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Drug repositioning is the process of identifying new indications for existing drugs. At present, the conventional de novo drug discovery process requires an average of about 14 years and US$2.5 billion to approve and launch a drug. Drug repositioning can reduce the time and cost of this process because it takes advantage of drugs already in clinical use for other indications or drugs that have cleared phase I safety trials but have failed to show efficacy in the intended diseases. Historically, drug repositioning has been realized through serendipitous clinical observations or improved understanding of disease mechanisms. However, recent technological advances have enabled a more systematic approach to drug repositioning. This eBook collects 16 articles from 112 authors, providing readers with current advances and future perspectives of drug repositioning.

database --- Integrative strategies --- molecular docking --- polypharmacology --- multi-omics --- computational analysis --- Drug Repositioning --- data sharing --- Patenting

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Drug repositioning is the process of identifying new indications for existing drugs. At present, the conventional de novo drug discovery process requires an average of about 14 years and US$2.5 billion to approve and launch a drug. Drug repositioning can reduce the time and cost of this process because it takes advantage of drugs already in clinical use for other indications or drugs that have cleared phase I safety trials but have failed to show efficacy in the intended diseases. Historically, drug repositioning has been realized through serendipitous clinical observations or improved understanding of disease mechanisms. However, recent technological advances have enabled a more systematic approach to drug repositioning. This eBook collects 16 articles from 112 authors, providing readers with current advances and future perspectives of drug repositioning.

database --- Integrative strategies --- molecular docking --- polypharmacology --- multi-omics --- computational analysis --- Drug Repositioning --- data sharing --- Patenting

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This open access textbook aims at providing detailed explanations on how to design and construct image analysis workflows to successfully conduct bioimage analysis. Addressing the main challenges in image data analysis, where acquisition by powerful imaging devices results in very large amounts of collected image data, the book discusses techniques relying on batch and GPU programming, as well as on powerful deep learning-based algorithms. In addition, downstream data processing techniques are introduced, such as Python libraries for data organization, plotting, and visualizations. Finally, by studying the way individual unique ideas are implemented in the workflows, readers are carefully guided through how the parameters driving biological systems are revealed by analyzing image data. These studies include segmentation of plant tissue epidermis, analysis of the spatial pattern of the eye development in fruit flies, and the analysis of collective cell migration dynamics. The presented content extends the Bioimage Data Analysis Workflows textbook (Miura, Sladoje, 2020), published in this same series, with new contributions and advanced material, while preserving the well-appreciated pedagogical approach adopted and promoted during the training schools for bioimage analysis organized within NEUBIAS – the Network of European Bioimage Analysts. This textbook is intended for advanced students in various fields of the life sciences and biomedicine, as well as staff scientists and faculty members who conduct regular quantitative analyses of microscopy images.

Cytology. --- Bioinformatics. --- Imaging systems in biology. --- Cell Biology. --- Computational and Systems Biology. --- Biological Imaging. --- Biological imaging systems --- Biology --- Bio-informatics --- Biological informatics --- Information science --- Computational biology --- Systems biology --- Cell biology --- Cellular biology --- Cells --- Data processing --- Analyzing Image Data in Biology --- Building a Bioimage Analysis Workflow --- Computational Analysis --- Chosing the Correct Components for Given Biological Questions --- Data Handling and Plotting --- Deep Learning --- Fast Computation --- GPU-Acceleration --- Handling Biological data --- Machine Learning --- Phyton --- Processing Language --- Understanding Bioimage Analysis Software --- Microscòpia electrònica

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Protein–ligand interactions play a fundamental role in most major biological functions. The number and diversity of small molecules that interact with proteins, whether naturally or not, can quickly become overwhelming. They are as essential as amino acids, nucleic acids or membrane lipids, enabling a large number of essential functions. One need only think of carbohydrates or even just ATP to be certain. They are also essential in drug discovery. With the increasing structural information of proteins and protein–ligand complexes, molecular modelling, molecular dynamics, and chemoinformatics approaches are often required for the efficient analysis of a large number of such complexes and to provide insights. Similarly, numerous computational approaches have been developed to characterize and use the knowledge of such interactions, which can lead to drug candidates. "Recent Developments on Protein–Ligand Interactions: From Structure, Function to Applications" was dedicated to the different aspect of protein–ligand analysis and/or prediction using computational approaches, as well as new developments dedicated to these tasks. It will interest both specialists and non-specialists, as the presented studies cover a very large spectra in terms of methodologies and applications. It underlined the variety of scientific area linked to these questions, i.e., chemistry, biology, physics, informatics, bioinformatics, structural bioinformatics and chemoinformatics.

Research & information: general --- Biology, life sciences --- Biochemistry --- pimaricin thioesterase --- protein-substrate interaction --- macrocyclization --- molecular dynamics (MD) simulation --- pre-reaction state --- folate --- folate receptor --- peptide conjugation --- click reaction --- biolayer interferometry --- acetylcholinesterase --- resistance --- organophosphorus --- pesticides --- molecular modeling --- lepidopterous --- insects --- conserved patterns --- similarity --- 3D-patterns --- epigenetics --- protein-RNA interaction --- RRM domain inhibitor --- NMR fragment-based screening --- TDP-43 --- galectin-1 --- gulopyranosides --- fluorescence polarization --- benzamide --- selective --- phospholipase C gamma 1 --- SLP76 --- virtual screening --- pharmacophore mapping --- molecular docking --- molecular dynamics --- caspase inhibition --- protein-ligand binding free energy --- Monte Carlo sampling --- docking and scoring --- molecular conformational sampling --- procollagen C-proteinase enhancer-1 --- glycosaminoglycans --- computational analysis of protein-glycosaminoglycan interactions --- calcium ions --- fragment-based docking --- protein–ligand analysis --- drug discovery and design --- structure–activity relationships --- bioremediation --- High Energy Molecules --- HMX --- protein design --- nitroreductase --- flavoprotein --- substrate specificity --- pharmacophore --- secretoglobin --- odorant-binding protein --- chemical communication --- pheromone --- N-phenyl-1-naphthylamine --- in silico docking --- protein–ligand interactions --- 2D interaction maps --- ligand-binding assays --- protein-ligand complexes --- dataset --- clustering --- structural alignment --- refinement --- PD-1/PD-L1 --- immune checkpoint inhibitors --- biphenyl-conjugated bromotyrosine --- amino acid conjugation --- amino-X --- in silico simulation --- IC50

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This book, which is a reprint of articles published in the Special Issue "Advances in Hydrogen Energy" in Energies, seeks to contribute to disseminating the most recent advancements in the field of hydrogen energy. It does so by presenting scientific works from around the world covering both modeling and experimental analysis. The focus is placed on research covering all aspects of the hydrogen energy, from production to storage and final use, including the development of other easy to transport and versatile hydrogen-based energy carriers via the power-to-x (PtX) route, such as ammonia and methanol.Hydrogen energy research and development has attracted growing attention as one of the key solutions for clean future energy systems. In order to reduce greenhouse gas emissions, governments across the world are developing ambitious policies to support hydrogen technology, and an increasing level of funding has been allocated for projects of research, development, and demonstration of these technologies. At the same time, the private sector is capitalizing on the opportunity with larger investments in hydrogen technology solutions.While intense research activities have been dedicated to this field, several issues require further research prior to achieving full commercialization of hydrogen technology solutions. This book addresses some of these issues by presenting detailed models to optimize design strategies and operating conditions for the entire hydrogen value chain, covering production via electrolysis, storage and use in different types of fuel cells and in different forms of energy carriers.

Technology: general issues --- methanol steam reforming --- hydrogen production --- exhaust waste heat --- rib microreactor --- air-cooled proton exchange membrane fuel cells --- adiabatic fuel cell temperature --- thermodynamic analysis of proton exchange membrane fuel cells --- ammonia --- hydrogen --- production --- storage --- utilization --- CO2 free --- hydrogen storage --- hydrogen compression --- non-mechanical compressors --- electrochemical compressors --- activated carbons --- computational analysis --- high-pressure methanol steam reformer --- phase change heat transfer --- high pressure steam condensation --- high temperature PEM --- fuel cell --- electro-osmotic drag --- polymer electrolyte membrane --- proton exchange membrane fuel cells --- proton exchange membrane electrolyzer cells --- membrane water transport --- elementary reactions steps --- rate-determining step --- solid oxide electrolysis cell --- multi-physics --- optimal rib/pitch ratio --- parameters sensitivity --- analytical expression --- SOFC --- system --- model --- stack test --- hydrogen systems --- cryogenics --- vortex tubes --- computational fluid dynamics --- low melting metal --- Al-based alloy --- metal smelting --- fuel cells --- hydrogen hybrid energy system --- thermography --- CFD modeling --- heat transfer --- optimization --- PEM --- fault --- diagnosis --- electrochemical impedance spectroscopy --- distribution of relaxation times --- reformate --- proton exchange membrane fuel cell --- gas diffusion layer --- microscopic porous layer --- fracture --- two phase flow