Download or read book Model Based Hypothesis Testing in Biomedicine written by Rikard Johansson and published by Linköping University Electronic Press. This book was released on 2017-10-03 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: The utilization of mathematical tools within biology and medicine has traditionally been less widespread compared to other hard sciences, such as physics and chemistry. However, an increased need for tools such as data processing, bioinformatics, statistics, and mathematical modeling, have emerged due to advancements during the last decades. These advancements are partly due to the development of high-throughput experimental procedures and techniques, which produce ever increasing amounts of data. For all aspects of biology and medicine, these data reveal a high level of inter-connectivity between components, which operate on many levels of control, and with multiple feedbacks both between and within each level of control. However, the availability of these large-scale data is not synonymous to a detailed mechanistic understanding of the underlying system. Rather, a mechanistic understanding is gained first when we construct a hypothesis, and test its predictions experimentally. Identifying interesting predictions that are quantitative in nature, generally requires mathematical modeling. This, in turn, requires that the studied system can be formulated into a mathematical model, such as a series of ordinary differential equations, where different hypotheses can be expressed as precise mathematical expressions that influence the output of the model. Within specific sub-domains of biology, the utilization of mathematical models have had a long tradition, such as the modeling done on electrophysiology by Hodgkin and Huxley in the 1950s. However, it is only in recent years, with the arrival of the field known as systems biology that mathematical modeling has become more commonplace. The somewhat slow adaptation of mathematical modeling in biology is partly due to historical differences in training and terminology, as well as in a lack of awareness of showcases illustrating how modeling can make a difference, or even be required, for a correct analysis of the experimental data. In this work, I provide such showcases by demonstrating the universality and applicability of mathematical modeling and hypothesis testing in three disparate biological systems. In Paper II, we demonstrate how mathematical modeling is necessary for the correct interpretation and analysis of dominant negative inhibition data in insulin signaling in primary human adipocytes. In Paper III, we use modeling to determine transport rates across the nuclear membrane in yeast cells, and we show how this technique is superior to traditional curve-fitting methods. We also demonstrate the issue of population heterogeneity and the need to account for individual differences between cells and the population at large. In Paper IV, we use mathematical modeling to reject three hypotheses concerning the phenomenon of facilitation in pyramidal nerve cells in rats and mice. We also show how one surviving hypothesis can explain all data and adequately describe independent validation data. Finally, in Paper I, we develop a method for model selection and discrimination using parametric bootstrapping and the combination of several different empirical distributions of traditional statistical tests. We show how the empirical log-likelihood ratio test is the best combination of two tests and how this can be used, not only for model selection, but also for model discrimination. In conclusion, mathematical modeling is a valuable tool for analyzing data and testing biological hypotheses, regardless of the underlying biological system. Further development of modeling methods and applications are therefore important since these will in all likelihood play a crucial role in all future aspects of biology and medicine, especially in dealing with the burden of increasing amounts of data that is made available with new experimental techniques. Användandet av matematiska verktyg har inom biologi och medicin traditionellt sett varit mindre utbredd jämfört med andra ämnen inom naturvetenskapen, såsom fysik och kemi. Ett ökat behov av verktyg som databehandling, bioinformatik, statistik och matematisk modellering har trätt fram tack vare framsteg under de senaste decennierna. Dessa framsteg är delvis ett resultat av utvecklingen av storskaliga datainsamlingstekniker. Inom alla områden av biologi och medicin så har dessa data avslöjat en hög nivå av interkonnektivitet mellan komponenter, verksamma på många kontrollnivåer och med flera återkopplingar både mellan och inom varje nivå av kontroll. Tillgång till storskaliga data är emellertid inte synonymt med en detaljerad mekanistisk förståelse för det underliggande systemet. Snarare uppnås en mekanisk förståelse först när vi bygger en hypotes vars prediktioner vi kan testa experimentellt. Att identifiera intressanta prediktioner som är av kvantitativ natur, kräver generellt sett matematisk modellering. Detta kräver i sin tur att det studerade systemet kan formuleras till en matematisk modell, såsom en serie ordinära differentialekvationer, där olika hypoteser kan uttryckas som precisa matematiska uttryck som påverkar modellens output. Inom vissa delområden av biologin har utnyttjandet av matematiska modeller haft en lång tradition, såsom den modellering gjord inom elektrofysiologi av Hodgkin och Huxley på 1950?talet. Det är emellertid just på senare år, med ankomsten av fältet systembiologi, som matematisk modellering har blivit ett vanligt inslag. Den något långsamma adapteringen av matematisk modellering inom biologi är bl.a. grundad i historiska skillnader i träning och terminologi, samt brist på medvetenhet om exempel som illustrerar hur modellering kan göra skillnad och faktiskt ofta är ett krav för en korrekt analys av experimentella data. I detta arbete tillhandahåller jag sådana exempel och demonstrerar den matematiska modelleringens och hypotestestningens allmängiltighet och tillämpbarhet i tre olika biologiska system. I Arbete II visar vi hur matematisk modellering är nödvändig för en korrekt tolkning och analys av dominant-negativ-inhiberingsdata vid insulinsignalering i primära humana adipocyter. I Arbete III använder vi modellering för att bestämma transporthastigheter över cellkärnmembranet i jästceller, och vi visar hur denna teknik är överlägsen traditionella kurvpassningsmetoder. Vi demonstrerar också frågan om populationsheterogenitet och behovet av att ta hänsyn till individuella skillnader mellan celler och befolkningen som helhet. I Arbete IV använder vi matematisk modellering för att förkasta tre hypoteser om hur fenomenet facilitering uppstår i pyramidala nervceller hos råttor och möss. Vi visar också hur en överlevande hypotes kan beskriva all data, inklusive oberoende valideringsdata. Slutligen utvecklar vi i Arbete I en metod för modellselektion och modelldiskriminering med hjälp av parametrisk ”bootstrapping” samt kombinationen av olika empiriska fördelningar av traditionella statistiska tester. Vi visar hur det empiriska ”log-likelihood-ratio-testet” är den bästa kombinationen av två tester och hur testet är applicerbart, inte bara för modellselektion, utan också för modelldiskriminering. Sammanfattningsvis är matematisk modellering ett värdefullt verktyg för att analysera data och testa biologiska hypoteser, oavsett underliggande biologiskt system. Vidare utveckling av modelleringsmetoder och tillämpningar är därför viktigt eftersom dessa sannolikt kommer att spela en avgörande roll i framtiden för biologi och medicin, särskilt när det gäller att hantera belastningen från ökande datamängder som blir tillgänglig med nya experimentella tekniker.

Download or read book Interpreting Biomedical Science written by Ülo Maiväli and published by Academic Press. This book was released on 2015-06-12 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interpreting Biomedical Science: Experiment, Evidence, and Belief discusses what can go wrong in biological science, providing an unbiased view and cohesive understanding of scientific methods, statistics, data interpretation, and scientific ethics that are illustrated with practical examples and real-life applications. Casting a wide net, the reader is exposed to scientific problems and solutions through informed perspectives from history, philosophy, sociology, and the social psychology of science. The book shows the differences and similarities between disciplines and different eras and illustrates the concept that while sound methodology is necessary for the progress of science, we cannot succeed without a right culture of doing things. Features theoretical concepts accompanied by examples from biological literature Contains an introduction to various methods, with an emphasis on statistical hypothesis testing Presents a clear argument that ties the motivations and ethics of individual scientists to the success of their science Provides recommendations on how to safeguard against scientific misconduct, fraud, and retractions Arms young scientists with practical knowledge that they can use every day

Download or read book Statistical Models and Methods for Biomedical and Technical Systems written by Filia Vonta and published by Springer Science & Business Media. This book was released on 2008-03-05 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the mathematical aspects of survival analysis and reliability as well as other topics, reflecting recent developments in the following areas: applications in epidemiology; probabilistic and statistical models and methods in reliability; models and methods in survival analysis, longevity, aging, and degradation; accelerated life models; quality of life; new statistical challenges in genomics. The work will be useful to a broad interdisciplinary readership of researchers and practitioners in applied probability and statistics, industrial statistics, biomedicine, biostatistics, and engineering.

Download or read book Statistical Methods For Biomedical Research written by Ji-qian Fang and published by World Scientific. This book was released on 2021-03-18 with total page 1159 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of four parts with 32 chapters adapted for four short courses, from the basic to the advanced levels of medical statistics (biostatistics), ideal for biomedical students. Part 1 is a compulsory course of Basic Statistics with descriptive statistics, parameter estimation and hypothesis test, simple correlation and regression. Part 2 is a selective course on Study Design and Implementation with sampling survey, interventional study, observational study, diagnosis study, data sorting and article writing. Part 3 is a specially curated course of Multivariate Analyses with complex analyses of variance, variety of regressions and classical multivariate analyses. Part 4 is a seminar course on Introduction to Advanced Statistical Methods with meta-analysis, time series, item response theory, structure equation model, multi-level model, bio-informatics, genetic statistics and data mining.The main body of each chapter is followed by five practical sections: Report Writing, Case Discrimination, Computer Experiments, Frequently Asked Questions and Summary, and Practice & Think. Moreover, there are 2 attached Appendices, Appendix A includes Introductions to SPSS, Excel and R respectively, and Appendix B includes all the programs, data and printouts for Computer Experiments in addition to the Tests for Review and the reference answers for Case Discrimination as well as Practice & Think..This book can be used as a textbook for biomedical students at both under- and postgraduate levels. It can also serve as an important guide for researchers, professionals and officers in the biomedical field.

Download or read book Good Research Practice in Non Clinical Pharmacology and Biomedicine written by Anton Bespalov and published by Springer Nature. This book was released on 2020-01-01 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book, published under a CC BY 4.0 license in the Pubmed indexed book series Handbook of Experimental Pharmacology, provides up-to-date information on best practice to improve experimental design and quality of research in non-clinical pharmacology and biomedicine.

Download or read book Epistemology of the Cell written by Edward R. Dougherty and published by John Wiley & Sons. This book was released on 2011-08-17 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Honorable mention – Biomedicine and Neuroscience, 2011 Prose Awards" An examination of how the cell should be described in order to effectively process biological data "The fruitful pursuit of biological knowledge requires one to take Einstein's admonition [on science without epistemology] as a practical demand for scientific research, to recognize Waddington's characterization of the subject matter of biology, and to embrace Wiener's conception of the form of biological knowledge in response to its subject matter. It is from this vantage point that we consider the epistemology of the cell." —from the Preface In the era of high biological data throughput, biomedical engineers need a more systematic knowledge of the cell in order to perform more effective data handling. Epistemology of the Cell is the first authored book to break down this knowledge. This text examines the place of biological knowledge within the framework of science as a whole and addresses issues focused on the specific nature of biology, how biology is studied, and how biological knowledge is translated into applications, in particular with regard to medicine. The book opens with a general discussion of the historical development of human understanding of scientific knowledge, the scientific method, and the manner in which scientific knowledge is represented in mathematics. The narrative then gets specific for biology, focusing on knowledge of the cell, the basic unit of life. The salient point is the analogy between a systems-based analysis of factory regulation and the regulation of the cell. Each chapter represents a key topic of current interest, including: Causality and randomness Translational science Stochastic validation: classification Stochastic validation: networks Model-based experimentation in biology Epistemology of the Cell is written for biomedical researchers whose interests include bioinformatics, biological modeling, biostatistics, and biological signal processing.

Download or read book Empirical Likelihood Methods in Biomedicine and Health written by Albert Vexler and published by CRC Press. This book was released on 2018-09-03 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empirical Likelihood Methods in Biomedicine and Health provides a compendium of nonparametric likelihood statistical techniques in the perspective of health research applications. It includes detailed descriptions of the theoretical underpinnings of recently developed empirical likelihood-based methods. The emphasis throughout is on the application of the methods to the health sciences, with worked examples using real data. Provides a systematic overview of novel empirical likelihood techniques. Presents a good balance of theory, methods, and applications. Features detailed worked examples to illustrate the application of the methods. Includes R code for implementation. The book material is attractive and easily understandable to scientists who are new to the research area and may attract statisticians interested in learning more about advanced nonparametric topics including various modern empirical likelihood methods. The book can be used by graduate students majoring in biostatistics, or in a related field, particularly for those who are interested in nonparametric methods with direct applications in Biomedicine.

Download or read book Natural and Artificial Computation for Biomedicine and Neuroscience written by José Manuel Ferrández Vicente and published by Springer. This book was released on 2017-06-10 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volumes LNCS 10337 and 10338 constitute the proceedings of the International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2017, held in Corunna, Spain, in June 2017. The total of 102 full papers was carefully reviewed and selected from 194 submissions during two rounds of reviewing and improvement. The papers are organized in two volumes, one on natural and artificial computation for biomedicine and neuroscience, addressing topics such as theoretical neural computation; models; natural computing in bioinformatics; physiological computing in affective smart environments; emotions; as well as signal processing and machine learning applied to biomedical and neuroscience applications. The second volume deals with biomedical applications, based on natural and artificial computing and addresses topics such as biomedical applications; mobile brain computer interaction; human robot interaction; deep learning; machine learning applied to big data analysis; computational intelligence in data coding and transmission; and applications.

Download or read book Image Analysis and Modeling in Ophthalmology written by Eddie Y. K. Ng and published by CRC Press. This book was released on 2014-02-11 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Successful thermal modeling of the human eye helps in the early diagnosis of eye abnormalities such as inflammation, cataracts, diabetic retinopathy, and glaucoma-all leading causes of blindness. This book presents a unified work of eye imaging and modeling techniques that have been proposed and applied to ophthalmologic problems. It delves into various morphological, texture, higher order spectra, and wavelet transformation techniques used to extract important diagnostic features from images, which can then be analyzed by a data scientist for automated diagnosis.

Download or read book Some Hypothesis Testing Results for Two way Linear Models in Clinical Trials written by Bin Cheng and published by . This book was released on 2004 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Hypothesis Testing in a Mixed Model Based on Conditional Specification written by Ali.Mohammed Asghar and published by . This book was released on 1978 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Biomedical Models and Resources written by National Research Council and published by National Academies Press. This book was released on 1998-02-16 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: Printbegrænsninger: Der kan printes 10 sider ad gangen og max. 40 sider pr. session.

Download or read book Modeling in Computational Biology and Biomedicine written by Frédéric Cazals and published by Springer Science & Business Media. This book was released on 2012-11-06 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational biology, mathematical biology, biology and biomedicine are currently undergoing spectacular progresses due to a synergy between technological advances and inputs from physics, chemistry, mathematics, statistics and computer science. The goal of this book is to evidence this synergy by describing selected developments in the following fields: bioinformatics, biomedicine and neuroscience. This work is unique in two respects - first, by the variety and scales of systems studied and second, by its presentation: Each chapter provides the biological or medical context, follows up with mathematical or algorithmic developments triggered by a specific problem and concludes with one or two success stories, namely new insights gained thanks to these methodological developments. It also highlights some unsolved and outstanding theoretical questions, with a potentially high impact on these disciplines. Two communities will be particularly interested in this book. The first one is the vast community of applied mathematicians and computer scientists, whose interests should be captured by the added value generated by the application of advanced concepts and algorithms to challenging biological or medical problems. The second is the equally vast community of biologists. Whether scientists or engineers, they will find in this book a clear and self-contained account of concepts and techniques from mathematics and computer science, together with success stories on their favorite systems. The variety of systems described represents a panoply of complementary conceptual tools. On a practical level, the resources listed at the end of each chapter (databases, software) offer invaluable support for getting started on a specific topic in the fields of biomedicine, bioinformatics and neuroscience.

Download or read book Hypothesis Testing Based on Ranks in Multivariate Linear Models written by Enoch B. Bortey and published by . This book was released on 1990 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Information Technology in Biomedicine written by Ewa Pietka and published by Springer. This book was released on 2019-06-26 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of advances in the field of medical data science, presenting carefully selected articles by leading information technology experts. Information technology, as a rapidly evolving discipline in medical data science, with significant potential in future healthcare, and multimodal acquisition systems, mobile devices, sensors, and AI-powered applications has redefined the optimization of clinical processes. This book features an interdisciplinary collection of papers that have both theoretical and applied dimensions, and includes the following sections: Medical Data Science Quantitative Data Analysis in Medical Diagnosis Data Mining Tools and Methods in Medical Applications Image Analysis Analytics in Action on SAS Platform Biocybernetics in Physiotherapy Signal Processing and Analysis Medical Tools & Interfaces Biomechanics and Biomaterials. As such, it is a valuable reference tool for scientists designing and implementing information processing tools used in systems that assist clinicians in patient care. It is also useful for students interested in innovations in quantitative medical data analysis, data mining, and artificial intelligence.

Download or read book Clinical Data Analysis on a Pocket Calculator written by Ton J. M. Cleophas and published by . This book was released on 2016 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: In everyone's life the day comes that medical and health care has the highest priority. It is unbelievable, that a field, so important, uses the scientific method so little. The current book is helpful for implementation of the scientific method in the daily life of medical and health care workers. From readers' comments to the first editions of this work, the authors came to realize that statistical software programs is experienced by professionals in the field as black box programs producing lots of p-values, but little answers to scientific questions, and many readers had not been happy with that situation. The pocket calculator analyses appeared to be, particularly, appreciated, because they enabled readers for the first time to understand the scientific methods of statistical reasoning and hypothesis testing. So much so, that it started something like a new dimension in their professional world. We should add a number of statistical methods can be performed more easily on a pocket calculator, than using a software program. Also, there are some specific advantages of the pocket calculator method. You better understand what you are doing. The pocket calculator works faster, because far less steps have to be taken, averages can be used. With statistical software all individual data have to be included separately, a time-consuming activity in case of large data files. Some analytical methods, for example, power calculations and required sample size calculations are difficult on a statistical software program, and easy on a pocket calculator. The reason for a rewrite was to give updated and upgraded versions of the forty chapters from the first editions, including the valuable comments of readers. Like in the textbook complementary to the current work, entitled "SPSS for Starters and 2nd Levelers" (Springer Heidelberg 2015, from the same authors), an improved structure of the chapters was produced, including background, main purpose, scientific question, schematic overview of data files, and reference sections. In addition, for the analysis of more complex data twenty novel chapters were written. We showed that, also here, a pocket calculator can be very helpful. For the readers' convenience the chapters have been reclassified according to the most basic difference in data characteristics: continuous outcome data (34 chapters), binary outcome data (26 chapters). Both hypothesized and real data examples are used to explain the sixty pocket calculator methods described. The arithmetic is of a no-more-than high-school level.

Download or read book Handbook of Research on Informatics in Healthcare and Biomedicine written by Lazakidou, Athina A. and published by IGI Global. This book was released on 2006-06-30 with total page 479 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes and analyzes recent breakthroughs in healthcare and biomedicine providing comprehensive coverage and definitions of important issues, concepts, new trends and advanced technologies.