Recombinant Protein Expression, Part B, Volume 660 in the Methods in Enzymology series, highlights new advances in the field with this new volume presenting interesting chapters on Multiplexed analysis protein: Protein interactions of polypeptides translated in Leishmania cell-free system, MultiBac system and its applications, performance and recent, Production of antibodies in Shuffle, Designing hybrid-promoter architectures by engineering cis-acting DNA sites to enhance transcription in yeast, Designing hybrid-promoter architectures by engineering cis-acting DNA sites to deregulate transcription in yeast, Antibody or protein-based vaccine production in plants, Cell-free protein synthesis, Plant-based expression of biologic drugs, and much more. Additional sections cover the Use of native mass spectrometry to guide detergent-based rescue of non-native oligomerization by recombinant proteins, Advancing overexpression and purification of recombinant proteins by pilot optimization through tandem affinity-buffer exchange chromatography online with native mass spectrometry, Method for High-Efficiency Fed-batch cultures of recombinant Escherichia coli, Method to transfer Chinese hamster ovary (CHO) shake flask experiments to the ambr (R) 250, and Expression of recombinant antibodies in Leishmania tarentolae.

The book presents a comprehensive and up-to-date overview of phytochemicals as efficient cancer therapeutics. Over the last few decades there has been a paradigm shift from conventional cancer therapeutic approaches to alternative and complementary medicinal approaches especially using phytoconstituents from natural products. As such, the book provides an in-depth understanding of phytochemicals targeting diverse signaling pathways involved in cancer along with the evaluation of the cancer modulatory effects of phytochemicals. It also highlights the potential modulatory effect of single nucleotide polymorphisms (SNPs) on the cancer-associated cellular pathways and their interactions with the phytochemicals. Further, it analyzes the drug delivery methods, bioavailability of active components of botanicals, and toxicity of phytochemicals. Lastly, the book elucidates the 3D cell culture and animal models systems to analyze the beneficial effects of phytochemicals in cancer.

Protein Interaction Networks, Volume 131 in the Advances in Protein Chemistry and Structural Biology series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors.

In studying biology, one of the more difficult factors to predict is how parents' attributes will affect their children and how those children will affect their own children. Organizing and calculating those vast statistics can become extremely tedious without the proper mathematical and reproductive knowledge. Attractors and Higher Dimensions in Population and Molecular Biology: Emerging Research and Opportunities is a collection of innovative research on the methods and applications of population logistics. While highlighting topics including gene analysis, crossbreeding, and reproduction, this book is ideally designed for academics, researchers, biologists, and mathematicians seeking current research on modeling the reproduction process of a biological population.

With the rapid development of biotechnologies, single-cell sequencing has become an important tool for understanding the molecular mechanisms of diseases, defining cellular heterogeneities and characteristics, and identifying intercellular communications and single-cell-based biomarkers. Providing a clear overview of the clinical applications, the book presents state-of-the-art information on immune cell function, cancer progression, infection, and inflammation gained from single-cell DNA or RNA sequencing. Furthermore, it explores the role of target gene methylation in the pathogenesis of diseases, with a focus on respiratory cancer, infection and chronic diseases. As such it is a valuable resource for clinical researchers and physicians, allowing them to refresh their knowledge and improve early diagnosis and therapy for patients.

Population genomics is revolutionizing wildlife biology, conservation, and management by providing key and novel insights into genetic, population and landscape-level processes in wildlife, with unprecedented power and accuracy. This pioneering book presents the advances and potential of population genomics in wildlife, outlining key population genomics concepts and questions in wildlife biology, population genomics approaches that are specifically applicable to wildlife, and application of population genomics in wildlife population and evolutionary biology, ecology, adaptation and conservation and management. It is important for students, researchers, and wildlife professionals to understand the growing set of population genomics tools that can address issues from delineation of wildlife populations to assessing their capacity to adapt to environmental change. This book brings together leading experts in wildlife population genomics to discuss the key areas of the field, as well as challenges, opportunities and future prospects of wildlife population genomics.

This book is the first overview on Deep Learning (DL) for biomedical data analysis. It surveys the most recent techniques and approaches in this field, with both a broad coverage and enough depth to be of practical use to working professionals. This book offers enough fundamental and technical information on these techniques, approaches and the related problems without overcrowding the reader's head. It presents the results of the latest investigations in the field of DL for biomedical data analysis. The techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine fundamental theory of Artificial Intelligence (AI), Machine Learning (ML) and DL with practical applications in Biology and Medicine. Certainly, the list of topics covered in this book is not exhaustive but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis. The book finds a balance between theoretical and practical coverage of a wide range of issues in the field of biomedical data analysis, thanks to DL. The few published books on DL for biomedical data analysis either focus on specific topics or lack technical depth. The chapters presented in this book were selected for quality and relevance. The book also presents experiments that provide qualitative and quantitative overviews in the field of biomedical data analysis. The reader will require some familiarity with AI, ML and DL and will learn about techniques and approaches that deal with the most important and/or the newest topics encountered in the field of DL for biomedical data analysis. He/she will discover both the fundamentals behind DL techniques and approaches, and their applications on biomedical data. This book can also serve as a reference book for graduate courses in Bioinformatics, AI, ML and DL. The book aims not only at professional researchers and practitioners but also graduate students, senior undergraduate students and young researchers. This book will certainly show the way to new techniques and approaches to make new discoveries.

Although the phenomenon of lateral gene transfer has been known since the 1940's, it was the genomics era that has really revealed the extent and many facets of this evolutionary/genetic phenomenon. Even in the early 2000s with but a handful of genomes available it became clear that the nature of microorganisms is full of genetic exchange between lineages that are sometimes far apart. The years following this saw an explosion of genomic data, which shook the "tree of life" and also raised doubts about the most appropriate species concepts for prokaryotes. This book attempts to represent the many-fold contributions of LGT to the evolution of micro and, to an extent, macro-organisms by focusing on the areas where the Editor felt it had the largest impact: metabolic innovations and adaptations and speciation.

This book compiles recent research on the modification of nucleic acids. It covers backbone modifications and conjugation of lipids, peptides and proteins to oligonucleotides and their therapeutic use. Synthesis and application in biomedicine and nanotechnology of aptamers, fluorescent and xeno nucleic acids, DNA repair and artificial DNA are discussed as well.

This book reviews important aspects of polycystic kidney diseases, the latest scientific understanding of the diseases and syndromes, along with the therapies being developed. Cystic kidney diseases comprise a spectrum of genetic syndromes defined by renal cyst formation and expansion with variable extrarenal manifestations. The most prevalent disorder is the autosomal dominant polycystic kidney disease (ADPKD). It is the most common monogenetic disorder in humans and accounts for 4.4% of end-stage renal disease (ESRD) cases in the U.S. Patients inevitably progress to ESRD and require renal replacement therapy in the form of dialysis or transplantation. Through advancements in genomics and proteomics approaches, novel genes responsible for cystic diseases have been identified, further expanding our understanding of basic mechanisms of disease pathogenesis. The hallmark among all cystic genetic syndromes is the formation and growth of fluid-filled cysts, which originate from tubular epithelia of nephron segments. Cysts are the disease, and treatment strategies are being developed to target prevention or delay of cyst formation and expansion at an early stage, however no such therapy is currently approved.

This open access volume presents state-of-the-art inference methods in population genomics, focusing on data analysis based on rigorous statistical techniques. After introducing general concepts related to the biology of genomes and their evolution, the book covers state-of-the-art methods for the analysis of genomes in populations, including demography inference, population structure analysis and detection of selection, using both model-based inference and simulation procedures. Last but not least, it offers an overview of the current knowledge acquired by applying such methods to a large variety of eukaryotic organisms. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, pointers to the relevant literature, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Statistical Population Genomics aims to promote and ensure successful applications of population genomic methods to an increasing number of model systems and biological questions.

Advances in biochemistry now allow us to control living systems in ways that were undreamt of a decade ago. This volume guides researchers and students through the full spectrum of experimental protocols used in biochemistry, plant biology and biotechnology.

Control of Cell Cycle & Cell Proliferation, Volume 135 in the Advances in Protein Chemistry and Structural Biology series, highlights new advances, with this new volume presenting chapters on a variety of timely topics, including Exploiting pivotal mechanisms behind the senescence-like cell cycle arrest, Viral infection on through Cell Cycle Regulation, Analyzing drug resistant mutation in CDK4 gene and identification of potential inhibitors through structure based virtual screening approach, Controlling cell proliferation by targeting CDK6 using drug repurposing approach, Cdk Regulators: Growth Arrest or Apoptosis? Scenarios in normal and cancerous cells, Targeting cell cycle signaling pathways for cancer therapy, and much more. Other sections focus on The role of the nucleolus in regulating cell cycle, Chromatin regulators in DNA replication and genome stability maintenance during S-phase, Role of macrophage in cancer cell progression and targeted immunotherapies, Anti-cancer drug molecules targeting cancer cell cycle and proliferation, Cellular signals integrate cell cycle and metabolic control in cancer, Therapeutic targeting and proliferation of HSCs by small molecules and biologicals, Mechanism of cell cycle regulation and cell proliferation during human viral infection, and Cyclin-dependent kinases: Role, regulation, and therapeutic targets in cancer.

Delivering fundamental insights into the most popular methods of molecular analysis, this text is an invaluable resource for students and researchers. It encompasses an extensive range of spectroscopic and spectrometric techniques used for molecular analysis in the life sciences, especially in the elucidation of the structure and function of biological molecules. Covering the range of up-to-date methodologies from everyday mass spectrometry and centrifugation to the more probing X-ray crystallography and surface-sensitive techniques, the book is intended for undergraduates starting out in the laboratory and for more advanced postgraduates pursuing complex research goals. The comprehensive text provides strong emphasis on the background principles of each method, including equations where they are of integral importance to the individual techniques. With sections on all the major procedures for analysing biological molecules, this book will serve as a useful guide across a range of fields, from new drug discovery to forensics and environmental studies.

Protein Design and Structure, Volume 130 in the Advances in Protein Chemistry and Structural Biology series, highlights new advances in the field, with this new volume presenting interesting chapters. Each chapter is written by an international board of authors.

This book reviews the recent research into biological aspects of suicide behavior and outlines each of the varied, recent approaches to prevent suicide. Suicidal behavior, perhaps, is the most complex behavior that combines biological, social, and psychological factors. A new frontier and new opportunities are opening with the technologies of data acquisition and data analysis. Personalized models based on digital phenotype could provide promising strategies for preventing suicide.