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Information criteria and statistical modeling
One of the main objectives of this book is to provide comprehensive explanations of the concepts and derivations of the AIC and related criteria, including Schwarz’s Bayesian information criterion (BIC), together with a wide range of practical examples of model selection and evaluation criteria. A secondary objective is to provide a theoretical basis for the analysis and extension of information criteria via a statistical functional approach. A generalized information criterion (GIC) and a bootstrap information criterion are presented, which provide unified tools for modeling and model evaluation for a diverse range of models, including various types of nonlinear models and model estimation procedures such as robust estimation, the maximum penalized likelihood method and a Bayesian approach.
Information and Complexity in Statistical Modeling
The main theme in this book is to teach modeling based on the principle that the objective is to extract the information from data that can be learned with suggested classes of probability models. The intuitive and fundamental concepts of complexity, learnable information, and noise are formalized, which provides a firm information theoretic foundation for statistical modeling.
Inference in Hidden Markov Models
This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states.In a unified way the book covers both models with finite state spaces, which allow for exact algorithms for filtering, estimation etc. and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Simulation in hidden Markov models is addressed in five different chapters that cover both Markov chain Monte Carlo and sequential Monte Carlo approaches. Many examples illustrate the algorithms and theory. The book also carefully treats Gaussian linear state-space models and their extensions and it contains a chapter on general Markov chain theory and probabilistic aspects of hidden Markov models.
Inductive logic programming ; 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers
This book constitutes the thoroughly refereed post-proceedings of the 16th International Conference on Inductive Logic Programming, ILP 2006, held in Santiago de Compostela, Spain, in August 2006. The papers address all current topics in inductive logic programming, ranging from theoretical and methodological issues to advanced applications.
Independent component analysis and signal separation ; 7th International Conference, ICA 2007, London, UK, September 9-12, 2007, Proceedings
Independent Component Analysis and Signal Separation has applications at the intersection of many science and engineering disciplinesconcernedwithunderstandingandextractingusefulinformationfrom data as diverse as neuronal activity and brain images, bioinformatics, com- nications, the World Wide Web, audio, video, sensor signals, or time series.
Implementation and application of automata ; 12th International Conference, CIAA 2007, Prague, Czech Republic, July 16-18, 2007, Revised Selected Papers
The 12th International Conference on Implementation and Application of - tomata CIAA 2007 washeld at the Czech Technical Universityin Prague,Czech Republic on July 16–18, 2007. These proceedings contain the papers that were presented at CIAA 2007, as well as the abstracts of the poster papers that were displayed during the conference.
Immunoinformatics
Immunoinformatics is an emerging subdiscipline of bioinformatics. It utilizes mathematics, information science, computer engineering, genomics, proteomics and immunological methods to bridge immunology and informatics. Similar to bioionformatics which became a driving force in genome research, immunoinformatics enables data-driven research strategies and systems approaches that aim at understanding the networks regulating the immune system. Considering the breath of topic, Immunoinformatics was composed to provide a cross-section of research ranging from data integration, epitope predictions to systems level applications. In ten chapters experts in the field introduce and discuss research strategies for immunologists and bioinformaticians who wish to endeavour existing and new approaches to gain insight into the workings of the immune system.
Immunogenetics: Methods and Protocols
Explores techniques for working in the field of immunogenetics, i.e. fundamental and translational research into the adaptive immune receptor repertoire. Many chapters are dedicated to lab protocols, bioinformatics, and immunoinformatics analysis of high-resolution immunome analysis, exemplified by numerous applications. Additionally, the newest technological variations on these protocols are discussed, including non-amplicon, single-cell, and cell-free strategies. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.
Immune mediators in cancer : Methods and protocols
Provides a comprehensive collection of classic and cutting-edge methodologies as well as bioinformatics and genome-editing approaches that are used to quantify immune mediators and analyze their function and biological activity in cancer cells and tissues. Beginning with a section on the detection of immune mediators in samples, the volume continues with sections covering cytokine bioassays, the expression and regulation of immune mediators in cancer cells, and methods to navigate the enormous datasets created by modern DNA and RNA sequencing and proteomic technology. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.
Homology modeling : Methods and protocols
It Provides state-of-the-art methodologies and reviews of important topics in the field of homology modeling. From homology modeling in the twilight zone and improving accuracy through sequence space analysis to approaches to construct multi-protein complex models, the book explores a wide variety of uses and applications of this valuable technique.
High-Performance Modelling and Simulation for Big Data Applications: Selected Results of the COST Action IC1406 cHiPSet
This book is the final compendium of case studies emanated from “High-Performance Modelling and Simulation for Big Data Applications” (cHiPSet).cHiPSet has created a sustainable reference network linking applied research in High Performance Computing (HPC) and Modelling & Simulation to tangibly address Big Data challenges.cHiPSet has also endeavoured to use and exploit results through Open Science practices, i.e., open access publication, open access to data repositories, and open-source software development. A testament to this philosophy, this compendium is set to become a required reference for the fast-changing fields of HPC, Big Data, and Modelling & Simulation.
High performance computing for drug discovery and biomedicine
Explores the application of high-performance computing (HPC) technologies to computational drug discovery (CDD) and biomedicine. Collects CDD approaches that, together with HPC, can revolutionize and automate drug discovery process, such as knowledge graphs, natural language processing (NLP), Bayesian optimization, automated virtual screening platforms, alchemical free energy workflows, fragment-molecular orbitals (FMO), HPC-adapted molecular dynamic simulation (MD-HPC), and the potential of cloud computing for drug discovery. And delves into computational algorithms and workflows for biomedicine, featuring an HPC framework to assess drug-induced arrhythmic risk, digital patient applications relevant to the clinic, virtual human simulations, cellular and whole-body blood flow modeling for stroke treatments, prediction of the femoral bone strength from CT data, and many more subjects.
Health Information Science ; 9th International Conference, HIS 2020, Amsterdam, The Netherlands, October 20–23, 2020, Proceedings
This book constitutes the proceedings of the 9th International Conference on Health Information Science, HIS 2020, which took place in Amsterdam, The Netherlands, during October 20-23, 2020. The 11 full papers and 6 short papers presented in this volume were carefully reviewed and selected from 62 submissions. They were organized in topical sections named: mental health; medical record processing; medical information systems; medical diagnosis with machine learning; and health behavior and medication.
Handbook of Nature-Inspired and Innovative Computing : Integrating Classical Models with Emerging Technologies
This comprehensive handbook, the first of its kind to address the connection between nature-inspired and traditional computational paradigms, is a repository of case studies dealing with different problems in computing and solutions to these problems based on nature-inspired paradigms. The "Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies" is an essential compilation of models, methods, and algorithms for researchers, professionals, and advanced-level students working in all areas of computer science, IT, biocomputing, and network engineering.
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.
Graph-theoretic concepts in computer science ; 30th International workshop, WG 2004, Bad Honnef, Germany, June 21-23, 2004, Revised Papers
During its 30-year existence, the International Workshop on Graph-Theoretic Concepts in Computer Science has become a distinguished and high-quality computer science event. The workshop aims at uniting theory and practice by demonstrating how graph-theoretic concepts can successfully be applied to v- ious areas of computer science and by exposing new theories emerging from applications. In this way, WG provides a common ground for the exchange of information among people dealing with several graph problems and working in various disciplines. Thereby, the workshop contributes to forming an interdis- plinary research community. The original idea of the Workshop on Graph-Theoretic Concepts in C- puter Science was ingenuity in all theoretical aspects and applications of graph concepts, wherever applied. Within the last ten years, the development has strengthened in particular the topic of structural graph properties in relation to computational complexity.
Global optimization ; Vol. 85 : Scientific and engineering case studies
Optimization models based on a nonlinear systems description often possess multiple local optima. The objective of global optimization (GO) is to find the best possible solution of multiextremal problems. Global Optimization: Selected Case Studies illustrates the applicability of GO modeling techniques and solution strategies to real-world problems.The contributed chapters cover a broad range of applications from agroecosystem management, assembly line design, bioinformatics, biophysics, black box systems optimization, cellular mobile network design, chemical process optimization, chemical product design, composite structure design, computational modeling of atomic and molecular structures, controller design for induction motors, electrical engineering design, feeding strategies in animal husbandry, the inverse position problem in kinematics, laser design, learning in neural nets, mechanical engineering design, numerical solution of equations, radiotherapy planning, robot design, and satellite data analysis. The solution strategies discussed encompass a range of practically viable methods, including both theoretically rigorous and heuristic approaches.
Genomics of Disease
Genomics of Disease is the 24th volume in the Stadler Genetics Symposium series published by Springer, which has, over many years, served as a comprehensive collection of current trends and hot topics in the field of genetics. The current volume summarizes recent progress in our attempts to characterize the genomics of plant and animal diseases. Authoritative analytical reviews are specialized to be attractive to professional researchers, teachers, and students, while also being appealing to a wider audience of scientists in related disciplines. Genomics of Disease offers essential reference material for any scientist or teacher working in the fields of plant and animal diseases. Coverage of key areas of both animal and plant disease is a unique feature of this volume and one that allows direct comparisons between the systems. All academics, scientists, and industry professionals that desire to take advantage of the most up-to-date information on the continuously emerging and expanding field of the genomics of plant and animal diseases will find it an invaluable resource.
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.
Genetic Programming Theory and Practice V
Genetic Programming Theory and Practice V was developed from the fifth workshop at the University of Michigan’s Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP). Contributions from the foremost international researchers and practitioners in the GP arena examine the similarities and differences between theoretical and empirical results on real-world problems. The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application.
