Relevant bibliographies by topics / Bioinformatics application

Contents

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

Academic literature on the topic 'Bioinformatics application'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Bioinformatics application"

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Ellis, John, and David A. Morrison. "Application of bioinformatics to parasitology." International Journal for Parasitology 35, no. 5 (2005): 463–64. http://dx.doi.org/10.1016/j.ijpara.2005.02.011.

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Finak, G., N. Godin, M. Hallett, et al. "BIAS: Bioinformatics Integrated Application Software." Bioinformatics 21, no. 8 (2004): 1745–46. http://dx.doi.org/10.1093/bioinformatics/bti170.

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Li, Huixing, Yan Xue, and Xiancai Zeng. "Investigation of data mining technique and artificial intelligence algorithm in microflora bioinformatics." E3S Web of Conferences 267 (2021): 01040. http://dx.doi.org/10.1051/e3sconf/202126701040.

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Bioinformatics has gradually received widespread attention and has shown the characteristics of a large amount of calculation and high complexity. Therefore, it is required to adopt computer algorithms in bioinformatics to improve the efficiency of bioinformatics processing problems. Big data and artificial intelligence technologies have the characteristics of supporting bioinformatics and have achieved certain results in the field of bioinformatics. Introduced the application basis of big data and artificial intelligence in bioinformatics, analyzed data collection, preprocessing, data storage and management, data analysis, and mining technology. Furthermore, typical applications in bioinformatics are discussed in terms of gene expression data analysis, genome sequence information analysis, biological sequence difference and similarity analysis, genetic data analysis, and protein structure and function prediction. Finally, the bottlenecks and challenges in the application of big data and artificial intelligence in bioinformatics are discussed, and the application prospects of related technologies in bioinformatics have prospected.
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Barrett, Steven J. "Intelligent Bioinformatics: The Application of Artificial Intelligence Techniques to Bioinformatics Problems." Genetic Programming and Evolvable Machines 7, no. 3 (2006): 283–84. http://dx.doi.org/10.1007/s10710-006-7003-4.

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Du, Rui Fang, Jing Yu Li, Jian Li Liu, and Ji Zhao Zhao. "Application of Bioinformatics in Microbial Ecology." Advanced Materials Research 955-959 (June 2014): 276–80. http://dx.doi.org/10.4028/www.scientific.net/amr.955-959.276.

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The major goal of microbial ecology is to study the structure and function of complex microbial communities. Various bioinformatics software were employed to handle a large number of genomic information emerged by using high throughput sequencing. This paper summarizes application of bioinformatics in microbial ecology and their corresponding software used in α, β-diversity studies; and finally expounds the important roles in establishment of four synthesis databases.
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Sun, Y., S. Zhao, H. Yu, G. Gao, and J. Luo. "ABCGrid: Application for Bioinformatics Computing Grid." Bioinformatics 23, no. 9 (2007): 1175–77. http://dx.doi.org/10.1093/bioinformatics/btm086.

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Zhang, Yi. "Application Swarming Intelligence in Bioinformatics: Survey." Journal of Bioinformatics and Intelligent Control 1, no. 1 (2012): 27–39. http://dx.doi.org/10.1166/jbic.2012.1015.

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Lopes, Robson da Silva, Nathalia Maria Resende, Adenilda Cristina Honorio-França, and Eduardo Luzía França. "Application of Bioinformatics in Chronobiology Research." Scientific World Journal 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/153839.

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Bioinformatics and other well-established sciences, such as molecular biology, genetics, and biochemistry, provide a scientific approach for the analysis of data generated through “omics” projects that may be used in studies of chronobiology. The results of studies that apply these techniques demonstrate how they significantly aided the understanding of chronobiology. However, bioinformatics tools alone cannot eliminate the need for an understanding of the field of research or the data to be considered, nor can such tools replace analysts and researchers. It is often necessary to conduct an evaluation of the results of a data mining effort to determine the degree of reliability. To this end, familiarity with the field of investigation is necessary. It is evident that the knowledge that has been accumulated through chronobiology and the use of tools derived from bioinformatics has contributed to the recognition and understanding of the patterns and biological rhythms found in living organisms. The current work aims to develop new and important applications in the near future through chronobiology research.
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YANG, HOWARD H., and MAXWELL P. LEE. "Application of Bioinformatics in Cancer Epigenetics." Annals of the New York Academy of Sciences 1020, no. 1 (2004): 67–76. http://dx.doi.org/10.1196/annals.1310.008.

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Vassilev, D., J. Leunissen, A. Atanassov, A. Nenov, and G. Dimov. "Application of Bioinformatics in Plant Breeding." Biotechnology & Biotechnological Equipment 19, sup3 (2005): 139–52. http://dx.doi.org/10.1080/13102818.2005.10817293.

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Dissertations / Theses on the topic "Bioinformatics application"

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Malm, Patrik. "Development of a hierarchical k-selecting clustering algorithm – application to allergy." Thesis, Linköping University, The Department of Physics, Chemistry and Biology, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-10273.

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<p>The objective with this Master’s thesis was to develop, implement and evaluate an iterative procedure for hierarchical clustering with good overall performance which also merges features of certain already described algorithms into a single integrated package. An accordingly built tool was then applied to an allergen IgE-reactivity data set. The finally implemented algorithm uses a hierarchical approach which illustrates the emergence of patterns in the data. At each level of the hierarchical tree a partitional clustering method is used to divide data into k groups, where the number k is decided through application of cluster validation techniques. The cross-reactivity analysis, by means of the new algorithm, largely arrives at anticipated cluster formations in the allergen data, which strengthen results obtained through previous studies on the subject. Notably, though, certain unexpected findings presented in the former analysis where aggregated differently, and more in line with phylogenetic and protein family relationships, by the novel clustering package.</p>
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Li, Yong-Jun. "The application of statistical physics in bioinformatics /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?PHYS%202003%20LI.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003.<br>Includes bibliographical references (leaves 55-58). Also available in electronic version. Access restricted to campus users.
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Momin, Amin Altaf. "Application of bioinformatics in studies of sphingolipid biosynthesis." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34842.

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The studies in this dissertation demonstrate that the gene expression pathway maps are useful tools to notice alteration in different branches of sphingolipid biosynthesis pathway based on microarray and other transcriptomic analysis. To facilitate the integrative analysis of gene expression and sphingolipid amounts, updated pathway maps were prepared using an open access visualization tool, Pathvisio v1.1. The datasets were formatted using Perl scripts and visualized with the aid of color coded pathway diagrams. Comparative analysis of transcriptomics and sphingolipid alterations from experimental studies and published literature revealed 72.8 % correlation between mRNA and sphingolipid differences (p-value < 0.0001 by the Fisher's exact test).The high correlation between gene expression differences and sphingolipid alterations highlights the application of this tool to evaluate molecular changes associate with sphingolipid alterations as well as predict differences in specific metabolites that can be experimentally verified using sensitive approaches such as mass spectrometry. In addition, bioinformatics sequence analysis was used to identify transcripts for sphingolipid biosynthesis enzyme 3-ketosphinganine reductase, and homology modeling studies helped in the evaluation of a cell line defective in sphingolipid metabolism due to mutation in the enzyme serine palmitoyltransferase, the first enzyme of de novo biosynthesis pathway. Hence, the combination of different bioinformatics approaches, including protein and DNA sequence analysis, structure modeling and pathway diagrams can provide valuable inputs for biochemical and molecular studies of sphingolipid metabolism.
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Tarcha, Eric J. "Application of Immunoproteomics and Bioinformatics to coccidioidomycosis Vaccinology." University of Toledo Health Science Campus / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=mco1154441973.

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Kiritchenko, Svetlana. "Hierarchical text categorization and its application to bioinformatics." Thesis, University of Ottawa (Canada), 2006. http://hdl.handle.net/10393/29298.

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In a hierarchical categorization problem, categories are partially ordered to form a hierarchy. In this dissertation, we explore two main aspects of hierarchical categorization: learning algorithms and performance evaluation. We introduce the notion of consistent hierarchical classification that makes classification results more comprehensible and easily interpretable for end-users. Among the previously introduced hierarchical learning algorithms, only a local top-down approach produces consistent classification. The present work extends this algorithm to the general case of DAG class hierarchies and possible internal class assignments. In addition, a new global hierarchical approach aimed at performing consistent classification is proposed. This is a general framework of converting a conventional "flat" learning algorithm into a hierarchical one. An extensive set of experiments on real and synthetic data indicate that the proposed approach significantly outperforms the corresponding "flat" as well as the local top-down method. For evaluation purposes, we use a novel hierarchical evaluation measure that is superior to the existing hierarchical and non-hierarchical evaluation techniques according to a number of formal criteria. Also, this dissertation presents the first endeavor of applying the hierarchical text categorization techniques to the tasks of bioinformatics. Three bioinformatics problems are addressed. The objective of the first task, indexing biomedical articles with Medical Subject Headings (MeSH), is to associate documents with biomedical concepts from the specialized vocabulary of MeSH. In the second application, we tackle a challenging problem of gene functional annotation from biomedical literature. Our experiments demonstrate a considerable advantage of hierarchical text categorization techniques over the "flat" method on these two tasks. In the third application, our goal is to enrich the analysis of plain experimental data with biological knowledge. In particular, we incorporate the functional information on genes directly into the clustering process of microarray data with the outcome of an improved biological relevance and value of clustering results.
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Abbas, Naeem. "Acceleration of a bioinformatics application using high-level synthesis." Phd thesis, École normale supérieure de Cachan - ENS Cachan, 2012. http://tel.archives-ouvertes.fr/tel-00847076.

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The revolutionary advancements in the field of bioinformatics have opened new horizons in biological and pharmaceutical research. However, the existing bioinformatics tools are unable to meet the computational demands, due to the recent exponential growth in biological data. So there is a dire need to build future bioinformatics platforms incorporating modern parallel computation techniques. In this work, we investigate FPGA based acceleration of these applications, using High-Level Synthesis. High-Level Synthesis tools enable automatic translation of abstract specifications to the hardware design, considerably reducing the design efforts. However, the generation of an efficient hardware using these tools is often a challenge for the designers. Our research effort encompasses an exploration of the techniques and practices, that can lead to the generation of an efficient design from these high-level synthesis tools. We illustrate our methodology by accelerating a widely used application -- HMMER -- in bioinformatics community. HMMER is well-known for its compute-intensive kernels and data dependencies that lead to a sequential execution. We propose an original parallelization scheme based on rewriting of its mathematical formulation, followed by an in-depth exploration of hardware mapping techniques of these kernels, and finally show on-board acceleration results. Our research work demonstrates designing flexible hardware accelerators for bioinformatics applications, using design methodologies which are more efficient than the traditional ones, and where resulting designs are scalable enough to meet the future requirements.
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Lou, Xuemei. "Methods Evaluation and Application in Complex Human Genetic Disease." NCSU, 2008. http://www.lib.ncsu.edu/theses/available/etd-06122008-114358/.

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One of the most important tasks in human genetics is to search for disease susceptibility genes. Linkage and association analyses are two major approaches for disease-gene mapping. Chapter 1 reviewed the development of disease-gene mapping methods in the past decades. Gene mapping of complex human diseases often results in the identification of multiple potential risk variants within a gene and/or in the identification of multiple genes within a linkage peak. Thus a question of interest is to test whether the linkage result can be explained in part or in full by the candidate SNP if it shows evidence of association, and then provide some guidance for the next time-consuming step of positional cloning of susceptibility genes. Two methods, GIST and LAMP, which access whether the SNP can partially or fully account for the linkage signal in the region identified by a linkage scan, are evaluated on Genetic Analysis Workshop 15 (GAW15) simulated rheumatoid arthritis (RA) data and discussed in Chapter 2. The simulation results showed that GIST is simple and works slightly better than LAMP-LE test when there is little linkage evidence, LAMP linkage test has limited power when there is not much linkage evidence, and LAMP association test is the best not only when the linkage evidence is extremely high, but also when there is some LD between the candidate SNP and the trait locus. The fact that complex traits are often determined by multiple genetic and environmental factors with small-to-moderate effects makes it important to investigate the behavior of current association methods under multiple risk variants model. In Chapter 3, we compared APL, FBAT, LAMP, APL-Haplotype, FBAT-LC and APL-OSA conditional test in five multiple risk variants models. The simulation results showed that the power of single marker association tests is closely correlated with the amount of LD between marker and disease loci, and these tests maintain good power to detect multiple risk variants in a small region with moderate degree of LD for fully genotyped families. Global tests, such as FBAT-LC are sensitive to the presence of at least one susceptibility variant, but are not helpful for selecting the most promising SNPs for further study. We reported that if multiple haplotypes are associated with different disease loci, the haplotype tests results can be misleading while APL-OSA conditional test has the greatest power to properly dissect the clustered associated markers for all models with an acceptable type I error rate ranging from 0.033 to 0.056. We applied APL-OSA conditional test on GENECARD samples, and got reasonable results. One linkage region of particular interest on chromosome 3 was identified by two independent genome linkage scan with Coronary Artery Disease (CAD). Multiple disease susceptibility genes have been reported from this region, and there are also linkage evidence that this region may harbors a gene or genes determining HDL-C levels. Within this region, a search for HDL-C QTL and analyses of the relationship between genetic variants, HDL-C level to CAD risk are discussed in Chapter 4. We performed CAD association and HDL-C QTL analysis on two independent datasets. We identified SNP rs2979307 in the OSBPL11 gene which survives a Bonferroni correction. We observed different HDL-C trends with HDL-C associated SNPs. Even with the evident heterogeneity presented in our CAD population, we detected several association signals with SNPs in KALRN, MYLK, CDGAP and PAK2 genes in both CAD datasets for HDL-C, where all these genes belong to a Rho pathway.
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Zhou, Yu. "Application of RNA Bioinformatics in decoding RNA structure and regulation." Paris 11, 2008. http://www.theses.fr/2008PA112234.

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Ma thèse porte sur le développement de méthodologies informatiques et bioinformatiques pour résoudre des problèmes provenant de questions biologiques liées à l’ARN, telles que la prédiction de structures, l’identification de structures communes, la découverte de cibles des micro-ARN, la prédiction de la régulation de l’épissage, et le design (ou repliement inverse) d'ARN. Le premier chapitre concerne la mise en place d’une méthode itérative pour la prédiction des structures secondaires des introns de groupes 1, incluant les pseudo-nœuds, et la développement d’une base de données complète sur les introns de groupe 1. Dans le deuxième chapitre, je décris mon travail sur l’analyse bioinformatique de la structure des sites d’incorporation de la Pyrrolysine, le 22ème acide aminé, dans des gènes d’archae. Les troisième et quatrième chapitres sont consacrés au développement et à la mise en œuvre de deux méthodes d’analyse de données expérimentales pour la recherche, dans les séquences d’ARN, de cibles de micro-ARN, et de sites de fixation de protéines impliquées dans le processus d’épissage des introns. Enfin, le cinquième chapitre présente un algorithme de design de structures d’ARN avec des contraintes de motifs, faisant appel à des manipulations d’automates et de grammaires non contextuelles<br>My thesis focuses on the application of RNA bioinformatics analysis to solve the problems originated from biological requirements, ranging from structure prediction, common structure identification, microRNA target discovery, splicing regulation prediction, and RNA design (inverse folding). The first chapter concerns the establishment of an iterative method for the secondary structure prediction of group I introns including pseudo-knots, and the development of a comprehensive group I intron sequence and structure database. In the second chapter, I describe my work on bioinformatics analysis of the Pyrrolysine (Pyl, 22nd amino acid) insertion structure in Pyl-associated genes in archaea. The third and fourth chapters are devoted to develop two methods of experimental data analysis for identification of micro-RNA target sites, and for determination of binding sites of a RNA binding protein implicated in pre-mRNA splicing, independently. Finally, the fifth chapter presents an algorithm for RNA design under motif constraints, involving manipulation of automata and context-free grammars
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Zaslavskiy, Mikhail. "Graph matching and its application in computer vision and bioinformatics." Paris, ENMP, 2010. http://www.theses.fr/2010ENMP1659.

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Le problème d'alignement de graphes, qui joue un rôle central dans différents domaines de la reconnaissance de formes, est l'un des plus grands défis dans le traitement de graphes. Nous proposons une méthode approximative pour l'alignement de graphes étiquetés et pondérés, basée sur la programmation convexe concave. Une application importante du problème d'alignement de graphes est l'alignement de réseaux d'interactions de protéines, qui joue un rôle central pour la recherche de voies de signalisation conservées dans l'évolution, de complexes protéiques conservés entre les espèces, et pour l'identification d'orthologues fonctionnels. Nous reformulons le problème d'alignement de réseaux d'interactions comme un problème d'alignement de graphes, et étudions comment les algorithmes existants d'alignement de graphes peuvent être utilisés pour le résoudre. Dans la formulation classique de problème d'alignement de graphes, seules les correspondances bijectives entre les noeuds de deux graphes sont considérées. Dans beaucoup d'applications, cependant, il est plus intéressant de considérer les correspondances entre des ensembles de noeuds. Nous proposons une nouvelle formulation de ce problème comme un problème d'optimisation discret, ainsi qu'un algorithme approximatif basé sur une relaxation continue. Nous présentons également deux résultats indépendents dans les domaines de la traduction automatique statistique et de la bio-informatique. Nous montrons d'une part comment le problème de la traduction statistique basé sur les phrases peut être reformulé comme un problème du voyageur de commerce. Nous proposons d'autre part une nouvelle mesure de similarité entre les sites de fixation de protéines, basée sur la comparaison 3D de nuages atomiques<br>The graph matching problem is among the most important challenges of graph processing, and plays a central role in various fields of pattern recognition. We propose an approximate method for labeled weighted graph matching, based on a convex-concave programming approach which can be applied to the matching of large sized graphs. This method allows to easily integrate information on graph label similarities into the optimization problem, and therefore to perform labeled weighted graph matching. One of the interesting applications of the graph matching problem is the alignment of protein-protein interaction networks. This problem is important when investigating evolutionary conserved pathways or protein complexes across species, and to help in the identification of functional orthologs through the detection of conserved interactions. We reformulate PPI alignment as a graph matching problem, and study how state-of-the-art graph matching algorithms can be used for this purpose. In the classical formulation of graph matching, only one-to-one correspondences are considered, which is not always appropriate. In many applications, it is more interesting to consider many-to-many correspondences between graph vertices. We propose a reformulation of the many-to-many graph matching problem as a discrete optimization problem and we propose an approximate algorithm based on a continuous relaxation. In this thesis, we also present two interesting results in statistical machine translation and bioinformatics. We show how the phrase-based statistical machine translation decoding problem can be reformulated as a Traveling Salesman Problem. We also propose a new protein binding pocket similarity measure based on a comparison of 3D atom clouds
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Rajabi, Zeyad. "BIAS : bioinformatics integrated application software and discovering relationships between transcription factors." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=81427.

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In the first part of this thesis, we present a new development platform especially tailored to Bioinformatics research and software development called Bias (Bioinformatics Integrated Application Software) designed to provide the tools necessary for carrying out integrative Bioinformatics research. Bias follows an object-relational strategy for providing persistent objects, allows third-party tools to be easily incorporated within the system, and it supports standards and data-exchange protocols common to Bioinformatics. The second part of this thesis is on the design and implementation of modules and libraries within Bias related to transcription factors. We present a module in Bias that focuses on discovering competitive relationships between mouse and yeast transcription factors. By competitive relationships we mean the competitive binding of two transcription factors for a given binding site. We also present a method that divides a transcription factor's set of binding sites into two or more different sets when constructing PSSMs.
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Books on the topic "Bioinformatics application"

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Wang, Xiangdong, Christian Baumgartner, Denis C. Shields, Hong-Wen Deng, and Jacques S. Beckmann, eds. Application of Clinical Bioinformatics. Springer Netherlands, 2016. http://dx.doi.org/10.1007/978-94-017-7543-4.

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Wei, Dong-Qing, Yilong Ma, William C. S. Cho, Qin Xu, and Fengfeng Zhou, eds. Translational Bioinformatics and Its Application. Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-1045-7.

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Weston, Paul. Bioinformatics Software Engineering. John Wiley & Sons, Ltd., 2005.

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service), SpringerLink (Online, ed. Evolutionary Biology from Concept to Application. Springer-Verlag Berlin Heidelberg, 2008.

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Pontarotti, Pierre. Evolutionary Biology: Concept, Modeling, and Application. Springer-Verlag Berlin Heidelberg, 2009.

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IFIP Conference on e-Business, e-Services, and e-Society (9th 2009 Nancy, France). Software services for e-business and e-society: 9th IFIP WG 6.1 Conference on e-Business, e-Services and e-Society, I3E 2009, Nancy, France, September 23-25, 2009 : proceedings. Springer, 2009.

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service), SpringerLink (Online, ed. Bioinformatics: Applications in Life and Environmental Sciences. Springer Netherlands, 2009.

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1978-, Stajich Jason Eric, Hansen David, and SpringerLink (Online service), eds. Bioinformatics: Tools and Applications. Springer-Verlag New York, 2009.

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Cai, Zhipeng, Oliver Eulenstein, Daniel Janies, and Daniel Schwartz, eds. Bioinformatics Research and Applications. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38036-5.

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Măndoiu, Ion, Raj Sunderraman, and Alexander Zelikovsky, eds. Bioinformatics Research and Applications. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-79450-9.

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Book chapters on the topic "Bioinformatics application"

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Parthasarathy, S. "Bioinformatics: Application to Genomics." In Plant Biology and Biotechnology. Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2283-5_13.

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Schwikowski, Benno, and Martin Vingron. "A clustering approach to Generalized Tree Alignment with application to Alu repeats." In Bioinformatics. Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/bfb0033210.

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Zhu, Feng, and Kai Huang. "Gene Therapy and Genomic Application in Heart Disease." In Translational Bioinformatics. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1429-2_13.

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Lu, Aiping, Dan Li, Yan Liu, and Haiyun Wang. "Application of Bioinformatics to Asthma." In Genomic Approach to Asthma. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8764-6_16.

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Stevens, Robert, and Phillip Lord. "Application of Ontologies in Bioinformatics." In Handbook on Ontologies. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-92673-3_33.

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Arbitman, Guy, Shmuel T. Klein, Pierre Peterlongo, and Dana Shapira. "Approximate Hashing for Bioinformatics." In Implementation and Application of Automata. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79121-6_15.

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Upadhyay, Jyoti, Rohit Joshi, Balwant Singh, et al. "Application of Bioinformatics in Understanding of Plant Stress Tolerance." In Plant Bioinformatics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67156-7_14.

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Babar, Mustafeez Mujtaba, Najam-us-Sahar Sadaf Zaidi, Venkata Raveendra Pothineni, et al. "Application of Bioinformatics and System Biology in Medicinal Plant Studies." In Plant Bioinformatics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67156-7_15.

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Guo, Michael H., and Andrew Dauber. "Application of Genomics to the Study of Human Growth Disorders." In Translational Bioinformatics. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1104-7_18.

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Zhang, Chao, Shunfu Xu, and Dong Xu. "Bioinformatics Applications in Clinical Microbiology." In Translational Bioinformatics and Its Application. Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-1045-7_15.

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Conference papers on the topic "Bioinformatics application"

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Rocha, Lucas B., Said Sadique Adi, and Eloi Araujo. "Specific Substring Problem: an application in bioinformatics." In XI Simpósio Brasileiro de Bioinformática. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/bsb_estendido.2018.8801.

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Given two sets of sequences A and B, the Substring Specific problem is to find all minimum substrings in A having distance at least k for each subsequence in B. This work addresses three new implementations for the Maaß algorithm when the Hamming distance is considered: a naive cubic-time algorithm and two quadratic-time algorithms. We run tests to compare the running time of these implementations and another recently described algorithm implementation that uses the edit distance. In addition, we conducted preliminary testing on a large Tara Ocean database, looking for efficient and effective strategies for finding unique sequences in a set of sequences comparing with the other
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Wang, Xinyi, Cangshuai Wu, and Zhen Huang. "Trends of Intel MIC Application In Bioinformatics." In 2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS). IEEE, 2019. http://dx.doi.org/10.1109/icsess47205.2019.9040682.

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Wang, Xinyi, Zhen Huang, Cangshuai Wu, Feng Liu, and Congrui Wang. "Review of Bioinformatics Application Using Intel MIC." In 2019 IEEE 19th International Conference on Communication Technology (ICCT). IEEE, 2019. http://dx.doi.org/10.1109/icct46805.2019.8947018.

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Tang, DeQuan, and Yang Tan. "Graph-Based Bioinformatics Mining Research and Application." In 2011 Fourth International Symposium on Knowledge Acquisition and Modeling (KAM). IEEE, 2011. http://dx.doi.org/10.1109/kam.2011.83.

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Wang, Jinrui. "Application of Analytic Number Theory in Bioinformatics." In 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017). Atlantis Press, 2017. http://dx.doi.org/10.2991/fmsmt-17.2017.63.

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Yang, Haoyu, Zheng An, Haotian Zhou, and Yawen Hou. "Application of machine learning methods in bioinformatics." In 6TH INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN, MANUFACTURING, MODELING AND SIMULATION (CDMMS 2018). Author(s), 2018. http://dx.doi.org/10.1063/1.5039089.

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Mao, Weidong, and Shaun McEnhimer. "Survey: The Application of GMOD in Bioinformatics Research." In 2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE). IEEE, 2010. http://dx.doi.org/10.1109/icbbe.2010.5516243.

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Huang, James Kuodo. "On Systems Software Engineering with Application to Bioinformatics." In 2007 IEEE International Conference on Granular Computing (GRC 2007). IEEE, 2007. http://dx.doi.org/10.1109/grc.2007.84.

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Huang, James Kuodo. "On Systems Software Engineering with Application to Bioinformatics." In 2007 IEEE International Conference on Granular Computing (GRC 2007). IEEE, 2007. http://dx.doi.org/10.1109/grc.2007.4403175.

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Takeda, K. "The application of bioinformatics to network intrusion detection." In Proceedings 39th Annual 2005 International Carnahan Conference on Security Technology. IEEE, 2005. http://dx.doi.org/10.1109/ccst.2005.1594860.

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Reports on the topic "Bioinformatics application"

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Anderson, J., and T. Critchlow. Design of Wrapper Integration Within the DataFoundry Bioinformatics Application. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/15002882.

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Zurawski, Jason, Jennifer Schopf, Hans Addleman, and Doug Southworth. Arcadia University Bioinformatics Application Deep Dive. Final report. KINBERCON 2019, Philadelphia, PA, April 3, 2019. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1542424.

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Srivastava, Anuj. A Statistical Theory for Shape Analysis of Curves and Surfaces with Applications in Image Analysis, Biometrics, Bioinformatics and Medical Diagnostics. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada532601.

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