Relevant bibliographies by topics / Bioinformatics infrastructure

Contents

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

Academic literature on the topic 'Bioinformatics infrastructure'

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

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Journal articles on the topic "Bioinformatics infrastructure"

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ROBBINS, ROBERT J. "Bioinformatics: Essential Infrastructure for Global Biology1." Journal of Computational Biology 3, no. 3 (1996): 465–78. http://dx.doi.org/10.1089/cmb.1996.3.465.

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Perriere, Guy. "ReNaBi-IFB: The French Bioinformatics Infrastructure." EMBnet.journal 18, no. 1 (2012): 12. http://dx.doi.org/10.14806/ej.18.1.502.

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Whitfield, Eleanor J., Manuela Pruess, and Rolf Apweiler. "Bioinformatics database infrastructure for biotechnology research." Journal of Biotechnology 124, no. 4 (2006): 629–39. http://dx.doi.org/10.1016/j.jbiotec.2006.04.006.

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Blomberg, Niklas, Arlindo Oliveira, Barend Mons, Bengt Persson, and Inge Jonassen. "The ELIXIR channel in F1000Research." F1000Research 4 (December 18, 2015): 1471. http://dx.doi.org/10.12688/f1000research.7587.1.

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ELIXIR, the European life science infrastructure for biological information, is a unique initiative to consolidate Europe’s national centres, services, and core bioinformatics resources into a single, coordinated infrastructure. ELIXIR brings together Europe’s major life-science data archives and connects these with national bioinformatics infrastructures - the ELIXIR Nodes. This editorial introduces the ELIXIR channel in F1000Research; the aim of the channel is to collect and present ELIXIR’s scientific and operational output, engage with the broad life science community and encourage discussion on proposed infrastructure solutions. Submissions will be assessed by the ELIXIR channel Editorial Board to ensure they are relevant to ELIXIR community, and subjected to F1000Research open peer review process.
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Blomberg, Niklas, Arlindo Oliveira, Barend Mons, Bengt Persson, and Inge Jonassen. "The ELIXIR channel in F1000Research." F1000Research 4 (May 4, 2016): 1471. http://dx.doi.org/10.12688/f1000research.7587.2.

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ELIXIR, the European life science infrastructure for biological information, is a unique initiative to consolidate Europe’s national centres, services, and core bioinformatics resources into a single, coordinated infrastructure. ELIXIR brings together Europe’s major life-science data archives and connects these with national bioinformatics infrastructures - the ELIXIR Nodes. This editorial introduces the ELIXIR channel in F1000Research; the aim of the channel is to collect and present ELIXIR’s scientific and operational output, engage with the broad life science community and encourage discussion on proposed infrastructure solutions. Submissions will be assessed by the ELIXIR channel Advisory Board to ensure they are relevant to ELIXIR community, and subjected to F1000Research open peer review process.
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Roterman, Irena. "E-infrastructure technologies triggering of Bioinformatics development." Bioinformation 2, no. 4 (2007): 126–27. http://dx.doi.org/10.6026/97320630002126.

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Butte, Atul J. "Challenges in bioinformatics: infrastructure, models and analytics." Trends in Biotechnology 19, no. 5 (2001): 159–60. http://dx.doi.org/10.1016/s0167-7799(01)01603-1.

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Mulder, Nicola J., Ezekiel Adebiyi, Marion Adebiyi, et al. "Development of Bioinformatics Infrastructure for Genomics Research." Global Heart 12, no. 2 (2017): 91. http://dx.doi.org/10.1016/j.gheart.2017.01.005.

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Ison, Jon, Hervé Ménager, Bryan Brancotte, et al. "Community curation of bioinformatics software and data resources." Briefings in Bioinformatics 21, no. 5 (2019): 1697–705. http://dx.doi.org/10.1093/bib/bbz075.

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Abstract The corpus of bioinformatics resources is huge and expanding rapidly, presenting life scientists with a growing challenge in selecting tools that fit the desired purpose. To address this, the European Infrastructure for Biological Information is supporting a systematic approach towards a comprehensive registry of tools and databases for all domains of bioinformatics, provided under a single portal (https://bio.tools). We describe here the practical means by which scientific communities, including individual developers and projects, through major service providers and research infrastructures, can describe their own bioinformatics resources and share these via bio.tools.
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Kadri, Sabah. "Building Infrastructure and Workflows for Clinical Bioinformatics Pipelines." Advances in Molecular Pathology 3 (November 2020): 157–67. http://dx.doi.org/10.1016/j.yamp.2020.07.014.

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Dissertations / Theses on the topic "Bioinformatics infrastructure"

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de, Beste Eugene. "Enabling the processing of bioinformatics workflows where data is located through the use of cloud and container technologies." University of the Western Cape, 2019. http://hdl.handle.net/11394/6767.

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>Magister Scientiae - MSc<br>The growing size of raw data and the lack of internet communication technology to keep up with that growth is introducing unique challenges to academic researchers. This is especially true for those residing in rural areas or countries with sub-par telecommunication infrastructure. In this project I investigate the usefulness of cloud computing technology, data analysis workflow languages and portable computation for institutions that generate data. I introduce the concept of a software solution that could be used to simplify the way that researchers execute their analysis on data sets at remote sources, rather than having to move the data. The scope of this project involved conceptualising and designing a software system to simplify the use of a cloud environment as well as implementing a working prototype of said software for the OpenStack cloud computing platform. I conclude that it is possible to improve the performance of research pipelines by removing the need for researchers to have operating system or cloud computing knowledge and that utilising technologies such as this can ease the burden of moving data.
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Luu, Tien Dao. "Développement d'une infrastructure d'analyse multi-niveaux pour la découverte des relations entre génotype et phénotype dans les maladies génétiques humaines." Phd thesis, Université de Strasbourg, 2012. http://tel.archives-ouvertes.fr/tel-00866371.

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Répondant au besoin de mieux comprendre les relations qui lient un génotype aux phénotypes moléculaires et cliniques associés, nous avons développé une nouvelle infrastructure bioinformatique qui unit, dans un même système, la collecte, la gestion, la maintenance et le traitement de multiples données ou informations. La première contribution de cette thèse est SM2PH Central et sa capacité de générer des instances. SM2PH Central constitue notre centre de référence en ligne pour toutes les protéines humaines intégrant des niveaux d'informations qui vont des aspects génomiques, structuraux, fonctionnels ou évolutifs aux aspects de transcriptomique, interactomique, protéomique ou métabolomique. La deuxième contribution est MSV3d, une ressource d'annotation multi-niveau (propriétés physico-chimiques, fonction, évolution, structure) des mutations humaines connues. MSV3d fournit l'ensemble des connaissances exploitées par la troisième contribution de cette thèse à savoir KD4v, notre base d'extraction de connaissances pour prédire l'impact phénotypique d'une mutation. La base de connaissances de KD4v induite par la Programmation Logique Inductive contient des règles exploitables par un humain ou un ordinateur et des facteurs prédictifs caractérisant les mutations neutres ou délétères. Enfin, l'ultime contribution de cette thèse est liée au développement de GEPeTTO, un prototype de priorisation de gènes. Une application biologique a été réalisée. Nous avons étudié la cécité nocturne en utilisant SM2PH Central, en combinaison avec le service d'annotation de MSV3d et la méthode de prédiction KD4v pour analyser le gène GPR179 et ses deux mutations nouvellement identifiées.
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Books on the topic "Bioinformatics infrastructure"

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Hanʼguk Kwahak Kisul Chŏngbo Inpʻŭra Wŏkʻŭsyap (6th 2001 Hanʼguk Kwahak Kisul Chŏngbo Yŏnʼguwŏn). Che 6-hoe Hanʼguk Kwahak Kisul Chŏngbo Inpʻŭra Wŏkʻŭsyap haksul palpʻyo nonmunjip =: The 6th Workshop on Korean Infrastructure for Science and Technology Information. Hanʼguk Kwahak Kisul Chŏngbo Yŏnʼguwŏn, 2001.

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Kalbfleisch, Theodore S. Developing Bioinformatics Infrastructures. Academic Press, 2008.

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Tran, Quoc-Nam, and Hamid R. Arabnia. Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology: Systems and Applications. Elsevier Science & Technology Books, 2016.

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Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology. Elsevier, 2016. http://dx.doi.org/10.1016/c2015-0-01779-8.

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Book chapters on the topic "Bioinformatics infrastructure"

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Xu, Dong, Jie Liang, and Ying Xu. "Resources and Infrastructure for Structural Bioinformatics." In Computational Methods for Protein Structure Prediction and Modeling. Springer New York, 2007. http://dx.doi.org/10.1007/978-0-387-68825-1_7.

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Cumbo, Fabio, Marco S. Nobile, Chiara Damiani, Riccardo Colombo, Giancarlo Mauri, and Paolo Cazzaniga. "COSYS: A Computational Infrastructure for Systems Biology." In Computational Intelligence Methods for Bioinformatics and Biostatistics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67834-4_7.

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Sexton, David. "Computational Infrastructure and Basic Data Analysis for High-Throughput Sequencing." In Bioinformatics for High Throughput Sequencing. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0782-9_4.

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Kibbe, Warren A. "The Informatics and Bioinformatics Infrastructure of a Nutrigenomics Biobank." In Nutritional Genomics. John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0471781797.ch16.

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Baldridge, Kim K., Wibke Sudholt, Jerry P. Greenberg, et al. "Cluster and Grid Infrastructure for Computational Chemistry and Biochemistry." In Parallel Computing for Bioinformatics and Computational Biology. John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471756504.ch22.

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Bongo, Lars Ailo, Edvard Pedersen, and Martin Ernstsen. "Data-Intensive Computing Infrastructure Systems for Unmodified Biological Data Analysis Pipelines." In Computational Intelligence Methods for Bioinformatics and Biostatistics. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24462-4_22.

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Tomaszek, Sandra, and Dennis S. Tomaszek. "Cell Lines, Tissue Samples, Model Organisms, and Biobanks: Infrastructure and Tools for Cancer Systems Biology." In Cancer Systems Biology, Bioinformatics and Medicine. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1567-7_4.

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García-Macías, J. Antonio, Luis E. Palafox, and Ismael Villanueva. "A Wireless Infrastructure for Assisting the Elderly and the Mobility Impaired." In Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02481-8_125.

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Perkins, Randa M., and Joseph Markowitz. "Development and Optimization of Clinical Informatics Infrastructure to Support Bioinformatics at an Oncology Center." In Methods in Molecular Biology. Springer US, 2020. http://dx.doi.org/10.1007/978-1-0716-0849-4_1.

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Perkins, Randa M., and Joseph Markowitz. "Correction to: Development and Optimization of Clinical Informatics Infrastructure to Support Bioinformatics at an Oncology Center." In Methods in Molecular Biology. Springer US, 2020. http://dx.doi.org/10.1007/978-1-0716-0849-4_17.

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Conference papers on the topic "Bioinformatics infrastructure"

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Jordan, Chris, Dan Stanzione, Doreen Ware, Jerry Lu, and Christos Noutsos. "Comprehensive data infrastructure for plant bioinformatics." In 2010 IEEE International Conference On Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS). IEEE, 2010. http://dx.doi.org/10.1109/clusterwksp.2010.5613093.

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Cuccuru, Gianmauro, Simone Leo, Luca Lianas, et al. "An automated infrastructure to support high-throughput bioinformatics." In 2014 International Conference on High Performance Computing & Simulation (HPCS). IEEE, 2014. http://dx.doi.org/10.1109/hpcsim.2014.6903742.

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Tusch, Guenter, Paul Leidig, Greg Wolffe, David Elrod, and Carl Strebel. "Technology infrastructure supporting a medical & bioinformatics masters degree." In the 9th annual SIGCSE conference. ACM Press, 2004. http://dx.doi.org/10.1145/1007996.1008097.

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Zacharioudakis, Giorgos, Lefteris Koumakis, Stelios Sfakianakis, and Manolis Tsiknakis. "A Semantic Infrastructure for the Integration of Bioinformatics Services." In 2009 Ninth International Conference on Intelligent Systems Design and Applications. IEEE, 2009. http://dx.doi.org/10.1109/isda.2009.221.

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"TASK SCHEDULING IN A FEDERATED CLOUD INFRASTRUCTURE FOR BIOINFORMATICS APPLICATIONS." In 2nd International Conference on Cloud Computing and Services Science. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003932801140120.

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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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Nimmagadda, Shravya, Amrita Basu, Matthew Eavenson, et al. "GlycoVault: A Bioinformatics Infrastructure for Glycan Pathway Visualization, Analysis and Modeling." In 2008 Fifth International Conference on Information Technology: New Generations (ITNG). IEEE, 2008. http://dx.doi.org/10.1109/itng.2008.242.

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Tusch, Guenter, Paul Leidig, Gregory Wolffe, David Elrod, and Carl Strebel. "Technology infrastructure in support of a medical & bioinformatics masters degree." In the 14th annual ACM SIGCSE conference. ACM Press, 2009. http://dx.doi.org/10.1145/1562877.1563030.

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Medina-Martínez, Juan S., Juan E. Arango-Ossa, Gunes Gundem, et al. "Abstract 5105: A plug-and-play infrastructure for scalable bioinformatics operations." In Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.sabcs18-5105.

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Medina-Martínez, Juan S., Juan E. Arango-Ossa, Gunes Gundem, et al. "Abstract 5105: A plug-and-play infrastructure for scalable bioinformatics operations." In Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.am2019-5105.

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