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Relevant bibliographies by topics / Bioinformatics – Research

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Academic literature on the topic 'Bioinformatics – Research'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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Journal articles on the topic "Bioinformatics – Research"

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Lee, Eunjung, and Doheon Lee. "Systems Bioinformatics Research Trends." Journal of Korean Society of Medical Informatics 14, no. 4 (2008): 313. http://dx.doi.org/10.4258/jksmi.2008.14.4.313.

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Vandamme, Anne-Mieke. "Bioinformatics in virus research." Infection, Genetics and Evolution 7, no. 3 (2007): 353. http://dx.doi.org/10.1016/j.meegid.2007.04.001.

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Chen, Yi-Ping Phoebe, and Geoff McLachlan. "Bioinformatics Research in Australia." Asia-Pacific Biotech News 07, no. 03 (2003): 82–84. http://dx.doi.org/10.1142/s0219030303000211.

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Bioinformatics is the intersection of computer science, statistics, molecular biology and genetics. It is one of the most important emerging research areas of the 21st century and has already attracted worldwide interest. It is clear that major initiatives are being undertaken which will establish Australia both as a vital link in the international bioinformatics community for research and development and also as an Asia-Pacific service for bioinformatics. This article briefly notes some groups carrying out bioinformatics research in Australia.

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Lesko, L. J. "Drug Research and Translational Bioinformatics." Clinical Pharmacology & Therapeutics 91, no. 6 (2012): 960–62. http://dx.doi.org/10.1038/clpt.2012.45.

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Perez-Iratxeta, C., M. A. Andrade-Navarro, and J. D. Wren. "Evolving research trends in bioinformatics." Briefings in Bioinformatics 8, no. 2 (2006): 88–95. http://dx.doi.org/10.1093/bib/bbl035.

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Boulesteix, A. L. "Over-optimism in bioinformatics research." Bioinformatics 26, no. 3 (2009): 437–39. http://dx.doi.org/10.1093/bioinformatics/btp648.

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Ellis, Heidi J. C. "Undergraduate involvement in bioinformatics research." ACM SIGCSE Bulletin 38, no. 3 (2006): 322. http://dx.doi.org/10.1145/1140123.1140228.

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Iwakiri, Junichi, Michiaki Hamada, and Kiyoshi Asai. "Bioinformatics tools for lncRNA research." Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms 1859, no. 1 (2016): 23–30. http://dx.doi.org/10.1016/j.bbagrm.2015.07.014.

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Meier, René, Christoph Ruttkies, Hendrik Treutler, and Steffen Neumann. "Bioinformatics can boost metabolomics research." Journal of Biotechnology 261 (November 2017): 137–41. http://dx.doi.org/10.1016/j.jbiotec.2017.05.018.

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Lang, E. "Section 7: Bioinformatics: Bioinformatics and its Impact on Clinical Research Methods." Yearbook of Medical Informatics 15, no. 01 (2006): 104–6. http://dx.doi.org/10.1055/s-0038-1638478.

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SummaryTo summarize current excellent research in the field of bioinformatics.Synopsis of the articles selected for the IMIA Yearbook 2006. Results: Current research in the field of bioinformatics clearly shows ongoing unification of experimental findings and clinical outcomes. Microarray data, gene sequences and clinical data are more and more perceived as different but related facets of one entity. Significant work is done in the area of text and data mining in order to bring together patient data and biochemical phenomena by means of ontologies. A strong trend in the clinical field is performance of exhaustive studies on DNA material derived from patients that suffer from diseases that are already known to be inherited. Examination of appropriate methods covers data and text mining, ontologies as well as machine learning and classification.The best paper selection of articles on bioinformatics shows examples of excellent research on methods used for studying inherited diseases and their underlying genetic dispositions. Clinical studies, inclusion of experimental findings like microarray data, and of knowledge representation formats all lead to a better understanding the linkage between gene sequences, biological functions and clinical findings in the form of healthy state or physiological disorders.

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Dissertations / Theses on the topic "Bioinformatics – Research"

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Freyhult, Eva. "New techniques for analysing RNA structure /." Uppsala, 2004. http://www.math.uu.se/research/pub/Freyhult1.pdf.

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Lesser, Alice. "Hereditarily optimal realizations /." Uppsala, 2004. http://www.math.uu.se/research/pub/Lesser1.pdf.

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Guo, Ling. "Bioinformatics in maize genome research." [Ames, Iowa : Iowa State University], 2007.

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Kusnierczyk, Waclaw. "Augmenting Bioinformatics Research with Biomedical Ontologies." Doctoral thesis, Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-2001.

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<p>The main objective of the reported study was to investigate how biomedical ontologies, logically structured representations of various aspects of the biomedical reality, can help researchers in analyzing experimental data. The dissertation reports two attempts to construct tools for the analysis of high-throughput experimental results using explicit domain knowledge representations. Furthermore, integrative efforts made by the community of Open Biomedical Ontologies (OBO), in which the author has participated, are reported, and a framework for consistently connecting the Gene Ontology (GO) with the Taxonomy of Species is proposed and discussed.</p>

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Elekwachi, Chijioke Obioma. "Bioinformatics resources to support bioremediation research." Thesis, University of Nottingham, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.595818.

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Contamination of ecosystems by xenobiotic substances has led to significant negative impacts on the ecologies and on the health and economic livelihood of the human populations in affected environments. Bioremediation, particularly microbial bioremediation, has proven to be a safe, low-cost and environmentally friendly method for remediation of such areas. However, a lack of complete understanding of the metabolic, enzymatic and cellular processes involved has made it difficult to model and predict outcomes of field processes. The ability of researchers to make critical decisions capable of influencing the direction and outcomes of these processes is also hampered. This study outlines the results of a survey and describes the electronic Microbial BioRemediation (eMBR) web portal, designed to improve collaboration in the bioremediation research community. It describes the structure, algorithms and output of three bioinformatics resources developed and deployed via the portal. eMBRLitMine addresses the problem of identifying which microorganisms would be suitable for remediating sites contaminated by named compounds. It combines named-entity recognition algorithms, a mySQL database, graph rendering technologies and Perl scripts to create, from the vast information available within published literature, a statistical co-occurrence matrix which it uses to infer possible associations between microorganisms and particular contaminants. This provides valuable insights into possible bacteria/contaminant relationships and highlights bacterial species that could be used in remediation of specified contaminants. eMBRCatalogue is a moderated and searchable database cataloguing bioremediation case studies. Implemented as an eXtensible Markup Language (XML) database employing a user-generated-content framework, it provides background knowledge necessary for planning and execution of bioremediation activities. Developed following the construction of a comprehensive metabolic biodegradation network, eMBRHelper enables the delineation of possible biodegradation pathways for named contaminants. By integrating relevant chemical, enzymatic and genomics information, it attempts to model the interplay between contaminants, enzymes, microorganisms and degradation pathway, enabling researchers to make informed decisions for improved outcomes, particularly for remediation exercises involving bioaugmentation. The study also analysed usage of the portal and resources, made recommendations for future developments and highlights avenues for further informatics support for the bioremediation research sector.

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Niklasson, Markus. "Coding to cure : NMR and thermodynamic software applied to congenital heart disease research." Doctoral thesis, Linköpings universitet, Kemi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-142785.

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Regardless of scientific field computers have become pivotal tools for data analysis and the field of structural biology is not an exception. Here, computers are the main tools used for tasks including structural calculations of proteins, spectral analysis of nuclear magnetic resonance (NMR) spectroscopy data and fitting mathematical models to data. As results reported in papers heavily rely on software and scripts it is of key importance that the employed computational methods are robust and yield reliable results. However, as many scientific fields are niched and possess a small potential user base the task to develop necessary software often falls on researchers themselves. This can cause divergence when comparing data analyzed by different measures or by using subpar methods. Therein lies the importance of development of accurate computational methods that can be employed by the scientific community. The main theme of this thesis is software development applied to structural biology, with the purpose to aid research in this scientific field by speeding up the process of data analysis as well as to ensure that acquired data is properly analyzed. Among the original results of this thesis are three user-friendly software: COMPASS - a resonance assignment software for NMR spectroscopy data capable of analyzing chemical shifts and providing the user with suggestions to potential resonance assignments, based on a meticulous database comparison. CDpal - a curve fitting software used to fit thermal and chemical denaturation data of proteins acquired by circular dichroism (CD) spectroscopy or fluorescence spectroscopy. PINT - a line shape fitting and downstream analysis software forNMRspectroscopy data, designed with the important purpose to easily and accurately fit peaks in NMR spectra and extract parameters such as relaxation rates, intensities and volumes of peaks. This thesis also describes a study performed on variants of the life essential regulatory protein calmodulin that have been associated with the congenital life threatening heart disease long QT syndrome (LQTS). The study provided novel insights revealing that all variants are distinct from the wild type in regards to structure and dynamics on a detailed level; the presented results are useful for the interpretation of results from protein interaction studies. The underlying research of this paper makes use of all three developed software, which validates that all developed methods fulfil a scientific purpose and are capable of producing solid results.

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Shankar, Vijay. "Extension of Multivariate Analyses to the Field of Microbial Ecology." Wright State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=wright1464358122.

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Nabiyouni, Maryam. "Mega-scale Bioinformatics Investigation of Codon Bias in Vertebrates." University of Toledo Health Science Campus / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=mco1308092740.

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Carr, Nicole. "Data Pooling to Identify Differentially Expressed Genes in Lung Cancer of Nonsmokers." University of Toledo Health Science Campus / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=mco1461881266.

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Regan-Fendt, Kelly E. "Integrative Network and Transcriptomics Approach Enables Computational Drug Repurposing and Drug Combination Discovery in Melanoma." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1521209048981327.

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Books on the topic "Bioinformatics – Research"

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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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Cai, Zhipeng, Ion Mandoiu, Giri Narasimhan, Pavel Skums, and Xuan Guo, eds. Bioinformatics Research and Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57821-3.

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Basu, Mitra, Yi Pan, and Jianxin Wang, eds. Bioinformatics Research and Applications. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08171-7.

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Măndoiu, Ion, and Alexander Zelikovsky, eds. Bioinformatics Research and Applications. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72031-7.

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Borodovsky, Mark, Johann Peter Gogarten, Teresa M. Przytycka, and Sanguthevar Rajasekaran, eds. Bioinformatics Research and Applications. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13078-6.

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Bourgeois, Anu, Pavel Skums, Xiang Wan, and Alex Zelikovsky, eds. Bioinformatics Research and Applications. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-38782-6.

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Bleris, Leonidas, Ion Măndoiu, Russell Schwartz, and Jianxin Wang, eds. Bioinformatics Research and Applications. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30191-9.

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Măndoiu, Ion, Giri Narasimhan, and Yanqing Zhang, eds. Bioinformatics Research and Applications. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01551-9.

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Cai, Zhipeng, Pavel Skums, and Min Li, eds. Bioinformatics Research and Applications. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20242-2.

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Book chapters on the topic "Bioinformatics – Research"

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Meetz, Kirsten, Hans-Peter Meinzer, Sândor Suhai, and Martina Kieninger. "Bioinformatics." In Current Cancer Research 1992. Steinkopff, 1992. http://dx.doi.org/10.1007/978-3-662-11384-4_10.

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Reczko, Martin, Sándor Suhai, Annemarie Poustka, Uwe Engelmann, Manuela Schäfer, and Hans-Peter Meinzer. "Bioinformatics." In Current Cancer Research 1995. Steinkopff, 1995. http://dx.doi.org/10.1007/978-3-642-48687-6_11.

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Gupta, S. "Bioinformatics—Research Applications." In Bioinformatics: Applications in Life and Environmental Sciences. Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-1-4020-8880-3_12.

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Villar, Elena Lopez, and William Chi-Shing Cho. "Proteomics and Cancer Research." In Translational Bioinformatics. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5811-7_4.

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Marsolo, Keith. "Research Patient Data Warehousing." In Translational Bioinformatics. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5149-1_6.

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Barnes, Michael G., John A. Lynch, Jeremy J. Corsmo, David P. Witte, and Paul E. Steele. "Biobanking in Pediatric Research." In Translational Bioinformatics. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5149-1_7.

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Gupta, Manoj Kumar, and Lambodar Behera. "Introduction to Bioinformatics." In Bioinformatics in Rice Research. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3993-7_1.

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Gupta, Manoj Kumar, Gayatri Gouda, Ravindra Donde, et al. "Statistics for Bioinformatics." In Bioinformatics in Rice Research. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3993-7_2.

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Subramaniyam, Devipriya, and Goutham Edula. "Imaging Techniques in Proteomics Research." In Translational Bioinformatics. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9202-8_13.

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Zhang, Minlu, Jingyuan Deng, Lirong Tan, Ye Chen, and Long Jason Lu. "Network Analysis in Translational Research." In Translational Bioinformatics. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5149-1_15.

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Conference papers on the topic "Bioinformatics – Research"

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Lim, Hwa A., and Charles R. Cantor. "Bioinformatics and Genome Research." In Proceedings of the Third International Conference. WORLD SCIENTIFIC, 1995. http://dx.doi.org/10.1142/9789814532266.

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Mercer, Simon. "BIOINFORMATICS AT MICROSOFT RESEARCH." In Proceedings of the Conference CSB 2006. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2006. http://dx.doi.org/10.1142/9781860947575_0006.

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Wu, Hao, Meijiao Wang, Jiaming Feng, and Yijian Pei. "Research Topic Evolution in "Bioinformatics"." In 2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE). IEEE, 2010. http://dx.doi.org/10.1109/icbbe.2010.5516318.

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Ellis, Heidi J. C. "Undergraduate involvement in bioinformatics research." In the 11th annual SIGCSE conference. ACM Press, 2006. http://dx.doi.org/10.1145/1140124.1140228.

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Ganote, Carrie L., Sheri A. Sanders, Bhavya Nalagampalli Papudeshi, Phillip D. Blood, and Thomas G. Doak. "A Voice for Bioinformatics." In PEARC17: Practice and Experience in Advanced Research Computing 2017. ACM, 2017. http://dx.doi.org/10.1145/3093338.3093374.

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MISHRA, SANTOSH K. "TRENDS IN BIOINFORMATICS RESEARCH AND SINGAPORE’S ROLE." In 3rd Asia-Pacific Bioinformatics Conference. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2005. http://dx.doi.org/10.1142/9781860947322_0039.

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C. Ellis, Heidi, Brian Sinnot, Susan Fox-Erlich, and Michael Gryk. "Undergraduate Research in Bioinformatics - The CONNJUR project." In Proceedings. Frontiers in Education. 36th Annual Conference. IEEE, 2006. http://dx.doi.org/10.1109/fie.2006.322491.

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Riehl, William J., Richard S. Canon, Boris Sadkhin, and Jay R. Bolton. "KBase: A Platform for Reproducible Bioinformatics Research." In 2019 IEEE/ACM International Workshop on Containers and New Orchestration Paradigms for Isolated Environments in HPC (CANOPIE-HPC). IEEE, 2019. http://dx.doi.org/10.1109/canopie-hpc49598.2019.00009.

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Dessi, Nicoletta, Giuliano Ferrentino, Emanuele Pascariello, and Barbara Pes. "Towards Ontology-Enabled BioContexts for Bioinformatics Research." In 2015 IEEE 24th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE). IEEE, 2015. http://dx.doi.org/10.1109/wetice.2015.17.

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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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Reports on the topic "Bioinformatics – Research"

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Chain, Patrick Sam Guy. LANL activities in: genomics, bioinformatics, microbiome research, data visualization and biosurveillance. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1493008.

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Slezak, T., and M. Wolinsky. FY02 CBNP Annual Report Input: Bioinformatics Support for CBNP Research and Deployments. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/15002105.

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