Bücher von Khalid Raza

Dieses Buch umfasst und beschäftigt sich mit den jüngsten Fortschritten und modernsten Anwendungen von naturinspirierten Computertechniken (NIC) im Bereich der Bioinformatik und der Computerbiologie, die die medizinischen Wissenschaften bei verschiedenen klinischen Anwendungen unterstützen können. Dieser Sammelband befasst sich mit den grundlegenden Anwendungen, dem Umfang und den Zukunftsperspektiven von NIC-Techniken in der Bioinformatik, einschließlich der Erstellung von Genomprofilen, der Klassifizierung von Genexpressionsdaten, der DNA-Berechnung, der System- und Netzwerkbiologie, der Lösung von Komplikationen bei personalisierten Therapien, der antimikrobiellen Resistenz bei bakteriellen Krankheitserregern und der computergestützten Entwicklung von Arzneimitteln, deren Entdeckung und Therapie. Darüber hinaus wird die Rolle von NIC-Techniken bei verschiedenen Krankheiten und Störungen behandelt, einschließlich Krebserkennung und -diagnose, Brustkrebs, Erkennung von Lungenkrankheiten, Krankheits-Biomarkern und Identifizierung potenzieller Therapeutika.

This book encapsulates recent applications of CI methods in the field of computational oncology, especially cancer diagnosis, prognosis, and its optimized therapeutics.The cancer has been known as a heterogeneous disease categorized in several different subtypes. According to WHO's recent report, cancer is a leading cause of death worldwide, accounting for over 10 million deaths in the year 2020. Therefore, its early diagnosis, prognosis, and classification to a subtype have become necessary as it facilitates the subsequent clinical management and therapeutics plan. Computational intelligence (CI) methods, including artificial neural networks (ANNs), fuzzy logic, evolutionary computations, various machine learning and deep learning, and nature-inspired algorithms, have been widely utilized in various aspects of oncology research, viz. diagnosis, prognosis, therapeutics, and optimized clinical management. Appreciable progress has been made toward the understanding the hallmarks of cancer development, progression, and its effective therapeutics. However, notwithstanding the extrinsic and intrinsic factors which lead to drastic increment in incidence cases, the detection, diagnosis, prognosis, and therapeutics remain an apex challenge for the medical fraternity. With the advent in CI-based approaches, including nature-inspired techniques, and availability of clinical data from various high-throughput experiments, medical consultants, researchers, and oncologists have seen a hope to devise and employ CI in various aspects of oncology. The main aim of the book is to occupy state-of-the-art applications of CI methods which have been derived from core computer sciences to back medical oncology. This edited book covers artificial neural networks, fuzzy logic and fuzzy inference systems, evolutionary algorithms, various nature-inspired algorithms, and hybrid intelligent systems which are widely appreciated for the diagnosis, prognosis, and optimization of therapeutics of various cancers. Besides, this book also covers multi-omics exploration, gene expression analysis, gene signature identification of cancers, genomic characterization of tumors, anti-cancer drug design and discovery, drug response prediction by means of CI, and applications of IoT, IoMT, and blockchain technology in cancer research.

This book encapsulates and occupies recent advances and state-of-the-art applications of nature-inspired computing (NIC) techniques in the field of bioinformatics and computational biology, which would aid medical sciences in various clinical applications. This edited volume covers fundamental applications, scope, and future perspectives of NIC techniques in bioinformatics including genomic profiling, gene expression data classification, DNA computation, systems and network biology, solving personalized therapy complications, antimicrobial resistance in bacterial pathogens, and computer-aided drug design, discovery, and therapeutics. It also covers the role of NIC techniques in various diseases and disorders, including cancer detection and diagnosis, breast cancer, lung disorder detection, disease biomarkers, and potential therapeutics identifications.