epidemic control to urban computing, agriculture and robotics.
Modern Formal Methods and Applications
Formal methods are a robust approach for problem solving. It is based on logic and algebraic methods where problems can be formulated in a way that can help to find an appropriate solution. This book shows the basic concepts of formal methods and highlights modern modifications and enhancements to provide a more robust and efficient problem solving tool.Applications are presented from different disciplines such as engineering where the operation of chemical plants is synthesized using formal methods. Computational biology becomes easier and systematic using formal methods. Also, hardware compilation and systems can be managed using formal methods.
Modelli Matematici in Biologia = Mathematical Models in Biology
This text is addressed first of all to the students of the Specialist Degrees in Biology of the Universities, but it will also be of interest to students of Natural Sciences and Medicine. The topics covered include the most classic mathematical models of biological phenomena (population dynamics, spread of infectious diseases, simple physiology models), but a relevant part of the text is dedicated to the mathematical approach to the theory of natural evolution. The only prerequisites required of the reader are those provided by the basic courses of Mathematics of the Bachelor's Degree in Biology, Natural Sciences or Medicine.
Modeling biological systems : Principles and applications
This extensively revised second edition of Modeling Biological Systems: Principles and Applications describes the essentials of creating and analyzing mathematical and computer simulation models for advanced undergraduates and graduate students. It offers a comprehensive understanding of the underlying principle, as well as details and equations applicable to a wide variety of biological systems and disciplines. Students will acquire from this text the tools necessary to produce their own models. The text contains two major sections: Principles and Applications. The first section discusses the principles of biological systems with a thorough description of the essential modeling activities of formulation, implementation, validation, and analysis. These activities are illustrated by a set of example models taken from recent and classical literature, chosen for their breadth of coverage and current timeliness. The new edition updates extensively many of these topics, especially quantitative model formulation, validation and model discrimination using information theory measures and Bayesian probability, and stability analysis and non-dimensionalization.
Introduction to Computational Biology : An Evolutionary Approach
Molecular biology has changed dramatically over the past two decades. Until the early 1990s genes were studied one at a time by small teams of researchers; today entire genomes are sequenced by internationally collaborating laboratories. In the bygone gene-centered era the accumulation of data was the rate-limiting step in research. Now that step is often data interpretation. This is increasingly dependent on computational methods and as a consequence, computational biology has emerged in the past decade as a new subdiscipline of biology. This introduction to computational biology is centered on the analysis of molecular sequence data. There are two closely connected aspects to biological sequences: (i) their relative position in the space of all other sequences, and (ii) their movement through this sequence space in evolutionary time. Accordingly, the first part of the book deals with classical methods of sequence analysis: pairwise alignment, exact string matching, multiple alignment, and hidden Markov models. In the second part evolutionary time takes center stage and phylogenetic reconstruction, the analysis of sequence variation, and the dynamics of genes in populations are explained in detail. In addition, the book contains a computer program with a graphical user interface that allows the reader to experiment with a number of key concepts developed by the authors.
Intelligent data engineering and automated Learning - IDEAL 2008 ; 9th International Conference Daejeon, South Korea, November 2-5, 2008 Proceedings
This book constitutes the refereed proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2008, held in Daejeon, Korea, in November 2008.The 56 revised full papers presented together with 10 invited papers were carefully reviewed and selected from numerous submissions for inclusion in the book. The papers are organized in topical sections on learning and information processing, data mining and information management, bioinformatics and neuroinformatics, agents and distributed systems, as well as financial engineering and modeling.
Intelligent Computing Theories and Application ; 16th International Conference, ICIC 2020, Bari, Italy, October 2–5, 2020, Proceedings, Part I
This two-volume set of LNCS 12463 and LNCS 12464 constitutes - in conjunction with the volume LNAI 12465 - the refereed proceedings of the 16th International Conference on Intelligent Computing, ICIC 2020, held in Bari, Italy, in October 2020. The 162 full papers of the three proceedings volumes were carefully reviewed and selected from 457 submissions The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is “Advanced Intelligent Computing Methodologies and Applications.” Papers related to this theme are especially solicited, addressing theories, methodologies, and applications in science and technology.
Intelligent Computing ; International Conference on Intelligent Computing, ICIC 2006, Kunming, China, August 16-19, 2006, Proceedings, Part I
The International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum with dedication to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, and computational biology, etc. It aims to bring together researchers and practitioners from both the academia and industry to share ideas, problems and solutions related to the multifaceted aspects of intelligent computing. The ICIC 2006 to be held in Kunming, Yunnan, China, 16-19 August 2006 is the second International Conference on Intelligent Computing, which is built upon the success of ICIC 2005 held in Hefei, China, 2005. This year, the conference mainly concentrates on the theories & methodologies as well as the emerging applications of intelligent computing. It intends to unify the contemporary intelligent computing techniques within an integral framework that highlights the trends in advanced computational intelligence and bridges the theoretical research with the applications. In particular, the bio-inspired computing emerges as a key role in pursuing for novel technology in recently years. The resulting techniques vitalize the life science engineering and daily life applications. In light of this trend, the theme for this conference is the Emerging Intelligent Computing Technology and Applications. Papers related to this theme were especially solicited, including theories, methodologies, and applications in science and technology.
Grid computing in life science ; 1st International Workshop on Life Science Grid, LSGRID 2004 Kanazawa, Japan, May 31-June 1, 2004, Revised Selected and Invited Papers
Researchers in the ?eld of life sciences rely increasingly on information te- nology to extract and manage relevant knowledge. The complex computational and data management needs of life science research make Grid technologies an attractive support solution. However, many important issues must be addressed before the Life Science Grid becomes commonplace. The 1st International Life Science Grid Workshop (LSGRID 2004) was held in Kanazawa Japan, May 31–June 1, 2004. This workshop focused on life s- ence applications of grid systems especially for bionetwork research and systems biology which require heterogeneous data integration from genome to phenome, mathematical modeling and simulation from molecular to population levels, and high-performance computing including parallel processing, special hardware and grid computing.
Genome Exploitation : Data Mining the Genome
Data Mining the Genomes, is the 23rd volume of the Stadler Symposia series published by Springer, which have served over many years as a comprehensive collection of current trends and emerging hot topics in the field of genetics. Data Mining the Genomes summarizes the progress in bioinformatics and computational biology in data mining the vast amount of exciting information emerging from studies of plant and animal genomes, with authoritative analytical reviews specialized enough to be attractive to professional researchers, yet also appealing to the wider audience of scientists in related disciplines.
Génetique statistique = Statistical genetics
Presents the main statistical tools useful in genetics: significance tests, analysis methods based on the likelihood function, EM algorithm, modeling, analysis of variance, hierarchical classifications, multiple comparisons, etc. All of them shed light on a number of biological phenomena such as carcinogenesis, population genetics, Hardy-Weinberg equilibrium, natural selection, mutations, heredity, coalescence processes, and even evolution. This book is intended for mathematicians and biologists alike. Written with a great concern for clarity, it is also accessible to non-specialists who will be able, thanks to it, to strengthen their theoretical base and above all to develop their know-how through very concrete applications.
Fundamentals of Clinical Data Science
This book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare.
Formal Methods in Systems Biology ; 1st International Workshop, FMSB 2008, Cambridge, UK, June 4-5, 2008. Proceedings
This book constitutes the refereed proceedings of the First International Workshop on Formal Methods in Systems Biology, FMSB 2008, held in Cambridge, UK, in June, 2008.The 9 revised full papers presented were carefully reviewed and selected from the workshop lectures that all were invited contributions. The purpose of this meeting was to identify techniques for the specification, development and verification of biological models. It also focused on the design of tools to execute and analyze biological models that can significantly advance our understanding of biological systems.
Evolutionary computation, machine learning and data mining in bioinformatics ; 6th European Conference, EvoBIO 2008, Naples, Italy, March 26-28, 2008. Proceedings
The feld of bioinformatics has two main objectives: the creation and main- nance of biological databases, and the discovery of knowledge from life sciences data in order to unravel the mysteries of biological function, leading to new drugs and therapies for human disease. Life sciences data come in the form of biological sequences, structures, pathways, or literature. One major aspect of discovering biological knowledge is to search, predict, or model specifc infortioninagivendatasetinorderto generate new in teresting knowledge.Computer science methods such as evolutionary computation, machine learning, and data mining all have a great deal to ofer the feld of bioinformatics.
Euro-Par 2006 Parallel Processing ; CoreGRID 2006, UNICORE Summit 2006, Petascale Computational Biology and Bioinformatics, Dresden, Germany, August 29-September 1, 2006, Revised Selected Papers
This book contiants Petascale Computational Biology and Bioinformatics.
DNA Computing ; 13th International Meeting on DNA Computing, DNA13, Memphis, TN, USA, June 4-8, 2007, Revised Selected Papers
This book constitutes the thoroughly refereed postproceedings of the 13th International Meeting on DNA Computing, DNA 13, held in Memphis, TN, USA, June 4-8, 2007.
Distributed, High-Performance and Grid Computing in Computational Biology ; International Workshop, GCCB 2006, International Workshop, GCCB 2006, Eilat, Israel, January 21, 2007, Proceedings
Modern computational biology and bioinformatics are characterized by large and complex structured data and by applications requiring considerable computing resources, such as processing units, storage elements and software programs. In addition, these disciplines are intrinsically geographically distributed in terms of their instruments, communities and computing resources. Tackling the computational challenges in computational biology and bioinformatics increasingly requires high-end and distributed computing infrastructures, systems and tools.
Distributed computing and internet technology ; 17th International Conference, ICDCIT 2021, Bhubaneswar, India, January 7–10, 2021, Proceedings
This book constitutes the proceedings of the 17th International Conference on Distributed Computing and Internet Technology, ICDCIT 2020, held in Bhubaneswar, India, in January 2021. The 13 full papers presented together with 4 short papers were carefully reviewed and selected from 99 submissions. The papers were organized in topical sections named: invited talks, cloud computing and networks, distributed algorithms, concurrency and parallelism, graph algorithms and security, social networks and machine learning, and short papers.
Discovering Biomolecular Mechanisms with Computational Biology
In this anthology, leading researchers present critical reviews of methods and high-impact applications in computational biology that lead to results that also non-bioinformaticians must know to design efficient experimental research plans. Discovering Biomolecular Mechanisms with Computational Biology also summarizes non-trivial theoretical predictions for regulatory and metabolic networks that have received experimental confirmation. Discovering Biomolecular Mechanisms with Computational Biology is essential reading for life science researchers and higher-level students that work on biomolecular mechanisms and wish to understand the impact of computational biology for their success.
