Literatura académica sobre el tema "Analysis of biological data"
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Artículos de revistas sobre el tema "Analysis of biological data"
Dwivedi, Vivek Dhar, Indra Prasad Tripathi, Aman Chandra Kaushik, Shiv Bharadwaj y Sarad Kumar Mishra. "Biological Data Analysis Program (BDAP): a multitasking biological sequence analysis program". Neural Computing and Applications 30, n.º 5 (17 de diciembre de 2016): 1493–501. http://dx.doi.org/10.1007/s00521-016-2772-z.
Texto completoSrivastava, Chandan. "Biological Data Analysis: Error and Uncertainty". World Journal of Computer Application and Technology 1, n.º 3 (noviembre de 2013): 67–74. http://dx.doi.org/10.13189/wjcat.2013.010302.
Texto completoEliceiri, K. W., C. Rueden, W. A. Mohler, W. L. Hibbard y J. G. White. "Analysis of Multidimensional Biological Image Data". BioTechniques 33, n.º 6 (diciembre de 2002): 1268–73. http://dx.doi.org/10.2144/02336bt01.
Texto completoGrewal, Rumdeep Kaur y Sampa Das. "Microarray data analysis: Gaining biological insights". Journal of Biomedical Science and Engineering 06, n.º 10 (2013): 996–1005. http://dx.doi.org/10.4236/jbise.2013.610124.
Texto completoEl-Bayomi, Kh M., El A. Rady, M. S. El-Tarabany y Fatma D. Mohammed. "Statistical Analysis of Biological Survival Data". Zagazig Veterinary Journal 42, n.º 1 (1 de marzo de 2014): 129–39. http://dx.doi.org/10.21608/zvjz.2014.59478.
Texto completoFry, J. C. "Biological Data Analysis: A Practical Approach." Biometrics 50, n.º 1 (marzo de 1994): 318. http://dx.doi.org/10.2307/2533236.
Texto completoJohnson, Michael L. "Review of Fry, Biological Data Analysis". Biophysical Journal 67, n.º 2 (agosto de 1994): 937. http://dx.doi.org/10.1016/s0006-3495(94)80557-0.
Texto completoSung, Wing-Kin. "Pan-omics analysis of biological data". Methods 102 (junio de 2016): 1–2. http://dx.doi.org/10.1016/j.ymeth.2016.05.004.
Texto completoStansfield, William D. y Matthew A. Carlton. "Bayesian Statistics for Biological Data: Pedigree Analysis". American Biology Teacher 66, n.º 3 (1 de marzo de 2004): 177–82. http://dx.doi.org/10.2307/4451651.
Texto completoTopaz, Chad M., Lori Ziegelmeier y Tom Halverson. "Topological Data Analysis of Biological Aggregation Models". PLOS ONE 10, n.º 5 (13 de mayo de 2015): e0126383. http://dx.doi.org/10.1371/journal.pone.0126383.
Texto completoTesis sobre el tema "Analysis of biological data"
Droop, Alastair Philip. "Correlation Analysis of Multivariate Biological Data". Thesis, University of York, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.507622.
Texto completoMcCormick, Paul Stephen. "Statistical analysis of biological expression data". Thesis, University of Cambridge, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.613819.
Texto completoHasegawa, Takanori. "Reconstructing Biological Systems Incorporating Multi-Source Biological Data via Data Assimilation Techniques". 京都大学 (Kyoto University), 2015. http://hdl.handle.net/2433/195985.
Texto completoWaterworth, Alan Richard. "Data analysis techniques of measured biological impedance". Thesis, University of Sheffield, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340146.
Texto completoBecker, Katinka [Verfasser]. "Logical Analysis of Biological Data / Katinka Becker". Berlin : Freie Universität Berlin, 2021. http://d-nb.info/1241541779/34.
Texto completoREHMAN, HAFEEZ UR. "Integration and Analysis of Heterogeneous Biological Data". Doctoral thesis, Politecnico di Torino, 2014. http://hdl.handle.net/11583/2537092.
Texto completoLi, Yehua. "Topics in functional data analysis with biological applications". [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1867.
Texto completoChen, Li. "Integrative Modeling and Analysis of High-throughput Biological Data". Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/30192.
Texto completoPh. D.
Causey, Jason L. "Studying Low Complexity Structures in Bioinformatics Data Analysis of Biological and Biomedical Data". Thesis, University of Arkansas at Little Rock, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10750808.
Texto completoBiological, biomedical, and radiological data tend to be large, complex, and noisy. Gene expression studies contain expression levels for thousands of genes and hundreds or thousands of patients. Chest Computed Tomography images used for diagnosing lung cancer consist of hundreds of 2-D image ”slices”, each containing hundreds of thousands of pixels. Beneath the size and apparent complexity of many of these data are simple and sparse structures. These low complexity structures can be leveraged into new approaches to biological, biomedical, and radiological data analyses. Two examples are presented here. First, a new framework SparRec (Sparse Recovery) for imputation of GWAS data, based on a matrix completion (MC) model taking advantage of the low-rank and low number of co-clusters of GWAS matrices. SparRec is flexible enough to impute meta-analyses with multiple cohorts genotyped on different sets of SNPs, even without a reference panel. Compared with Mendel-Impute, another MC method, our low-rank based method achieves similar accuracy and efficiency even with up to 90% missing data; our co-clustering based method has advantages in running time. MC methods are shown to have advantages over statistics-based methods, including Beagle and fastPhase. Second, we demonstrate NoduleX, a method for predicting lung nodule malignancy from chest Computed Tomography (CT) data, based on deep convolutional neural networks. For training and validation, we analyze >1000 lung nodules in images from the LIDC/IDRI cohort and compare our results with classifications provided by four experienced thoracic radiologists who participated in the LIDC project. NoduleX achieves high accuracy for nodule malignancy classification, with an AUC of up to 0.99, commensurate with the radiologists’ analysis. Whether they are leveraged directly or extracted using mathematical optimization and machine learning techniques, low complexity structures provide researchers with powerful tools for taming complex data.
Zandegiacomo, Cella Alice. "Multiplex network analysis with application to biological high-throughput data". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/10495/.
Texto completoLibros sobre el tema "Analysis of biological data"
Maglaveras, Nicos, Ioanna Chouvarda, Vassilis Koutkias y Rüdiger Brause, eds. Biological and Medical Data Analysis. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11946465.
Texto completoOliveira, José Luís, Víctor Maojo, Fernando Martín-Sánchez y António Sousa Pereira, eds. Biological and Medical Data Analysis. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11573067.
Texto completoBarreiro, José María, Fernando Martín-Sánchez, Víctor Maojo y Ferran Sanz, eds. Biological and Medical Data Analysis. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/b104033.
Texto completoDolph, Schluter, ed. The analysis of biological data. Greenwood Village, Colo: Roberts and Co. Publishers, 2009.
Buscar texto completoC, Fry John, ed. Biological data analysis: A practical approach. Oxford: IRL Press at Oxford University Press, 1993.
Buscar texto completoGlasbey, C. A. Image analysis for the biological sciences. Chichester: J. Wiley, 1995.
Buscar texto completoAnalysis of infectious disease data. London: Chapman and Hall, 1989.
Buscar texto completoR, Margules C., Austin M. P y CSIRO (Australia), eds. Nature conservation: Cost effective biological surveys and data analysis. [Canberra]: CSIRO Australia, 1991.
Buscar texto completoOphir, Frieder y Martino Robert L, eds. High performance computational methods for biological sequence analysis. Boston: Kluwer Academic Publishers, 1996.
Buscar texto completoPodani, János. Introduction to the exploration of multivariate biological data. Leiden: Backhuys Publishers, 2000.
Buscar texto completoCapítulos de libros sobre el tema "Analysis of biological data"
Kim, Ju Han. "Biological Network Analysis". En Genome Data Analysis, 233–46. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-1942-6_13.
Texto completoRieger, Josef, Karel Kosar, Lenka Lhotska y Vladimir Krajca. "EEG Data and Data Analysis Visualization". En Biological and Medical Data Analysis, 39–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30547-7_5.
Texto completoKim, Ju Han. "Gene Ontology and Biological Pathway-Based Analysis". En Genome Data Analysis, 121–34. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-1942-6_7.
Texto completoBarah, Pankaj, Dhruba Kumar Bhattacharyya y Jugal Kumar Kalita. "Information Flow in Biological Systems". En Gene Expression Data Analysis, 27–38. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9780429322655-2.
Texto completoO'Hara, Timothy D., Thomas A. Schlacher, Ashley A. Rowden y Derek P. Tittensor. "Data Analysis Considerations". En Biological Sampling in the Deep Sea, 386–403. Chichester, UK: John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781118332535.ch17.
Texto completoIno, Fumihiko, Katsunori Matsuo, Yasuharu Mizutani y Kenichi Hagihara. "Minimizing Data Size for Efficient Data Reuse in Grid-Enabled Medical Applications". En Biological and Medical Data Analysis, 195–206. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11946465_18.
Texto completoPotamias, George. "Knowledgeable Clustering of Microarray Data". En Biological and Medical Data Analysis, 491–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30547-7_49.
Texto completoPolaillon, Géraldine, Laure Vescovo, Magali Michaut y Jean-Christophe Aude. "Mining Biological Data Using Pyramids". En Selected Contributions in Data Analysis and Classification, 397–408. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73560-1_37.
Texto completoHernández, Juan A., Martha L. Mora, Emanuele Schiavi y Pablo Toharia. "RF Inhomogeneity Correction Algorithm in Magnetic Resonance Imaging". En Biological and Medical Data Analysis, 1–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30547-7_1.
Texto completoDiez, Raquel Montes, Juan M. Marin y David Rios Insua. "Bayesian Prediction of Down Syndrome Based on Maternal Age and Four Serum Markers". En Biological and Medical Data Analysis, 85–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30547-7_10.
Texto completoActas de conferencias sobre el tema "Analysis of biological data"
Soetaert, Karline, Dick van Oevelen, Theodore E. Simos, George Psihoyios, Ch Tsitouras y Zacharias Anastassi. "Modelling Marine Biological and Biogeochemical Data". En NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2011: International Conference on Numerical Analysis and Applied Mathematics. AIP, 2011. http://dx.doi.org/10.1063/1.3636664.
Texto completoOgiela, Lidia. "Biological Modelling in Semantic Data Analysis Systems". En 2012 Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS). IEEE, 2012. http://dx.doi.org/10.1109/imis.2012.81.
Texto completoKim, Christine, Peggy Yin, Carlos X. Soto, Ian K. Blaby y Shinjae Yoo. "Multimodal biological analysis using NLP and expression profile". En 2018 New York Scientific Data Summit (NYSDS). IEEE, 2018. http://dx.doi.org/10.1109/nysds.2018.8538944.
Texto completoLivengood, Philip, Ross Maciejewski, Wei Chen y David S. Ebert. "A visual analysis system for metabolomics data". En 2011 IEEE Symposium on Biological Data Visualization (BioVis). IEEE, 2011. http://dx.doi.org/10.1109/biovis.2011.6094050.
Texto completoThai, My T., Ping Deng, Weili Wu, Taieb Znati, Onur Seref, O. Erhun Kundakcioglu y Panos Pardalos. "Approximation algorithms of non-unique probes selection for biological target identification". En DATA MINING, SYSTEMS ANALYSIS AND OPTIMIZATION IN BIOMEDICINE. AIP, 2007. http://dx.doi.org/10.1063/1.2817340.
Texto completoJager, Gunter, Florian Battke y Kay Nieselt. "TIALA — Time series alignment analysis". En 2011 IEEE Symposium on Biological Data Visualization (BioVis). IEEE, 2011. http://dx.doi.org/10.1109/biovis.2011.6094048.
Texto completoPedersen, Edvard, Inge Alexander Raknes, Martin Ernstsen y Lars Ailo Bongo. "Integrating Data-Intensive Computing Systems with Biological Data Analysis Frameworks". En 2015 23rd Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP). IEEE, 2015. http://dx.doi.org/10.1109/pdp.2015.106.
Texto completoNowke, Christian, Maximilian Schmidt, Sacha J. van Albada, Jochen M. Eppler, Rembrandt Bakker, Markus Diesrnann, Bernd Hentschel y Torsten Kuhlen. "VisNEST — Interactive analysis of neural activity data". En 2013 IEEE Symposium on Biological Data Visualization (BioVis). IEEE, 2013. http://dx.doi.org/10.1109/biovis.2013.6664348.
Texto completoCui, Guangzhao, Xianghong Cao y Xuncai Zhang. "Analysis of Biological Data with Digital Signal Processing". En 2005 IEEE 7th Workshop on Multimedia Signal Processing. IEEE, 2005. http://dx.doi.org/10.1109/mmsp.2005.248561.
Texto completoMajid Rastegar-Mojarad, Saeed Talatian-Azad y Behrouz Minaei-Bidgoli. "A survey on biological data analysis by biclustering". En 2010 International Conference on Educational and Information Technology (ICEIT). IEEE, 2010. http://dx.doi.org/10.1109/iceit.2010.5607792.
Texto completoInformes sobre el tema "Analysis of biological data"
Langston, Michael A. Scalable Computational Methods for the Analysis of High-Throughput Biological Data. Office of Scientific and Technical Information (OSTI), septiembre de 2012. http://dx.doi.org/10.2172/1050046.
Texto completoRatnarajah, Lavenia. Map of BioEco Observing networks/capability. EuroSea, octubre de 2021. http://dx.doi.org/10.3289/eurosea_d1.2.
Texto completoReilly-Collette, Marina, Brandon Booker, Kathryn Trubac, Tyler Elliott, Andrew Reichert, Charles Woodruff y Lien Senchak. Testing of dry decontamination technologies for chemical, biological, radiological, and nuclear (CBRN) response. Engineer Research and Development Center (U.S.), mayo de 2023. http://dx.doi.org/10.21079/11681/47032.
Texto completoRodriguez Muxica, Natalia. Open configuration options Bioinformatics for Researchers in Life Sciences: Tools and Learning Resources. Inter-American Development Bank, febrero de 2022. http://dx.doi.org/10.18235/0003982.
Texto completoMatthew, Gray. Data from "Winter is Coming – Temperature Affects Immune Defenses and Susceptibility to Batrachochytrium salamandrivorans". University of Tennessee, Knoxville Libraries, enero de 2021. http://dx.doi.org/10.7290/t7sallfxxe.
Texto completoCao, Siyang, Yihao Wei, Tiantian Qi, Peng Liu, Yingqi Chen, Fei Yu, Hui Zeng y Jian Weng. Stem cell therapy for peripheral nerve injury: An up-to-date meta-analysis of 55 preclinical researches. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, octubre de 2022. http://dx.doi.org/10.37766/inplasy2022.10.0083.
Texto completoNachtrieb, Julie. Field site analysis of giant salvinia nitrogen content and salvinia weevil density. Engineer Research and Development Center (U.S.), septiembre de 2021. http://dx.doi.org/10.21079/11681/42060.
Texto completoTorney, D. C., W. Bruno y V. Detours. Nonlinear analysis of biological sequences. Office of Scientific and Technical Information (OSTI), noviembre de 1998. http://dx.doi.org/10.2172/674921.
Texto completoMcMinn, James W. Biological Diversity Research: An Analysis. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station, 1991. http://dx.doi.org/10.2737/se-gtr-071.
Texto completoMcMinn, James W. Biological Diversity Research: An Analysis. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station, 1991. http://dx.doi.org/10.2737/se-gtr-71.
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