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Macromolecular Structure Underlying Recognition in Innate Immunity

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889455270 Year: Pages: 151 DOI: 10.3389/978-2-88945-527-0 Language: English
Publisher: Frontiers Media SA
Subject: Medicine (General) --- Allergy and Immunology
Added to DOAB on : 2019-01-23 14:53:42
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Abstract

Immune molecules have evolved to distinguish “self “molecules from “non-self”, “altered self” and “danger” molecules. Recognition is mediated via interactions between pattern recognition receptor molecules (PPRs) and their ligands, which include hydrophobic and electrostatic interactions between amino acid residues on the PPRs and uncharged or charged groups on amino acid residues, sugar rings or DNA/RNA molecules. Recognition in innate immunity range from cases (C1q, mannin-binding protein etc) where recognition is orchestrated by interaction between many ligands with one receptor molecule, and density of interaction is necessary for strong specific recognition, distinct from weak non-specific binding, and cases such as TLRs and NLRs where recognition involves complexation of single receptor and ligand, followed by oligomerisation of the receptor molecule. The majority of PPR molecules bind and recognise a wide variety of ligands, e.g TLR4 recognises LPS (gram negative bacteria), Lipotechoic acid (gram positive bacteria), heat shock protein hsp60, respiratory syncytial virus fusion protein etc, molecules that are structurally dissimilar to each other. This indicates considerable flexibility in their binding domains (amino acid residue variations) and modes (hydrophobic and charged, direct or mediated via an adaptor molecule). However, in many cases there is a dearth of structural and molecular data available, required to delineate the mechanism of ligand binding underlining recognition in pathogen receptors in innate immunity. Insights into requirements of conformation, charge, surface etc in the recognition and function of innate immunity receptors and their activation pathways, based on current data can suggest valuable avenues for future work.

Computational Systems Biology of Pathogen-Host Interactions

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889198214 Year: Pages: 198 DOI: 10.3389/978-2-88919-821-4 Language: English
Publisher: Frontiers Media SA
Subject: Microbiology --- Science (General)
Added to DOAB on : 2016-01-19 14:05:46
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A thorough understanding of pathogenic microorganisms and their interactions with host organisms is crucial to prevent infectious threats due to the fact that Pathogen-Host Interactions (PHIs) have critical roles in initiating and sustaining infections. Therefore, the analysis of infection mechanisms through PHIs is indispensable to identify diagnostic biomarkers and next-generation drug targets and then to develop strategic novel solutions against drug-resistance and for personalized therapy. Traditional approaches are limited in capturing mechanisms of infection since they investigate hosts or pathogens individually. On the other hand, the systems biology approach focuses on the whole PHI system, and is more promising in capturing infection mechanisms. Here, we bring together studies on the below listed sections to present the current picture of the research on Computational Systems Biology of Pathogen-Host Interactions:- Computational Inference of PHI Networks using Omics Data- Computational Prediction of PHIs- Text Mining of PHI Data from the Literature- Mathematical Modeling and Bioinformatic Analysis of PHIs Computational Inference of PHI Networks using Omics Data Gene regulatory, metabolic and protein-protein networks of PHI systems are crucial for a thorough understanding of infection mechanisms. Great advances in molecular biology and biotechnology have allowed the production of related omics data experimentally. Many computational methods are emerging to infer molecular interaction networks of PHI systems from the corresponding omics data. Computational Prediction of PHIs Due to the lack of experimentally-found PHI data, many computational methods have been developed for the prediction of pathogen-host protein-protein interactions. Despite being emerging, currently available experimental PHI data are far from complete for a systems view of infection mechanisms through PHIs. Therefore, computational methods are the main tools to predict new PHIs. To this end, the development of new computational methods is of great interest. Text Mining of PHI Data from Literature Despite the recent development of many PHI-specific databases, most data relevant to PHIs are still buried in the biomedical literature, which demands for the use of text mining techniques to unravel PHIs hidden in the literature. Only some rare efforts have been performed to achieve this aim. Therefore, the development of novel text mining methods specific for PHI data retrieval is of key importance for efficient use of the available literature. Mathematical Modeling and Bioinformatic Analysis of PHIs After the reconstruction of PHI networks experimentally and/or computationally, their mathematical modeling and detailed computational analysis is required using bioinformatics tools to get insights on infection mechanisms. Bioinformatics methods are increasingly applied to analyze the increasing amount of experimentally-found and computationally-predicted PHI data. Acknowledgements: We, editors of this e-book, acknowledge Emrah Nikerel (Yeditepe University, Turkey) and Arzucan Özgür (Bogaaziçi University, Turkey) for their contributions during the initiation of the Research Topic.

Molecular Science for Drug Development and Biomedicine

ISBN: 9783906980836 9783906980843 Year: Pages: 356
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Added to DOAB on : 2015-10-22 06:15:53
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With the avalanche of biological sequences generated in the postgenomic age, molecular science is facing an unprecedented challenge, i.e., how to timely utilize the huge amount of data to benefit human beings. Stimulated by such a challenge, a rapid development has taken place in molecular science, particularly in the areas associated with drug development and biomedicine, both experimental and theoretical. The current thematic issue was launched with the focus on the topic of “Molecular Science for Drug Development and Biomedicine”, in hopes to further stimulate more useful techniques and findings from various approaches of molecular science for drug development and biomedicine.

Molecular Computing and Bioinformatics

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ISBN: 9783039211951 / 9783039211968 Year: Pages: 390 DOI: 10.3390/books978-3-03921-196-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Biotechnology
Added to DOAB on : 2019-08-28 11:21:27
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This text will provide the most recent knowledge and advances in the area of molecular computing and bioinformatics. Molecular computing and bioinformatics have a close relationship, paying attention to the same object but working towards different orientations. The articles will range from topics such as DNA computing and membrane computing to specific biomedical applications, including drug R&D and disease analysis.

Keywords

prostate cancer --- Mycoplasma hominis --- endoplasmic reticulum --- systems biology --- protein targeting --- biomedical text mining --- big data --- Tianhe-2 --- parallel computing --- load balancing --- bacterial computing --- bacteria and plasmid system --- Turing universality --- recursively enumerable function --- miRNA biogenesis --- structural patterns --- DCL1 --- protein–protein interaction (PPI) --- clustering --- protein complex --- penalized matrix decomposition --- avian influenza virus --- interspecies transmission --- amino acid mutation --- machine learning --- Bayesian causal model --- causal direction learning --- K2 --- brain storm optimization --- line graph --- Cartesian product graph --- join graph --- atom-bond connectivity index --- geometric arithmetic index --- P-glycoprotein --- efflux ratio --- in silico --- machine learning --- hierarchical support vector regression --- absorption --- distribution --- metabolism --- excretion --- toxicity --- image encryption --- chaotic map --- DNA coding --- Hamming distance --- Stenotrophomonas maltophilia --- iron acquisition systems --- iron-depleted --- RAST server --- NanoString Technologies --- siderophores --- gene fusion data --- gene susceptibility prioritization --- evaluating driver partner --- gene networks --- drug-target interaction prediction --- machine learning --- drug discovery --- microRNA --- environmental factor --- structure information --- similarity network --- bioinformatics --- identification of Chinese herbal medicines --- biochip technology --- DNA barcoding technology --- DNA strand displacement --- cascade --- 8-bit adder/subtractor --- domain label --- Alzheimer’s disease --- gene coding protein --- sequence information --- support vector machine --- classification --- adverse drug reaction prediction --- heterogeneous information network embedding --- stacking denoising auto-encoder --- meta-path-based proximity --- Panax ginseng --- oligopeptide transporter --- flowering plant --- phylogeny --- transcription factor --- multiple interaction networks --- function prediction --- multinetwork integration --- low-dimensional representation --- dihydrouridine --- nucleotide physicochemical property --- pseudo dinucleotide composition --- RNA secondary structure --- ensemble classifier --- diabetes mellitus --- hypoxia-inducible factor-1? --- angiogenesis --- bone formation --- osteogenesis --- protein transduction domain --- membrane computing --- edge detection --- enzymatic numerical P system --- resolution free --- molecular computing --- molecular learning --- DNA computing --- self-organizing systems --- pattern classification --- machine learning --- laccase --- Brassica napus --- lignification --- stress --- molecular computing --- bioinformatics --- machine learning --- protein --- DNA --- RNA --- drug --- bio-inspired

Plant Genetics and Molecular Breeding

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ISBN: 9783039211753 / 9783039211760 Year: Pages: 628 DOI: 10.3390/books978-3-03921-176-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology
Added to DOAB on : 2019-08-28 11:21:27
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The development of new plant varieties is a long and tedious process involving the generation of large seedling populations for the selection of the best individuals. While the ability of breeders to generate large populations is almost unlimited, the selection of these seedlings is the main factor limiting the generation of new cultivars. Molecular studies for the development of marker-assisted selection (MAS) strategies are particularly useful when the evaluation of the character is expensive, time-consuming, or with long juvenile periods. The papers published in the Special Issue “Plant Genetics and Molecular Breeding” report highly novel results and testable new models for the integrative analysis of genetic (phenotyping and transmission of agronomic characters), physiology (flowering, ripening, organ development), genomic (DNA regions responsible for the different agronomic characters), transcriptomic (gene expression analysis of the characters), proteomic (proteins and enzymes involved in the expression of the characters), metabolomic (secondary metabolites), and epigenetic (DNA methylation and histone modifications) approaches for the development of new MAS strategies. These molecular approaches together with an increasingly accurate phenotyping will facilitate the breeding of new climate-resilient varieties resistant to abiotic and biotic stress, with suitable productivity and quality, to extend the adaptation and viability of the current varieties.

Keywords

sugarcane --- cry2A gene --- particle bombardment --- stem borer --- resistance --- NPK fertilizers --- agronomic traits --- molecular markers --- quantitative trait loci --- common wild rice --- Promoter --- Green tissue-specific expression --- light-induced --- transgenic chrysanthemum --- WRKY transcription factor --- salt stress --- gene expression --- DgWRKY2 --- Cucumis sativus L. --- RNA-Seq --- DEGs --- sucrose --- ABA --- drought stress --- Aechmea fasciata --- squamosa promoter binding protein-like --- flowering time --- plant architecture --- bromeliad --- Oryza sativa --- endosperm development --- rice quality --- WB1 --- the modified MutMap method --- abiotic stress --- Cicer arietinum --- candidate genes --- genetics --- heat-stress --- molecular breeding --- metallothionein --- Brassica --- Brassica napus --- As3+ stress --- broccoli --- cytoplasmic male sterile --- bud abortion --- gene expression --- transcriptome --- RNA-Seq --- sesame --- genome-wide association study --- yield --- QTL --- candidate gene --- cabbage --- yellow-green-leaf mutant --- recombination-suppressed region --- bulk segregant RNA-seq --- differentially expressed genes --- marker–trait association --- haplotype block --- genes --- root traits --- D-genome --- genotyping-by-sequencing --- single nucleotide polymorphism --- durum wheat --- bread wheat --- complex traits --- Brassica oleracea --- Ogura-CMS --- iTRAQ --- transcriptome --- pollen development --- rice --- OsCDPK1 --- seed development, starch biosynthesis --- endosperm appearance --- Chimonanthus praecox --- nectary --- floral scent --- gene expression --- Prunus --- flowering --- bisulfite sequencing --- genomics --- epigenetics --- breeding --- AP2/ERF genes --- Bryum argenteum --- transcriptome --- gene expression --- stress tolerance --- SmJMT --- transgenic --- Salvia miltiorrhiza --- overexpression --- transcriptome --- phenolic acids --- Idesia polycarpa var --- glycine --- FAD2 --- linoleic acid --- oleic acid --- anther wall --- tapetum --- pollen accumulation --- OsGPAT3 --- rice --- cytoplasmic male sterility (CMS) --- phytohormones --- differentially expressed genes --- pollen development --- Brassica napus --- Rosa rugosa --- RrGT2 gene --- Clone --- VIGS --- Overexpression --- Tobacco --- Flower color --- Anthocyanin --- sugarcane --- WRKY --- subcellular localization --- gene expression pattern --- protein-protein interaction --- transient overexpression --- soybean --- branching --- genome-wide association study (GWAS) --- near-isogenic line (NIL) --- BRANCHED1 (BRC1) --- TCP transcription factor --- Zea mays L. --- MADS transcription factor --- ZmES22 --- starch --- flowering time --- gene-by-gene interaction --- Hd1 --- Ghd7 --- rice --- yield trait --- Oryza sativa L. --- leaf shape --- yield trait --- molecular breeding --- hybrid rice --- nutrient use efficiency --- quantitative trait loci (QTLs), molecular markers --- agronomic efficiency --- partial factor productivity --- P. suffruticosa --- R2R3-MYB --- overexpression --- anthocyanin --- transcriptional regulation --- ethylene-responsive factor --- Actinidia deliciosa --- AdRAP2.3 --- gene expression --- waterlogging stress --- regulation --- Chrysanthemum morifolium --- WUS --- CYC2 --- gynomonoecy --- reproductive organ --- flower symmetry --- Hs1pro-1 --- cZR3 --- gene pyramiding --- Heterodera schachtii --- resistance --- tomato --- Elongated Internode (EI) --- QTL --- GA2ox7 --- n/a

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