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| dna vs rna venn diagram: Plants, Stress & Proteins Dipanjana Ghosh, Qingsong Lin, Jian Xu, Hanjo A. Hellmann, 2017-09-08 Biotic and abiotic stress factors deliver a huge impact on plant life. Biotic stress factors such as damage through pathogens or herbivore attack, as well as abiotic stress factors like variation in temperature, rainfall and salinity, have placed the plant kingdom under constant challenges for survival. As a consequence, global agricultural and horticultural productivity has been disturbed to a large extent. Being sessile in nature, plants cannot escape from the stress, and instead adapt changes within their system to overcome the adverse conditions. These changes include physiological, developmental and biochemical alterations within the plant body which influences the genome, proteome and metabolome profiles of the plant. Since proteins are the ultimate players of cellular behavior, proteome level alterations during and recovery period of stress provide direct implications of plant responses towards stress factors. With current advancement of modern high-throughput technologies, much research has been carried out in this field. This e-book highlights the research and review articles that cover proteome level changes during the course or recovery period of various stress factors in plant life. Overall, the chapters in this e-book has provided a wealth of information on how plants deal with stress from a proteomics perspective. |
| dna vs rna venn diagram: The Cystic Fibrosis Transmembrane Conductance Regulator Kevin L. Kirk, David C. Dawson, 2003-10-31 The CFTR chloride channel is one of the most well studied transport proteins in biology. Yet there remain many mysteries about the functional properties and biological roles of this ABC transporter. The Cystic Fibrosis Transmembrane Conductance Regulator addresses a select series of `hot' topics that relate to the function of CFTR, and the links between CFTR dysfunction and human disease (i.e., cystic fibrosis). The timeliness of these topics distinguishes this collection from previous volumes of this type. Given the general interest in CFTR, this collection will appeal to a broad readership with interests in CFTR, cystic fibrosis, ion channels and ABC transporters. |
| dna vs rna venn diagram: DNA Methylation Dynamics and Human Diseases Li Tan, Jiemin Wong, Peter Adams, Chunjie Jiang, Hao Chen, 2022-07-18 |
| dna vs rna venn diagram: Traditional and Up-to-date Genomic Insights into Domestic Animal Diversity Johann Sölkner, Michael N. Romanov, Natalia A. Zinovieva, Steffen Weigend, Klaus Wimmers, 2023-02-01 |
| dna vs rna venn diagram: Cell and Molecular Biology of Breast Cancer Heide Schatten, 2013-09-27 Highlighting recent advances in our understanding of breast cancer, this book is intended for a wide audience as a reference book. Included are reviews of genetics, epigenetics, various aspects of cell and molecular biology, and several other areas of breast cancer that are aimed at determining new intervention sites for treatments and cures of the disease. The chapters are written by internationally recognized experts and include reviews of key topics in breast cancer research. Each chapter highlights the new aspects of specific research topics and the various impacts of designing new strategies as well as identifies new targets for therapeutic intervention. The topics addressed are selected to be of interest to patients, scientists, students, teachers, and anyone else interested in expanding their knowledge of breast cancer imaging, diagnostics, therapeutics, or basic biomedical research on breast cancer. |
| dna vs rna venn diagram: RNA at a breaking point? cytoplasmic cleavage and other post-transcriptional RNA processing in neurodevelopment and disease Catia Andreassi, Monika Piwecka, Raphaëlle Luisier, 2023-06-29 |
| dna vs rna venn diagram: Reviews and Protocols in DT40 Research Jean-Marie Buerstedde, Shunichi Takeda, 2006-10-21 The vertebrate genome DT40 has proven to be a reliable and robust research subject, with fast doubling time, easy clonability and a relatively stable karyotype. This book provides an up to date overview of the different facets of research, and also intends to help newcomers get started and avoid looming pitfalls. The collection of protocols which have been provided by a number of laboratories will be particularly useful in this regard. |
| dna vs rna venn diagram: Modeling for Prediction of Radiation-Induced Toxicity to Improve Therapeutic Ratio in the Modern Radiation Therapy Era Ester Orlandi, Tiziana Rancati, Giuseppe Sanguineti, Claudio Fiorino, Riccardo Valdagni, 2021-07-27 |
| dna vs rna venn diagram: Non-coding RNA and coronary artery disease En-Zhi Jia, Laiyuan Wang, Xiangming Ding, BuChun Zhang, 2023-04-18 |
| dna vs rna venn diagram: International Plant Proteomics Organization (INPPO) World Congress 2014 Joshua L. Heazlewood, Jesús V. Jorrín-Novo, Ganesh Kumar Agrawal, Silvia Mazzuca, Sabine Lüthje, 2017-02-08 The field of proteomics has advanced considerably over the past two decades. The ability to delve deeper into an organism’s proteome, identify an array of post-translational modifications and profile differentially abundant proteins has greatly expanded the utilization of proteomics. Improvements to instrumentation in conjunction with the development of these reproducible workflows have driven the adoption and application of this technology by a wider research community. However, the full potential of proteomics is far from being fully exploited in plant biology and its translational application needs to be further developed. In 2011, a group of plant proteomic researchers established the International Plant Proteomics Organization (INPPO) to advance the utilization of this technology in plants as well as to create a way for plant proteomics researchers to interact, collaborate and exchange ideas. The INPPO conducted its inaugural world congress in mid 2014 at the University of Hamburg (Germany). Plant proteomic researchers from around the world were in attendance and the event marked the maturation of this research community. The Research Topic captures the opinions, ideas and research discussed at the congress and encapsulates the approaches that were being applied in plant proteomics. |
| dna vs rna venn diagram: Investigating the Elements of Plant Defense Mechanisms Within Plant Immune Responses Against Pathogens Katarzyna Otulak-Kozieł, Edmund Kozieł , Jozef Julian Bujarski, 2024-11-11 Biotic stress can increase or reduce a plant's susceptibility to specific pathogens. A wide range of plant pathogens, i.e., viruses, bacteria, and fungi causing diseases, modulate different elements of plant defense mechanisms responses that influence disease and the physiological state of host plants. Nevertheless, plant hosts are not static and defenseless. Plants have developed active and dynamic complex defense mechanisms to protect themselves against different pathogenic stressors. Plants' defense mechanisms consist of multi-elements and can be determined by pre-formed, natural barriers or inducible defense responses directly activated upon detection of a pathogen. The inducible response is defined as ‘basal resistance’ or ‘innate immunity’ and is regulated by signal transduction and transcriptional networks. Moreover, plant responses to pathogens are finely tuned and complex at the immune receptor, cellular, proteome, epigenetic, and transcriptome levels. We can tell that a sophisticated molecular ‘arms race’ is taking place in the biological co-evolution of plant-pathogen interactions especially in developing novel elements involved in this interaction. Therefore, a comprehensive understanding of the broad spectrum and underlying elements of defense mechanisms in the interactions between plants and their pathogenic enemies will improve plant resistance to pathogens. |
| dna vs rna venn diagram: Exploring the Impact of Genetics on New Drugs and Potential Drug Targets: A Multi-Omics Approach to Improve Personalized Therapeutics. Shaoqiu Chen , Jian Gao, 2024-07-08 In recent years, significant advancements have been made in the field of new drug development. With the advent of high-throughput sequencing technologies, the identification of new drug targets has become more efficient and precise. In addition, multi-omics approaches, including genomics, transcriptomics, proteomics, and metabolomics, have emerged as a powerful tool for understanding the complexity of diseases and identifying new therapeutic targets. |
| dna vs rna venn diagram: Multi-omics and computational biology in horticultural plants: From genotype to phenotype Yunpeng Cao, Hui Song, Liangsheng Zhang, Suvendu Mondal, 2023-02-28 |
| dna vs rna venn diagram: Characterizing Modern Microbialites and The Geobiological Processes Underlying Their Formation Jamie S. Foster, Pieter T. Visscher, Ruth Pamela Reid, Christophe Dupraz, 2019-12-23 |
| dna vs rna venn diagram: Non-Coding RNAs and Human Diseases Yujing Li, Ge Shan, Zhao-Qian Teng, Thomas S. Wingo, 2020-07-08 |
| dna vs rna venn diagram: Improvement for Quality and Safety Traits in Horticultural Plants Pei Xu, Xinchao Wang, Ferdinando Branca, 2022-06-23 |
| dna vs rna venn diagram: Multi-omics and Computational Biology in Horticultural Plants: From Genotype to Phenotype, Volume II Yunpeng Cao, Hui Song, Muhammad Abdullah, Xiaoxu Li, Muhammad Aamir Manzoor, 2024-02-13 This Research Topic is part of the article collection series - Multi-omics and Computational Biology in Horticultural Plants: From Genotype to Phenotype. Horticultural plants play an important role for humans by providing herbal medicines, beverages, vegetables, fruits, and ornamentals. High-throughput technologies have revolutionised the time scale and power of detecting insights into physiological changes and biological mechanisms in plants. All sequencing data and tools have helped us better understand the evolutionary histories of horticultural plants and provide genotype and phenotype resources for molecular studies on economically important traits. The integration of these -omics technologies (e.g., genomics, transcriptomics, proteomics, metabolomics, lipidomics, ionomics, and redoxomics) is currently at the forefront of plant research. The genomes of horticultural plants are highly diverse and complex, often with a high degree of heterozygosity and polyploidy. Novel computational methods need to be developed to take advantage of state-of-the-art genomic technologies. As a result, the mining of multi-omics data and the development of new computational biology approaches for the reliable and efficient analysis of plant traits is necessary. |
| dna vs rna venn diagram: The Role of Steroid Hormones and Growth Factors in Cancer Marzia Di Donato, Paul J. Higgins, Isabel R. Schlaepfer, Gustavo Cernera, 2022-08-25 |
| dna vs rna venn diagram: Post-Transcriptional Regulation of Immune Responses Manuel Daniel Díaz-Muñoz, Osamu Takeuchi, Simon Fillatreau, 2022-11-17 |
| dna vs rna venn diagram: The Tobacco Plant Genome Nikolai V. Ivanov, Nicolas Sierro, Manuel C. Peitsch, 2020-03-16 This book describes the history of tobacco genomics, from its “discovery” by Europeans to next-generation omics approaches in plant science. The authors primarily focus on the allotetraploid common tobacco plant (N. tabacum); however, separate chapters are dedicated to closely related Nicotiana species, such as N. benthamiana and N. attenuata, for which substantial progress in omics data analysis has been already achieved. While genetic maps, transcriptomes, and physical maps of BAC libraries have significantly enhanced our understanding of the tobacco plant, the genome of tobacco and related Nicotiana species has opened a new era in modern tobacco research. This book addresses current and future industrial and research applications as well as central challenges in tobacco science, including diseases, low variability of cultivars, the genome’s large size, polyploidy, and gene duplication. |
| dna vs rna venn diagram: Omic Network Modules in Complex diseases Tejaswi Venkata Satya Badam, 2021-01-15 Biological systems encompass various molecular entities such as genes, proteins, and other biological molecules, including interactions among those components. Understanding a given phenotype, the functioning of a cell or tissue, aetiology of disease, or cellular organization, requires accurate measurements of the abundance profiles of these molecular entities in the form of biomedical data. The analysis of the interplay between these different entities at various levels represented in the form of biological network provides a mechanistic understanding of the observed phenotype. In order to study this interplay, there is a requirement of a conceptual and intuitive framework which can model multiple omics such as genome, transcriptome, or a proteome. This can be addressed by application of network-based strategies. Translational bioinformatics deals with the development of analytic and interpretive methods to optimize the transformation of different omics and clinical data to understanding of complex diseases and improving human health. Complex diseases such as multiple sclerosis (MS), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and non-small cell lung cancer (NSCLC) etc., are hypothesized to be a result of a disturbance in the omic networks rendering the healthy cells to be in a state of malfunction. Even though there are numerous methods to layout the relation of the interactions among omics in complex diseases, the output network modules were not clearly interpreted. In this PhD thesis, we showed how different omic data such as transcriptome and methylome can be mapped to the network of interactions to extract highly interconnected gene sets relevant to the disease, so called disease modules. First, we selected common module identification methods and assembled them into a unified framework of the methods implemented in an Rpackage MODifieR (Paper I). Secondly, we showed that the concept of the network modules can be applied on the whole genome sequencing data for developing a tested model for predicting myelosuppressive toxicity (Paper II). Furthermore, we demonstrated that network modules extracted using the methylome data helped identifying several genes that were associated with pregnancy-induced pathways and were enriched for disease-associated methylation changes that were also shared by three auto-immune and inflammatory diseases, namely MS, RA, and SLE (Paper III). Remarkably, those methylation changes correlated with the expected outcome from clinical experience in those diseases. Last, we benchmarked the omic network modules on 19 different complex diseases using both transcriptomic and methylomic data. This led to the identification of a multi-omic MS module that was highly enriched disease-associated genes identified by genome-wide association studies, but also genes associated with the most common environmental risk factors of MS (Paper IV). The application of the network modules concept on different omics is the centrepiece of the research presented in this PhD thesis. The thesis represents the application of omic network modules in complex diseases and how these modules should be integrated and interpreted. In particular, it aimed to show the importance of networks owing to the incomplete knowledge of the genes dysregulated in complex diseases and the contribution of this thesis that provides tools and benchmarks for the methods as well as insights into how a network module can be extracted and interpreted from the omic data in complex diseases. Biologiska system består av gener, proteiner och andra biologiska molekyler, liksom interaktioner mellan dessa komponenter. Förståelse av en given fenotyp, funktion av en cell eller vävnad, etiologi av sjukdomar eller cellulär organisation kräver exakta mätningar av uttrycksprofilerna för dessa molekyler, vilket ger upphov till enorma mängder av biomedicinska data. Analys av biomedicinska data tillåter oss att förklara viktiga funktioner i interaktionerna som leder till en mekanistisk förståelse av den observerade fenotypen. Samspelet mellan olika komponenter på olika nivåer kan representeras i form av biologiska nätverk, till exempel protein-protein interaktioner (PPI). Nätverk ger en konceptuell och intuitiv ram för att modellera olika komponenter i flera omik-data, såsom transkriptom. De topologiska egenskaperna hos sjukdomsassocierade gener varierar signifikant från sjukdom till sjukdom. Translationell bioinformatik handlar om utveckling av analytiska och tolkningsmetoder för att omvandla omik-data till förståelsen av komplexa sjukdomar. Komplexa sjukdomar som multipel skleros, reumatoid artrit och lungcancer är några av de sjukdomar som antas vara resultat av underliggande störningar i omik nätverken. Även om det finns många metoder för att modellera interaktioner mellan omik-data vid komplexa sjukdomar saknas det fortfarande tydlighet i hur de resulterande nätverksmodulerna ska tolkas. I denna doktorsavhandling visade vi hur olika omik-data som transkriptom och metylom kan användas överlagrat på nätverket av proteininteraktioner och att extrahera tätt sammankopplade nätverksstrukturer av relevans för sjukdom, så kallade sjukdomsmoduler. I den första artikeln gjorde vi ett urval av de mest förekommande metoder för identifiering av sjukdomsmoduler och implementerade dessa i ett R-paket MODifieR, som erbjuder en lättanvänd gemensam struktur för olika metoder, samt möjlighet att kombinera moduler från olika metoder. I den andra artikeln visade vi hur nätverksmodulskoncept kan tillämpas på data från helgenomsekvensering för att utveckla en modell för prediktion av myelosuppressiv toxicitet i icke-småcellig lungcancer. I tredje artikeln demonstrerades ytterligare en framgångsrik tillämning av nätverksmoduler som användes för att identifiera gener som är associerade med biologiska pathways samt sjukdomsassocierade metyleringsförändringar relaterade till multipel skleros, reumatoid artrit och systemisk lupus erythematosus, där sjukdomskopplingar till graviditet undersöktes. Sedan utvärderades de omiska nätverksmodulerna på 19 olika komplexa sjukdomar genom att använda både transkriptom och metylom data. Vidare identifierade vi också en multi-omik modul i multipel skleros, med signifikant koppling till sjukdomsriskfaktorer genom att utnyttja genomisk överensstämmelse, dvs att flera omik ska ge höga genöverlapp. Tillämpningen av nätverksmodulerna som ett koncept för att koppla omikdata till sjukdomsmekanismer är kärnan i forskningen som presenteras i denna doktorsavhandling. I synnerhet syftade den till att visa betydelse av hur nätverksomik-koncept kan bidra till kunskap om gener som är dysreglerade vid komplexa sjukdomar för att förstå sjukdomsmekanismer. Denna avhandling ger också verktyg och riktmärken för metoder och insikter i hur en nätverksmodul kan extraheras och tolkas från omik-data vid komplexa sjukdomar. |
| dna vs rna venn diagram: Recent Advances in Big Data, Machine, and Deep Learning for Precision Agriculture Muhammad Fazal Ijaz, Marcin Wozniak, 2024-02-19 |
| dna vs rna venn diagram: CSIR NET Life Science Exam 2024 (English Edition) - 17 Solved Practice Tests (8 Mock Tests, 6 Sectional Tests and 3 Previous Year Papers) with Free Access to Online Tests EduGorilla Prep Experts, 2024-06-27 • Best Selling Book in English Edition for CSIR NET Life Science Exam with objective-type questions as per the latest syllabus given by the CSIR. • CSIR NET Life Science Exam Preparation Kit comes with 17 Practice Tests (8 Mock Tests + 6 Sectional Tests + 3 Previous Year Papers) with the best quality content. • Increase your chances of selection by 16X. • CSIR NET Life Science Exam Prep Kit comes with well-structured and 100% detailed solutions for all the questions. • Clear exam with good grades using thoroughly Researched Content by experts. |
| dna vs rna venn diagram: Salt tolerance: Molecular and physiological mechanisms and breeding applications, volume II Loredana F. Ciarmiello, Pasqualina Woodrow, 2023-01-27 |
| dna vs rna venn diagram: Head and Neck Cancer: New Insights for the Healthcare Professional: 2013 Edition , 2013-07-22 Head and Neck Cancer: New Insights for the Healthcare Professional: 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Diagnosis and Screening. The editors have built Head and Neck Cancer: New Insights for the Healthcare Professional: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Diagnosis and Screening in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Head and Neck Cancer: New Insights for the Healthcare Professional: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/. |
| dna vs rna venn diagram: Multi-omics strategies to analyze complex agronomic traits in plants Lin Chen, Guo-Fei Tan, 2023-11-01 |
| dna vs rna venn diagram: Shaping of Human Immune System and Metabolic Processes by Viruses and Microorganisms Marina I. Arleevskaya, Rustam Aminov, Wesley H. Brooks, Gayane Manukyan, Yves Renaudineau, 2019-08-15 Recent advances in the understanding of microbiota in health and diseases are presented in this special issue of Frontiers in Immunology and Frontiers in Microbiology as well as their impact on the immune system that can lead to the development of pathologies. Potential perspectives and biomarkers are also addressed. We offer this Research Topic involving 64 articles and 501 authors to discuss recent advances regarding: 1. An overview of the human microbiota and its capacity to interact with the human immune system and metabolic processes, 2. New developments in understanding the immune system’s strategies to respond to infections and escape strategies used by pathogens to counteract such responses, 3. The link between the microbiota and pathology in terms of autoimmunity, allergy, cancers and other diseases. |
| dna vs rna venn diagram: Reproductive Genomics Xi Wang, Mengcheng Luo, Yan Yun, Wenjie Shi, 2022-09-27 |
| dna vs rna venn diagram: Multidisciplinary Approaches in Exploring Cancer Heterogeneity, TME and Therapy Resistance: Perspectives for Systems Medicine Brigitte M. Pützer, Kanaga Sabapathy, Julio Vera González, 2022-03-07 |
| dna vs rna venn diagram: The Routledge Companion to Biology in Art and Architecture Charissa Terranova, Meredith Tromble, 2016-08-12 The Routledge Companion to Biology in Art and Architecture collects thirty essays from a transdisciplinary array of experts on biology in art and architecture. The book presents a diversity of hybrid art-and-science thinking, revealing how science and culture are interwoven. The book situates bioart and bioarchitecture within an expanded field of biology in art, architecture, and design. It proposes an emergent field of biocreativity and outlines its historical and theoretical foundations from the perspective of artists, architects, designers, scientists, historians, and theoreticians. Includes over 150 black and white images. |
| dna vs rna venn diagram: Concepts of Biology Samantha Fowler, Rebecca Roush, James Wise, 2023-05-12 Black & white print. Concepts of Biology is designed for the typical introductory biology course for nonmajors, covering standard scope and sequence requirements. The text includes interesting applications and conveys the major themes of biology, with content that is meaningful and easy to understand. The book is designed to demonstrate biology concepts and to promote scientific literacy. |
| dna vs rna venn diagram: Foodborne Pathogens: Hygiene and Safety Maria Schirone, Pierina Visciano, Rosanna Tofalo, Giovanna Suzzi, 2019-11-26 |
| dna vs rna venn diagram: Editors' Showcase 2022: Insights in Molecular and Cellular Reproduction Rafael A. Fissore, Shao-Chen Sun, 2023-12-01 |
| dna vs rna venn diagram: Nutrigenetics Dolores Corella, 2018-07-10 This book is a printed edition of the Special Issue Nutrigenetics that was published in Nutrients |
| dna vs rna venn diagram: Protein Modifications in Epigenetic Dysfunctional Diseases: Mechanisms and Potential Therapeutic Strategies Bin Liu, Wei Liu, Lan Zhu, 2023-06-01 |
| dna vs rna venn diagram: Advanced Molecular Targets in the Diagnosis and Treatment of Gastrointestinal Cancers Zsolt Kovacs, Simona Gurzu, Raluca Ioana Stefan-van Staden, Cornelia Braicu, 2023-06-05 Gastrointestinal cancers are among the most common cancer types, based on the Cancer Genome Atlas. GI cancers are within the most frequent malignancy, with almost 150.000 new cases in 2020. On one hand a big number of researches are focused on the diagnosis, new diagnostic approaches in upper and lower gastrointestinal tract cancers. On the other hand in the last 10 years several papers had been published about the possible therapeutic targets, pointing to precision and personalized medicine. |
| dna vs rna venn diagram: Omics data-based identification of plant specialized metabolic genes Peipei Wang, Pengxiang Fan, Yan Bao, Li Wang, Wei Li, 2023-06-30 |
| dna vs rna venn diagram: Epigenetic Variation Influences on Livestock Production and Disease Traits Eveline M. Ibeagha-Awemu, Hélène Kiefer, Stephanie McKay, George E. Liu, 2022-07-07 |
| dna vs rna venn diagram: Genetics, genomics, and breeding of edible mushrooms in Asia Chenyang Huang, Tadanori Aimi, Vikineswary Sabaratnam, 2024-03-27 |
| dna vs rna venn diagram: Use of Barley and Wheat Reference Sequences: Downstream Applications in Breeding, Gene Isolation, GWAS and Evolution Dragan Perovic, Hikmet Budak, Kazuhiro Sato, Pierre Sourdille, 2020-08-27 This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact. |
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