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Linking Phenotypes and Genotypes
The first book to comprehensively cover the field of systems genetics, gathering contributions from leading scientists.
Advances in Learning Theory
This text details advances in learning theory that relate to problems studied in neural networks, machine learning, mathematics and statistics.
Survival Guide for Early Career Researchers
Navigating research careers is often highly challenging for early career researchers (ECRs) in the social sciences. The ability to thrive in research careers is complex and requires "soft" people and management skills and resilience that often cannot be formally taught through university coursework. Written from a peer perspective, this book provides guidance and establishes emotional rapport on topical issues relevant for ECRs in academia and industry. The authors are ECRs who have been successful in navigating their careers, and they seek to connect with readers in a supportive and collegial manner. Each chapter includes elements of story-telling and scientific thinking and is organized in...
Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data
This book constitutes the refereed joint proceedings of the 4th International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, and the First International Workshop on Topological Data Analysis and Its Applications for Medical Data, TDA4MedicalData 2021, held on September 27, 2021, in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021. The 7 full papers presented at iMIMIC 2021 and 5 full papers held at TDA4MedicalData 2021 were carefully reviewed and selected from 12 submissions each. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. TDA4MedicalData is focusing on using TDA techniques to enhance the performance, generalizability, efficiency, and explainability of the current methods applied to medical data.
Mathematical and Computational Oncology
This book constitutes the refereed proceedings of the First International Symposium on Mathematical and Computational Oncology, ISMCO'2019, held in Lake Tahoe, NV, USA, in October 2019. The 7 full papers presented were carefully reviewed and selected from 30 submissions. The papers are organized in topical sections named: Tumor evolvability and intra-tumor heterogeneity; Imaging and scientific visualization for cancer research; Statistical methods and data mining for cancer research (SMDM); Spatio-temporal tumor modeling and simulation (STTMS).
Between Data Science and Applied Data Analysis
The volume presents new developments in data analysis and classification and gives an overview of the state of the art in these scientific fields and relevant applications. Areas that receive considerable attention in the book are clustering, discrimination, data analysis, and statistics, as well as applications in economics, biology, and medicine it provides recent technical and methodological developments and a large number of application papers demonstrating the usefulness of the newly developed techniques.
Algorithms in Bioinformatics
The refereed proceedings from the 7th International Workshop on Algorithms in Bioinformatics are provided in this volume. Papers address current issues in algorithms in bioinformatics, ranging from mathematical tools to experimental studies of approximation algorithms to significant computational analyses. Biological problems examined include genetic mapping, sequence alignment and analysis, phylogeny, comparative genomics, and protein structure.
Plainsong
National Book Award Finalist A heartstrong story of family and romance, tribulation and tenacity, set on the High Plains east of Denver. In the small town of Holt, Colorado, a high school teacher is confronted with raising his two boys alone after their mother retreats first to the bedroom, then altogether. A teenage girl—her father long since disappeared, her mother unwilling to have her in the house—is pregnant, alone herself, with nowhere to go. And out in the country, two brothers, elderly bachelors, work the family homestead, the only world they've ever known. From these unsettled lives emerges a vision of life, and of the town and landscape that bind them together—their fates somehow overcoming the powerful circumstances of place and station, their confusion, curiosity, dignity and humor intact and resonant. As the milieu widens to embrace fully four generations, Kent Haruf displays an emotional and aesthetic authority to rival the past masters of a classic American tradition.
Research in Computational Molecular Biology
This book constitutes the refereed proceedings of the 10th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2006, held in Venice, Italy in April 2006. The 40 revised full papers presented together with abstracts of 7 keynote talks were carefully reviewed and selected from 212 submissions. As the top conference in computational molecular biology, RECOMB addresses all current issues in algorithmic, theoretical, and experimental bioinformatics.
Statistical Diagnostics for Cancer
This ready reference discusses different methods for statistically analyzing and validating data created with high-throughput methods. As opposed to other titles, this book focusses on systems approaches, meaning that no single gene or protein forms the basis of the analysis but rather a more or less complex biological network. From a methodological point of view, the well balanced contributions describe a variety of modern supervised and unsupervised statistical methods applied to various large-scale datasets from genomics and genetics experiments. Furthermore, since the availability of sufficient computer power in recent years has shifted attention from parametric to nonparametric methods, the methods presented here make use of such computer-intensive approaches as Bootstrap, Markov Chain Monte Carlo or general resampling methods. Finally, due to the large amount of information available in public databases, a chapter on Bayesian methods is included, which also provides a systematic means to integrate this information. A welcome guide for mathematicians and the medical and basic research communities.
