Relevant bibliographies by topics / Agricultural Bioinformatics

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Agricultural Bioinformatics'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Agricultural Bioinformatics"

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AHOUSE, JEREMY C. "Bioinformatics–A Middle Way." BioScience 50, no. 3 (2000): 264. http://dx.doi.org/10.1641/0006-3568(2000)050[0264:bamw]2.3.co;2.

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Elwess, Nancy L., Sandra M. Latourelle, and Olivia Cauthorn. "Visualising ‘junk’ DNAthrough bioinformatics." Journal of Biological Education 39, no. 2 (2005): 76–80. http://dx.doi.org/10.1080/00219266.2005.9655966.

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Dalpech, Roger. "Bioinformatics and school biology." Journal of Biological Education 40, no. 4 (2006): 147–48. http://dx.doi.org/10.1080/00219266.2006.9656035.

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Bromham, Lindell. "Putting the ‘bio’ into bioinformatics." Biology Letters 5, no. 3 (2009): 391–93. http://dx.doi.org/10.1098/rsbl.2009.0227.

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Bioinformatic analyses have grown rapidly in sophistication and efficiency to accommodate the vast increase in available data. One of the major challenges has been to incorporate the growing appreciation of the complexity of molecular evolution into new analytical methods. As the reliance on molecular data in biology and medicine increases, we need to be confident that these methods adequately reflect the underlying processes of genome change. This special issue focuses on the way that patterns and processes of molecular evolution are influenced by features of populations of whole organisms, such as selection pressure, population size and life history. The advantage of this approach to molecular evolution is that it views genomic change not simply as a biochemical or stochastic process, but as the result of a complex series of interactions that shape the kinds of genomic changes that can and do happen.
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Bloom, Mark. "Biology insilico: The Bioinformatics Revolution." American Biology Teacher 63, no. 6 (2001): 400–407. http://dx.doi.org/10.1662/0002-7685(2001)063[0397:bistbr]2.0.co;2.

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Ali, Muhammad Muddassir, Muhammad Hamid, Muhammad Saleem, et al. "Status of Bioinformatics Education in South Asia: Past and Present." BioMed Research International 2021 (April 26, 2021): 1–9. http://dx.doi.org/10.1155/2021/5568262.

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Bioinformatics education has been a hot topic in South Asia, and the interest in this education peaks with the start of the 21st century. The governments of South Asian countries had a systematic effort for bioinformatics. They developed the infrastructures to provide maximum facility to the scientific community to gain maximum output in this field. This article renders bioinformatics, measures, and its importance of implementation in South Asia with proper ways of improving bioinformatics education flaws. It also addresses the problems faced in South Asia and proposes some recommendations regarding bioinformatics education. The information regarding bioinformatics education and institutes was collected from different existing research papers, databases, and surveys. The information was then confirmed by visiting each institution’s website, while problems and solutions displayed in the article are mostly in line with South Asian bioinformatics conferences and institutions’ objectives. Among South Asian countries, India and Pakistan have developed infrastructure and education regarding bioinformatics rapidly as compared to other countries, whereas Bangladesh, Sri Lanka, and Nepal are still in a progressing phase in this field. To advance in a different sector, the bioinformatics industry has to be revolutionized, and it will contribute to strengthening the pharmaceutical, agricultural, and molecular sectors in South Asia. To advance in bioinformatics, universities’ infrastructure needs to be on a par with the current international standards, which will produce well-trained professionals with skills in multiple fields like biotechnology, mathematics, statistics, and computer science. The bioinformatics industry has revolutionized and strengthened the pharmaceutical, agricultural, and molecular sectors in South Asia, and it will serve as the standard of education increases in the South Asian countries. A framework for developing a centralized database is suggested after the literature review to collect and store the information on the current status of South Asian bioinformatics education. This will be named as the South Asian Bioinformatics Education Database (SABE). This will provide comprehensive information regarding the bioinformatics in South Asian countries by the country name, the experts of this field, and the university name to explore the top-ranked outputs relevant to queries.
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Bloom, Mark. "Biology in silico: The Bioinformatics Revolution." American Biology Teacher 63, no. 6 (2001): 397–403. http://dx.doi.org/10.2307/4451145.

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MUSANTE, SUSAN. "Using Bioinformatics in the Undergraduate Classroom." BioScience 54, no. 7 (2004): 625. http://dx.doi.org/10.1641/0006-3568(2004)054[0625:ubituc]2.0.co;2.

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Bourne, Philip E. "Is “bioinformatics” dead?" PLOS Biology 19, no. 3 (2021): e3001165. http://dx.doi.org/10.1371/journal.pbio.3001165.

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Khan, Fasiha F., Kaleem Ahmad, Aleem Ahmed, and Shujjah Haider. "APPLICATIONS OF BIOTECHNOLOGY IN AGRICULTURE- REVIEW ARTICLE." World Journal of Biology and Biotechnology 2, no. 1 (2017): 139. http://dx.doi.org/10.33865/wjb.002.01.0013.

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Agricultural biotechnology plays a key role in research tools that scientists use to understand and manipulate the genetic makeup of organisms for use in agriculture: crops, livestock, forestry and fisheries. Biotechnology has vast application than genetic engineering; it also includes genomics and bioinformatics, markers-assisted selection, micropropagation, tissue culture, cloning, artificial insemination, embryo transfer and other technologies. However, genetic engineering, mainly in crop sector, is the area in which biotechnology is most directly affecting agriculture in developing countries and in which the most vital public concerns and policy issues have arisen. Therefore, this review report tries to touches all the aspect of biotechnology in the field of agriculture.
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Dissertations / Theses on the topic "Agricultural Bioinformatics"

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Hocking, Toby Dylan. "Learning algorithms and statistical software, with applications to bioinformatics." Phd thesis, École normale supérieure de Cachan - ENS Cachan, 2012. http://tel.archives-ouvertes.fr/tel-00906029.

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Statistical machine learning is a branch of mathematics concerned with developing algorithms for data analysis. This thesis presents new mathematical models and statistical software, and is organized into two parts. In the first part, I present several new algorithms for clustering and segmentation. Clustering and segmentation are a class of techniques that attempt to find structures in data. I discuss the following contributions, with a focus on applications to cancer data from bioinformatics. In the second part, I focus on statistical software contributions which are practical for use in everyday data analysis.
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Nair, Karthik. "Optimisation of autoencoders for prediction of SNPs determining phenotypes in wheat." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-437451.

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The increase in demand for food has resulted in increased demand for tools that help streamline plant breeding process in order to create new varieties of crops. Identifying the underlying genetic mechanism of favourable characteristics is essential in order to make the best breeding decisions. In this project we have developed a modified autoencoder model which allows for lateral phenotype injection into the latent layer, in order to identify causal SNPs for phenotypes of interest in wheat. SNP and phenotype data for 500 samples of Lantmännen SW Seed provided by Lantmännen was used to train the network. Artificial phenotype created using a single SNP was used during training instead of real phenotype, since the relationship between the phenotype and SNP is already known. The modified training model with lateral phenotype injection showed significant increase in genotype concordance of the artificial phenotype when compared to the control model without phenotype injection. Causal SNP was successfully identified by using concordance terrain graph, where the difference in concordance of individual SNPs  between the modified modified model and control model was plotted against the genomic position of each SNP. The model requires further testing to elucidate its behaviour for phenotypes linked to multiple SNPs.
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Ahmed, Ikhlak. "A bioinformatics analysis of the arabidopsis thaliana epigenome." Phd thesis, Université Paris Sud - Paris XI, 2011. http://tel.archives-ouvertes.fr/tel-00684391.

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Eukaryotic genomes are packed into the confines of the nucleus through a nucleoproteic structure called chromatin. Chromatin is a dynamic structure that can respond to developmental or environmental cues to regulate and orchestrate the functions of the genome. The fundamental unit of chromatin, the nucleosome, consists of a protein octamer, which contains two molecules of each of the core histone proteins (H2A, H2B, H3, H4), around which 147 bp of DNA is wrapped. The post-translational modifications (PTMs) of histones and methylation of the cytosine residues in DNA (DNA methylation) constitute primary epigenomic markers that dynamically alter the interaction of DNA with nucleosomes and participate in the regulation and control access to the underlying DNA. The main objective of my thesis was to understand the spatial and temporal dynamics of chromatin states in Arabidopsis by investigating on a genome-wide scale, patterns of DNA methylation and a set of well-characterized histone post-translational modifications. DNA methylation, a hallmark of epigenetic inactivation and heterochromatin in both plants and mammals, is largely confined to transposable elements and other repeat sequences. I show in this thesis that in Arabidopsis, methylated TE sequences having no or few matching siRNAs, and therefore unlikely to be targeted by the RNA-directed DNA methylation (RdDM) machinery, acquire DNA methylation through spreading from adjacent siRNA-targeted regions. Further, I propose that this spreading of DNA methylation through promoter regions can explain, at least in part, the negative impact of siRNA-targeted TE sequences on neighbouring gene expression. In a second part, I have contributed to integrative analysis of DNA methylation and eleven histone PTMs. I have shown through combinatorial and cluster analysis that the Arabidopsis epigenome shows simple principles of organisation and can be distinguished into four primary types of chromatin that preferentially index active genes, repressed genes, TEs, and intergenic regions. Finally, in a third part, I integrated epigenomics with transcriptome data at three different time points in a developmental window to investigate the temporal dynamics of chromatin states in response to an external stimulus. This used the light-induced transcriptional response as a paradigm to assess the impact of histone H2B monoubiquitination (H2Bub), and showed that this PTM is associated with active transcription and implicated in the selective fine-tuning of gene expression. Taken together, the work presented here contributes significantly to our understanding of the spatial organisation of chromatin states in plants, its dynamic nature and how it can contribute to allow plants to respond to a signal from the environment.
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Orozco, Alina. "A spatial analysis of Norwegian spruce cone developmental stages." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-425746.

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The Norway spruce Picea abies is an economically important export to the Swedish economy. There are a number of environmental and endogenous factors that impact the generation time of this species meaning that it can take 20-25 years for a tree to mature. The long generation time creates a challenge for plant breeding programs in terms of how genetic mechanisms are able to be studied as well as how quickly trees can be produced for lumber. The characterization of gene expression patterns in the context of special tissue domains is essential to understanding the underlying functions behind complex biological systems and in the case of P. abies may prove more crucial to determining the activation of genes at specific reproductive growth points. There are several techniques available for the analysis of spatial expression profiles, however, the unique high throughput nature coupled to the morphological information provided by Spatial Transcriptomics creates new opportunities for exploratory analysis. Spatial Transcriptomics offers a distinct approach to answering fundamental questions about the genetic mechanisms that regulate reproductive phase change and cone-setting in conifers. This study focuses on spatial gene expression analysis and the integration of de novo transcriptome assembly contigs to confirm the spatial context of putatively discovered genes such as DAL1, DAL2, DAL3, and DAL10 from previous studies and to potentially localize transcripts that could not previously be identified due to the inability to obtain complete transcripts. The aim is to create a workflow to identify genes that contribute to the growth patterns in the naturally occurring acrocona mutant that could prove useful to improving tree breeding programs.
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Machemer-Noonan, Katja Marlene. "Interplay between unusual MYB transcription factors and their role in cell size regulation in plants." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1397482170.

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McGinley, Susan. "Bioinformatics at BIO5: Professional Science Master's Internships." College of Agriculture, University of Arizona (Tucson, AZ), 2007. http://hdl.handle.net/10150/295889.

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Sathanantham, Preethi. "Impact of Mutations of Targeted Serine, Histidine, and Glutamine Residues in Citrus paradisi Flavonol Specific Glucosyltransferase Activity." Digital Commons @ East Tennessee State University, 2015. https://dc.etsu.edu/etd/2560.

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A flavonol specific glucosyltransferase cloned from Citrus paradisi has strict substrate and regio-specificity (Cp3OGT). The amino acid sequence of Cp3OGT was aligned with sequences of an anthocyanidin UDP- dependant glucosyltransferase (UGT) from Clitorea ternatea and a UGT from Vitis vinifera that can glucosylate both flavonols and anthocyanidins. Using homology modeling to identify candidate regions followed by site directed mutagenesis, three double mutations were constructed and biochemically characterized. S20G+T21S mutant protein retained activity with flavonols similar to the wildtype Cp3OGT but the mutant had optimum activity at 60°C and broadened substrate acceptance to include the flavanone naringenin. S290C+S319A mutant protein retained 40% activity with quercetin relative to WT, and had an optimum pH shift. H154Y+Q87I mutant protein was only 10% active with quercetin relative to WT. Docking analysis revealed that H154, Q87 and S20 could be involved in orienting the acceptor molecules within the acceptor binding site whereas S319 and S290 residues are involved in maintaining the active site conformation.
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Pan, Juan. "Ether Bridge Formation and Chemical Diversification in Loline Alkaloid Biosynthesis." UKnowledge, 2014. http://uknowledge.uky.edu/plantpath_etds/14.

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Loline alkaloids, found in many grass-Epichloë symbiota, are toxic or feeding deterrent to invertebrates. The loline alkaloids all share a saturated pyrrolizidine ring with a 1-amine group and an ether bridge linking C2 and C7. The steps in biosynthesis of loline alkaloids are catalyzed by enzymes encoded by a gene cluster, designated LOL, in the Epichloë genome. This dissertation addresses the enzymatic, genetic and evolutionary basis for diversification of these alkaloids, focusing on ether bridge formation and the subsequent modifications of the 1-amine to form different loline alkaloids. Through gene complementation of a natural lolO mutant and comparison of LOL clusters in strains with different loline alkaloid profiles, I found that lolO, predicted to encode a 2-oxoglutarate-dependent nonheme iron (2OG/Fe) dioxygenase, is required in formation of the ether bridge. Through application of isotopically labeled compound to Epichloë uncinata culture, I established that exo-1-acetamidopyrrolizidine (AcAP) and N-acetylnorloline (NANL) are true pathway intermediates. Application of AcAP to yeast expressing lolO resulted in production of NANL, establishing that LolO is sufficient to catalyze this unusual oxygenation reaction. After ether formation, modifications on the 1-amino group give loline, N-methylloline (NML), N-formylloline (NFL) and N-acetylloline (NAL). A double knockout of lolN, predicted to encode an acetamidase, and lolM, predicted to encode a methyltransferase, produced only NANL. Complementation of the double knockout with wild-type lolN and lolM restored the loline alkaloid profile. These results indicate that LolN is involved in deacetylating NANL to produce norloline, which is then modified to form the other lolines. Crude protein extract of a yeast transformant expressing LolM converted norloline to loline and NML, and loline to NML, supporting the hypothesis that LolM functions as a methyltransferase in the loline-alkaloid biosynthesis pathway. The alkaloid NAL was observed in some but not all plants symbiotic with Epichloë siegelii, and when provided with exogenous loline, asymbiotic meadow fescue (Lolium pratense) plants produced N-acetylloline (NAL), indicating that a plant acetyltransferase converts loline to NAL. I further analyzed the basis for loline alkaloid diversity by comparing the LOL clusters in the Epichloë and Atkinsonella species with different loline alkaloid profiles, and found that LOL clusters changed position, orientation and gene content over their evolutionary history. Frequent, independent losses of some or all late pathway genes, lolO, lolN, lolM and lolP, resulted in diverse loline alkaloid profiles. In addition, phylogenetic analyses demonstrated transspecies polymorphism of the LOL clusters. Based on my findings, I established that in Epichloë and Atkinsonella species the ether bridge is formed on acetamidopyrrolizidine. My study of the loline alkaloid profile of Adenocarpus decorticans (Fabaceae) suggests that these plants probably use a similar strategy at least with respect to ether-bridge formation. Further diversification steps of loline alkaloids in grass-Clavicipitaceae symbiota are carried out by enzymes of both Epichloë species and the host plant. Finally, I present evidence that LOL clusters have evolved by balancing selection for chemical diversity.
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Roux, Simon. "Diversité, évolution et écologie virale : des communautés aux génotypes. Analyse bioinformatique de métagénomes viraux." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2013. http://tel.archives-ouvertes.fr/tel-00908344.

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Les virus sont omniprésents dans la biosphère et infectent vraisemblablement l'ensemble des êtres vivants. Au sein des écosystèmes, ils ont ainsi un impact sur la diversité des populations microbiennes, l'évolution des génomes de ces populations, et directement ou indirectement sur les cycles biogéochimiques majeurs. Leur caractère protéiforme et l'absence de marqueur unique (tant génétique que physique) font toutefois de l'exploration de la diversité virale une tâche complexe, de telle sorte que nos connaissances sur ces communautés virales environnementales sont encore très limitées. La métagénomique, ou séquençage massif et aléatoire de fragments nucléotidiques extraits d'un prélèvement, offre un point de vue unique sur les génomes viraux. Ce type d'approche, récemment développé, a ainsi mis en évidence la richesse extraordinaire des populations virales environnementales, tant du point de vue des gènes que des génotypes. C'est dans ce cadre de l'étude des communautés virales de l'environnement par métagénomique que se sont inscrits les travaux de cette thèse, organisée autour de quatre axes principaux : * Le développement de nouvelles méthodes d'analyses adaptées aux spécificités des génomes et métagénomes viraux par la mise en place du serveur web Metavir, premier serveur dédié à l'analyse des viromes. Proposant aujourd'hui un ensemble cohérent d'outils pour différents types de viromes, Metavir compte plus de 300 utilisateurs pour plus de 2000 viromes analysés. * Le potentiel fonctionnel des génomes viraux a pu être approché par l'étude conjointe d'un ensemble de viromes. Après une analyse rigoureuse des contaminations potentielles, nous avons pu confirmer que les génomes viraux comprenaient un ensemble limité mais non négligeable de gènes associés au métabolisme cellulaire. La plupart des virus agissent ainsi certainement directement sur le métabolisme de la cellule hôte durant l'infection. * La prépondérance des paramètres environnementaux, et particulièrement de la salinité, en tant que facteurs structurant les communautés virales aquatiques a également pu être mise en avant. La distance géographique entre prélèvements semble n'avoir qu'une influence secondaire, confirmant la capacité importante de dispersion des capsides virales. Une adaptation locale semble toutefois exister dans certains cas, notamment en cas de compétition importante entre les résistances développées par les hôtes et les capacités d'infection des virus. * Enfin, différentes familles de petits virus à ADN simple brin ont pu être caractérisées par une méta-analyse de viromes. Leur apparente simplicité a ainsi révélé des mécanismes d'évolution plus complexes que prévus, impliquant différents cycles et capacités de transfert de gènes jusqu'ici plutôt considérés comme l'apanage des virus à ADN double brin, et remettant en cause les séparations admises entre les différents groupes de virus sur la base de la nature de leur génome. En permettant une étude depuis l'échelle de la communauté jusqu'à des génotypes spécifiques, les viromes constituent des outils de choix pour caractériser la diversité virale, appréhender les différents facteurs régulant ces communautés, et ainsi mieux comprendre la place des virus dans la biosphère. De plus, ces études ont confirmé l'existence d'interactions étroites entre virus et organismes cellulaires, ces interactions semblant nombreuses, multiples dans leurs natures et conséquences, et présentes tout au long de l'histoire du vivant. Ces nouvelles connaissances apportées par l'analyse de viromes permettent donc d'aborder certaines questions fondamentales concernant l'origine des grandes innovations évolutives ou le fonctionnement global des écosystèmes.
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Sarkar, Anita. "Facettes de glycobioinformatique : applications à l'étude des interactions protéines-sucres." Phd thesis, Université de Grenoble, 2012. http://tel.archives-ouvertes.fr/tel-00870801.

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Le travail décrit dans ce manuscrit rassemble les résultats obtenus au cours de ma thèse de doctorat. Ils s'inscrivent dans le domaine de la glycobioinformatique. Ils ont impliqué des développements de bases de données structurales et des applications en modélisation moléculaire des interactions protéines-sucres. Les méthodes de modélisation moléculaire ont été utilisées dans la reconstruction et dans la prédiction des structures tridimensionnelles de polysaccharides et d'oligosaccharides, ces dernières étant également établies par une approche de type "haut-débit" par application d'un algorithme génétique à des fins de minimisation énergétique. Les données ainsi générées ont été organisées sous la forme de bases de données relationnelles, proprement annotées (PolySca3DB et BiOligo) qui sont en libre accès pour consultation sur internet. Ces méthodes de modélisation moléculaire ont été appliquées à la caractérisation, par RMN en solution, des conformations de basse énergie d'une souche pathogène d'un polysaccharide de la bactérie E. coli. D'autres bactéries pathogènes de type gram négatif, interagissent avec des oligosaccharides par l'intermédiaire de protéines secrétées, telles que des lectines. Nous avons testé, au travers de l'utilisation de méthodes d'amarrage moléculaire, la possibilité d'identifier de manière automatique, la nature de ces interactions, en prenant comme cibles des épitopes oligosaccharidiques fucosylés. Les résultats de ces recherches ont été comparés, de manière critique, à ceux issus de l'application de bio-puces à sucres et de calorimétrie isotherme de titration. Les conclusions et perspectives de ces travaux sont présentées dans un article de revue consacré à l'application des méthodes de chimie computationnelle dans l'étude des interactions protéines-glucides qui viennent compléter l'arsenal des outils dédiés au champs de recherche couvert par la glycobiologie structurale et moléculaire.
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Books on the topic "Agricultural Bioinformatics"

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P.B., Kavi Kishor, Rajib Bandopadhyay, and Prashanth Suravajhala, eds. Agricultural Bioinformatics. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1880-7.

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Li, Daoliang. Computer And Computing Technologies In Agriculture, Volume II: First IFIP TC 12 International Conference on Computer and Computing Technologies in Agriculture (CCTA 2007), Wuyishan, China, August 18-20, 2007. International Federation for Information Processing, 2008.

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Upadhyay, Atul Kumar, R. Sowdhamini, and Virupaksh U. Patil, eds. Bioinformatics for agriculture: High-throughput approaches. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4791-5.

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Basher, Mian M. Abul, and Rajshahi University. Department of Statistics, eds. International Conference on Statistical Data Mining for Bioinformatics, Health, Agriculture and Environment, 21-24 December, 2012: Proceedings. Higher Education Quality Enhancement Program, 2012.

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Kenneth, Blum, and Madigan Margaret A, eds. OMICS: Biomedical perspectives and applications. Taylor & Francis, 2012.

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Suravajhala, Prashanth, Kavi Kishor P. B, and Rajib Bandopadhyay. Agricultural Bioinformatics. Springer, 2014.

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Suravajhala, Prashanth, Kavi Kishor P. B, and Rajib Bandopadhyay. Agricultural Bioinformatics. Springer, 2016.

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Nelson, Stuart. Dielectric Properties of Agricultural Materials and Their Applications. Elsevier Science & Technology, 2015.

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K, Arora Dilip, Berka Randy M. 1954-, and Singh Gautam B, eds. Applied mycology and biotechnology. Elsevier, 2006.

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Barh, Debmalya, Vasco Azevedo, and Vasudeo Zambare. Omics: Applications in Biomedical, Agricultural, and Environmental Sciences. Taylor & Francis Group, 2017.

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Book chapters on the topic "Agricultural Bioinformatics"

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Pasam, Raj K., and Rajiv Sharma. "Association Mapping: A New Paradigm for Dissection of Complex Traits in Crops." In Agricultural Bioinformatics. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1880-7_1.

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James, Priyanka, S. Silpa, and Raghunath Keshavachandran. "Bioinformatics Strategies Associated with Important Ethnic Medicinal Plants." In Agricultural Bioinformatics. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1880-7_10.

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Sakata, Katsumi, Takuji Nakamura, and Setsuko Komatsu. "Mining Knowledge from Omics Data." In Agricultural Bioinformatics. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1880-7_11.

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Chavali, L. N. "Cloud Computing in Agriculture." In Agricultural Bioinformatics. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1880-7_12.

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Koduru, Uma Devi, Sandhya Galidevara, Annette Reineke, and Akbar Ali Khan Pathan. "Bioinformatic Tools in the Analysis of Determinants of Pathogenicity and Ecology of Entomopathogenic Fungi Used as Microbial Insecticides in Crop Protection." In Agricultural Bioinformatics. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1880-7_13.

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Thakur, Subarna, Asim K. Bothra, and Arnab Sen. "Exploring the Genomes of Symbiotic Diazotrophs with Relevance to Biological Nitrogen Fixation." In Agricultural Bioinformatics. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1880-7_14.

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Pathak, Khyatiben V., and Sivaramaiah Nallapeta. "Plant-Microbial Interaction: A Dialogue Between Two Dynamic Bioentities." In Agricultural Bioinformatics. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1880-7_15.

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Singh, Tiratha Raj. "Machine Learning with Special Emphasis on Support Vector Machines (SVMs) in Systems Biology: A Plant Perspective." In Agricultural Bioinformatics. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1880-7_16.

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Suravajhala, Renuka, Rajdeep Poddar, Sivaramaiah Nallapeta, and Saif Ullah. "Xanthine Derivatives: A Molecular Modeling Perspective." In Agricultural Bioinformatics. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1880-7_17.

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Gupta, Sohini, Sayak Ganguli, and Abhijit Datta. "The Silent Assassins: Informatics of Plant Viral Silencing Suppressors." In Agricultural Bioinformatics. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1880-7_2.

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Conference papers on the topic "Agricultural Bioinformatics"

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Santisirisomboon, Jerasorn, and Jaruthat Santisirisomboon. "Agricultural Residue Biomass Resources in Thailand." In Computational Intelligence and Bioinformatics / Modelling, Simulation, and Identification. ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.755-038.

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Santisirisomboon, Jerasorn, and Jaruthat Santisirisomboon. "Agricultural Residue Biomass Resources in Thailand." In Computational Intelligence and Bioinformatics / Modelling, Simulation, and Identification. ACTAPRESS, 2012. http://dx.doi.org/10.2316/p.2012.755-038.

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Vizza, Patrizia, Giuseppe Tradigo, Pierangelo Veltri, et al. "Tracking agricultural products for wellness care." In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2018. http://dx.doi.org/10.1109/bibm.2018.8621161.

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Shi, Henghua, and Xin Xu. "Study on the Talent Flexible Training Mode of Bioinformatics Direction in Agricultural Information." In 2016 4th International Conference on Management, Education, Information and Control (MEICI 2016). Atlantis Press, 2016. http://dx.doi.org/10.2991/meici-16.2016.117.

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"Assessment of genetic diversity in the wheat genetic resources based on agricultural traits." In Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 2019. http://dx.doi.org/10.18699/plantgen2019-167.

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Xu, Huashan, Yufen Ren, Tongqian Zhao, Mingjie Zhao, and Chaohong Ma. "Agricultural Non-Point Nitrogen Pollution Control Function by Phragmites." In 2009 3rd International Conference on Bioinformatics and Biomedical Engineering (iCBBE). IEEE, 2009. http://dx.doi.org/10.1109/icbbe.2009.5162295.

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Khanina, L. G., V. E. Smirnov, S. S. Bykhovets, M. S. Romanov, and M. V. Bobrovsky. "Analysis of spatiotemporal data to assess the influence of grass fires on the vegetation in abandoned agricultural lands." In Mathematical Biology and Bioinformatics. IMPB RAS - Branch of KIAM RAS, 2018. http://dx.doi.org/10.17537/icmbb18.108.

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Jiang, Hong, and Qingxiang Guo. "Experimental Investigation on Converting of Agricultural Waste to Bio-Gas." In 2008 2nd International Conference on Bioinformatics and Biomedical Engineering. IEEE, 2008. http://dx.doi.org/10.1109/icbbe.2008.544.

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Tradigo, Giuseppe, Patrizia Vizza, Pierangelo Veltri, et al. "SISTABENE: an information system for the traceability of agricultural food production." In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2019. http://dx.doi.org/10.1109/bibm47256.2019.8983039.

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Li, Jingjing, Hongzhi Wang, Yong Zhou, and Rendong Li. "Dynamics and Driving Factors of Agricultural Landscape in Jianghan Plain." In 2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2010). IEEE, 2010. http://dx.doi.org/10.1109/icbbe.2010.5516606.

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