Bioinformatik

This book explores the importance of Single Nucleotide Polymorphisms (SNPs) in biomedical research. As SNP technologies have evolved from labor intensive, expensive, time-consuming processes to relatively inexpensive methods, SNP discovery has exploded. In terms of human biology, this research, particularly since the completion of the Human Genome Project, has provided a detailed understanding of evolutionary forces that have generated SNPs. It also has shown how SNPs shape human variation. The ability to inexpensively generate and analyze vast amounts of genetic data is poised to transform our understanding of human evolution and biology. "e;Single Nucleotide Polymorphisms"e; covers a broad  survey of SNPs and their classification into synonymous and non-synonymous; the role of SNPs in human disease; case studies providing specific examples of synonymous and non-synonymous SNPs associated with human diseases or affecting therapeutic interventions; mechanisms by which synonymous mutations affect protein levels or protein folding which affect human physiology and response to therapy; and the role of SNPs in personalized medicine. Understanding what SNPs are, how they have been shaped is necessary for an increasingly expanding audience. This research will revolutionize the future of medicine. Chapter 4 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. SNPs Ability to Influence Disease Risk: Breaking the Silence on Synonymous Mutations in Cancer"e; is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Over the past decade, neuroproteomics has shed light on the molecular features of schizophrenia by depicting biological processes involved with its establishment, maintenance and treatment. These studies have also pointed to potential biomarkers applicable to diagnosis and medication monitoring. Edited by a leader in the field of neuroproteomics with contributions from subject experts, this new volume will address recent findings and compile evidence from difference perspectives-such as human samples, animal models, pluripotent stem cell-derived in vitro pre-clinical models-and provide findings to inform the development of innovative future treatment strategies.This volume will be useful for a broad audience of researchers and professionals, including biologists, neurologists, psychiatrists, analytical chemists, and pharmacists, among others.

This book gathers selected, extended and revised contributions to the 17th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering and the 5th Conference on Imaging and Visualization (CMBBE 2021), held online on September 7-9, 2021, from Bonn, Germany. It reports on cutting-edge models, algorithms and imaging techniques for studying cells, tissues and organs in normal and pathological conditions. It covers numerical and machine learning methods, finite element modeling and virtual reality techniques, applied to understand biomechanics of movement, fluid and soft tissue biomechanics. It also reports on related advances in rehabilitation, surgery and diagnosis. All in all, this book offers a timely snapshot of the latest research and current challenges at the interface between biomedical engineering, computational biomechanics and biological imaging. Thus, it is expected to provide a source of inspiration for future research and cross-disciplinary collaborations.

Computational Methods and Deep Learning for Ophthalmology presents readers with the concepts and methods needed to design and use advanced computer-aided diagnosis systems for ophthalmologic abnormalities in the human eye.  Chapters cover computational approaches for diagnosis and assessment of a variety of ophthalmologic abnormalities. Computational approaches include topics such as Deep Convolutional Neural Networks, Generative Adversarial Networks, Auto Encoders, Recurrent Neural Networks, and modified/hybrid Artificial Neural Networks. Ophthalmological abnormalities covered include Glaucoma, Diabetic Retinopathy, Macular Degeneration, Retinal Vein Occlusions, eye lesions, cataracts, and optical nerve disorders. This handbook provides biomedical engineers, computer scientists, and multidisciplinary researchers with a significant resource for addressing the increase in the prevalence of diseases such as Diabetic Retinopathy, Glaucoma, and Macular Degeneration.

This thorough book collects methods and strategies to analyze proteomics data. It is intended to describe how data obtained by gel-based or gel-free proteomics approaches can be inspected, organized, and interpreted to extrapolate biological information. Organized into four sections, the volume explores strategies to analyze proteomics data obtained by gel-based approaches, different data analysis approaches for gel-free proteomics experiments, bioinformatic tools for the interpretation of proteomics data to obtain biological significant information, as well as methods to integrate proteomics data with other omics datasets including genomics, transcriptomics, metabolomics, and other types of data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will ensure high quality results in the lab. Authoritative and practical, Proteomics Data Analysis serves as an idealguide to introduce researchers, both experienced and novice, to new tools and approaches for data analysis to encourage the further study of proteomics.Chapter 16 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book constitutes the refereed proceedings of the 10th International Workshop on Biomedical Image Registration, WBIR 2020, which was supposed to be held in Munich, Germany, in July 2022.The 11 full and poster papers together with 17 short papers included in this volume were carefully reviewed and selected from 32 submitted papers. The papers are organized in the following topical sections: optimization, deep learning architectures, neuroimaging, diffeomorphisms, uncertainty, topology and metrics.

This handbook covers tested and proven DNA forensic testing methodologies, forensic bioinformatics techniques, case studies and current forensic legal framework for investigation of variety of crimes and provides a clinching evidence for speedy justice. DNA testing is widely used for forensic purposes and is changing the paradigm of (crime) investigation. The book contains chapters on usage of ultramodern DNA collection kits, presents era evidence collection and preservation, high-end DNA sample analysis in laboratory, DNA legislation, expert evidences, challenging and successful case studies, data generation and application of AI and IoT techniques for DNA data analysis, DNA databanks and training manpower to facilitate timely reporting to the requesting agencies. This handbook equips and enables police, investigators and crime analysis laboratories with knowhow of high-end tools, procedures and techniques to link or exclude a criminal to a crime. It is expected that this will be used by first responders, police, forensic analysts, judiciaries, evidence handlers and students and scholars of criminology and forensic sciences worldwide. The intention to write this handbook is to make DNA technology and its importance reach every common man and professional for correctly using it as a tool as and when required. This is quite evident that awareness of DNA technology has increased at a reasonable pace. Courts and investigating agencies are convinced and confident with its accuracy, reliability and unmatched peace delivered by various techniques of DNA fingerprinting and DNA profiling.

Emery and Rimoin¿s Principles and Practice of Medical Genetics and Genomics: Developmental Disorders, Seventh Edition is distinguished as the ultimate resource for clinicians integrating genetics into medical practice. This updated edition includes the latest information on seminal topics such as prenatal diagnosis, genome and exome sequencing, public health genetics, genetic counseling, and management and treatment strategies. This comprehensive yet practical resource emphasizes theory and research fundamentals related to applications of medical genetics across the full spectrum of inherited disorders and applications in medicine more broadly. Users will find comprehensive sections on medical genetics applied to a range of developmental disorders and an emphasis on understanding the genetic mechanisms underlying these disorders, diagnostic approaches, and therapeutics that make use of current genomic technologies and translational studies. Updated chapters on human developmental genetics as well as the genetics of sexual development, clefting, dental, and craniofacial syndromes, craniosynostosis, rasopathies, sex-chromosome abnormalities, and autosomal deletions, among other disorders are included.

Bioinformatics, and by extension omic sciences - the collective disciplines that are dependent on the use of extensive datasets of biological information - present a challenge of data management for researchers all over the world. Big data collected as part of research projects and experiments can be complex, with several kinds of variables involved. Coupled with continuously changing bioinformatics and information technology tools, there is a need to bring a multidisciplinary approach into these fields.Advances in Bioinformatics, Biostatistics and Omic Sciences attempts to realize an integrated approach between all omic sciences, exploring innovative bioinformatics and biostatistical methodologies which enable researchers to unveil hidden sides of biological phenomena.This volume presents reviews on the following topics which give a glimpse of recent advances in the field: - New Integrated Mitochondrial DNA Bioinformatics Pipeline to Improve Quality Assessment of Putative Pathogenic Variants from NGS Experiments- Variant Calling on RNA Sequencing Data: State of Art and Future Perspectives- An innovative Gene Prioritization Pipeline for WES analyses- New Integrated Differential Expression Approach for RNA-Seq Data Analysis- Innovations in Data Visualization for Straightforward Interpretation of Nucleic Acid Omics OutcomesThis volume serves as a guide for graduate students in bioinformatics as well as researchers planning new projects as a part of their professional and academic activities.

As a baby, one of our earliest stimuli is that of human faces. We rapidly learn to identify, characterize and eventually distinguish those who are near and dear to us. We accept face recognition later as an everyday ability. We realize the complexity of the underlying problem only when we attempt to duplicate this skill in a computer vision system. This book is arranged around a number of clustered themes covering different aspects of face recognition. The first section presents an architecture for face recognition based on Hidden Markov Models; it is followed by an article on coding methods. The next section is devoted to 3D methods of face recognition and is followed by a section covering various aspects and techniques in video. Next short section is devoted to the characterization and detection of features in faces. Finally, you can find an article on the human perception of faces and how different neurological or psychological disorders can affect this.