The two-volume set LNBI 11465 and LNBI 11466 constitutes the proceedings of the 7th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2019, held in Granada, Spain, in May 2019. The total of 97 papers presented in the proceedings, was carefully reviewed and selected from 301 submissions. The papers are organized in topical sections as follows: Part I: High-throughput genomics: bioinformatics tools and medical applications; omics data acquisition, processing, and analysis; bioinformatics approaches for analyzing cancer sequencing data; next generation sequencing and sequence analysis; structural bioinformatics and function; telemedicine for smart homes and remote monitoring; clustering and analysis of biological sequences with optimization algorithms; and computational approaches for drug repurposing and personalized medicine. Part II: Bioinformatics for healthcare and diseases; computational genomics/proteomics; computational systems for modelling biological processes; biomedical engineering; biomedical image analysis; and biomedicine and e-health.

This book constitutes the refereed proceedings of the 4th International Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2016, held in Granada, Spain, in April 2016. The 69 papers presented were carefully reviewed and selected from 286 submissions. The scope of the conference spans the following areas: bioinformatics for healthcare and diseases; biomedical image analysis; biomedical signal analysis; computational systems for modeling biological processes; eHealth; tools for next generation sequencing data analysis; assistive technology for people with neuromotor disorders; fundamentals of biological dynamics and maximization of the information extraction from the experiments in the biological systems; high performance computing in bioinformatics, computational biology and computational chemistry; human behavior monitoring, analysis and understanding; pattern recognition and machine learning in the -omics sciences; and resources for bioinformatics.

Developments in the areas of biology and bioinformatics are continuously evolving and creating a plethora of data that needs to be analyzed and decrypted. Since it can be difficult to decipher the multitudes of data within these areas, new computational techniques and tools are being employed to assist researchers in their findings. The Handbook of Research on Computational Intelligence Applications in Bioinformatics examines emergent research in handling real-world problems through the application of various computation technologies and techniques. Featuring theoretical concepts and best practices in the areas of computational intelligence, artificial intelligence, big data, and bio-inspired computing, this publication is a critical reference source for graduate students, professionals, academics, and researchers.

Many aspects of modern life have become personalized, yet healthcare practices have been lagging behind in this trend. It is now becoming more common to use big data analysis to improve current healthcare and medicinal systems, and offer better health services to all citizens. Applying Big Data Analytics in Bioinformatics and Medicine is a comprehensive reference source that overviews the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Featuring coverage on relevant topics that include smart data, proteomics, medical data storage, and drug design, this publication is an ideal resource for medical professionals, healthcare practitioners, academicians, and researchers interested in the latest trends and techniques in personalized medicine.

As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge. In order to discover patterns and make relevant predictions based on large data sets, researchers and medical professionals must find new methods to analyze and extract relevant health information. Big Data Analytics in Bioinformatics and Healthcare merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management. Complete with interdisciplinary research resources, this publication is an essential reference source for researchers, practitioners, and students interested in the fields of biological computation, database management, and health information technology, with a special focus on the methodologies and tools to manage massive and complex electronic information.

Why are cutting-edge data science techniques such as bioinformatics, few-shot learning, and zero-shot learning underutilized in the world of biological sciences?. In a rapidly advancing field, the failure to harness the full potential of these disciplines limits scientists’ ability to unlock critical insights into biological systems, personalized medicine, and biomarker identification. This untapped potential hinders progress and limits our capacity to tackle complex biological challenges. The solution to this issue lies within the pages of Applying Machine Learning Techniques to Bioinformatics. This book serves as a powerful resource, offering a comprehensive analysis of how these emerging disciplines can be effectively applied to the realm of biological research. By addressing these challenges and providing in-depth case studies and practical implementations, the book equips researchers, scientists, and curious minds with the knowledge and techniques needed to navigate the ever-changing landscape of bioinformatics and machine learning within the biological sciences.

This book constitutes the refereed post-proceedings of the 15th International Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2022, held as a Virtual Event, during February 9–11, 2022. The 21 full papers included in this book were carefully reviewed and selected from 262 submissions. The papers selected to be included in this book contribute to the understanding of relevant trends of current research on Biomedical Engineering Systems and Technologies, including: Pattern Recognition and Machine Learning, Application of Health Informatics in Clinical Cases, Evaluation and Use of Healthcare IT, Medical Signal Acquisition, Analysis and Processing, Data Mining and Data Analysis, Decision Support Systems, e-Health, e-Health Applications, Mobile Technologies for Healthcare Applications and Medical Devices design.

Business intelligence (BI) tools are capable of working with healthcare data in an efficient manner to generate real-time information and knowledge relevant to the success of healthcare organizations. Further, BI tools benefit healthcare professionals making critical decisions within hospitals, clinics, and physicians’ offices. Applying Business Intelligence to Clinical and Healthcare Organizations presents new solutions for data analysis within the healthcare sector in order to improve the quality of medical care and patient quality of life. Business intelligence models and techniques are explored and their benefits for the healthcare sector exposed in this timely research-based publication comprised of chapters written by professionals and researchers from around the world. Hospital administrators, healthcare professionals, biomedical engineers, informatics engineers, and students in graduate-level healthcare management programs will find this publication essential to their professional development and research needs.

Biomedical signal processing in the medical field has helped optimize patient care and diagnosis within medical facilities. As technology in this area continues to advance, it has become imperative to evaluate other ways these computation techniques could be implemented. Computational Tools and Techniques for Biomedical Signal Processing investigates high-performance computing techniques being utilized in hospital information systems. Featuring comprehensive coverage on various theoretical perspectives, best practices, and emergent research in the field, this book is ideally suited for computer scientists, information technologists, biomedical engineers, data-processing specialists, and medical physicists interested in signal processing within medical systems and facilities.

Glial cells, including microglia, astrocytes, oligodendrocytes, and their progenitors NG2-glia, serve as key players in maintaining structural integrity and complex brain homeostasis. They actively participate in neurotransmission, energy metabolism, synaptic plasticity, neurogenesis, ion balance, immune defense, and the clearance of neuronal debris. However, the physiological functions of glial cells are often compromised in aging, neurodegenerative diseases such as Alzheimer's, Parkinson's, ALS, and multiple sclerosis, as well as in gliomas, brain tumors demanding specialized understanding for effective therapeutic interventions. Physiology and Function of Glial Cells in Health and Disease provides a comprehensive exploration of the vital role played by glial cells in maintaining neural homeostasis within the central nervous system (CNS). This book delves into the intricate interaction between glial cells and neurons, shedding light on their essential contributions to neural function and overall brain health. The book also highlights emerging research on astrocyte reprogramming for the management of neurodegenerative diseases, offering a glimpse into potential future therapies. This book is an essential resource for researchers, clinicians, and students in the field of neuroscience. Its academic tone, coupled with in-depth discussions and cutting-edge insights, makes it a valuable reference for anyone seeking a comprehensive understanding of the role of glial cells in both health and disease.