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Littérature scientifique sur le sujet « Hot spot prediction »

Auteur : Grafiati

Publié le 4 juin 2021

Mis à jour le 1 février 2022

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Articles de revues sur le sujet "Hot spot prediction"

Zhang, Sijia, Le Zhao, Chun-Hou Zheng, and Junfeng Xia. "A feature-based approach to predict hot spots in protein–DNA binding interfaces." Briefings in Bioinformatics 21, no. 3 (April 8, 2019): 1038–46. http://dx.doi.org/10.1093/bib/bbz037.

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Abstract DNA-binding hot spot residues of proteins are dominant and fundamental interface residues that contribute most of the binding free energy of protein–DNA interfaces. As experimental methods for identifying hot spots are expensive and time consuming, computational approaches are urgently required in predicting hot spots on a large scale. In this work, we systematically assessed a wide variety of 114 features from a combination of the protein sequence, structure, network and solvent accessible information and their combinations along with various feature selection strategies for hot spot

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Kenneth Morrow, John, and Shuxing Zhang. "Computational Prediction of Protein Hot Spot Residues." Current Drug Metabolism 18, no. 9 (March 1, 2012): 1255–65. http://dx.doi.org/10.2174/138920012799362909.

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Kenneth Morrow, John, and Shuxing Zhang. "Computational Prediction of Protein Hot Spot Residues." Current Pharmaceutical Design 18, no. 9 (March 1, 2012): 1255–65. http://dx.doi.org/10.2174/138161212799436412.

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Nair B.J, Bipin, and Lijo Joy. "A hybrid approach for hot spot prediction and deep representation of hematological protein – drug interactions." International Journal of Engineering & Technology 7, no. 1.9 (March 1, 2018): 145. http://dx.doi.org/10.14419/ijet.v7i1.9.9752.

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In our research work we will collect the data of drugs as well as protein regarding hematic diseases, then applying feature extraction as well as classification, predict hot spot and non-hot spot then we are predicting the hot region using prediction algorithm. Parallelly from the hematological drug we are extracting the feature using molecular finger print then classifying using a classifier and applying deep learning concept to reduce the dimensionality then finally using machine learning algorithm predicting which drug will interact with the help of a hybrid approach.

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Tuncbag, N., O. Keskin, and A. Gursoy. "HotPoint: hot spot prediction server for protein interfaces." Nucleic Acids Research 38, Web Server (May 5, 2010): W402—W406. http://dx.doi.org/10.1093/nar/gkq323.

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Liu, Siyu, Chuyao Liu, and Lei Deng. "Machine Learning Approaches for Protein–Protein Interaction Hot Spot Prediction: Progress and Comparative Assessment." Molecules 23, no. 10 (October 4, 2018): 2535. http://dx.doi.org/10.3390/molecules23102535.

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Hot spots are the subset of interface residues that account for most of the binding free energy, and they play essential roles in the stability of protein binding. Effectively identifying which specific interface residues of protein–protein complexes form the hot spots is critical for understanding the principles of protein interactions, and it has broad application prospects in protein design and drug development. Experimental methods like alanine scanning mutagenesis are labor-intensive and time-consuming. At present, the experimentally measured hot spots are very limited. Hence, the use of

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Roll, Uri, Lewi Stone, and Shai Meiri. "Hot-Spot Facts and Artifacts-Questioning Israel's Great Biodiversity." Israel Journal of Ecology and Evolution 55, no. 3 (May 6, 2009): 263–79. http://dx.doi.org/10.1560/ijee.55.3.263.

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Israel's biological diversity has been praised as being particularly rich in relation to its size; however this assumption was never tested when taking into account the empirical form of the species-area relationship. Here we compared the species richness of different countries to see if the Israeli diversity is exceptionally rich when area is accurately accounted for. We compared richness of amphibians, birds, mammals, reptiles, flowering plants, conifers and cycads, and ferns in all the world's countries. We further tested the effects of mean latitude, altitude span, and insularity on specie

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Wang, Ao, and Yimin Xuan. "Multiscale prediction of localized hot-spot phenomena in solar cells." Renewable Energy 146 (February 2020): 1292–300. http://dx.doi.org/10.1016/j.renene.2019.07.073.

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Grosdidier, Solene, and Juan Fernandez-Recio. "Protein-protein Docking and Hot-spot Prediction for Drug Discovery." Current Pharmaceutical Design 18, no. 30 (August 23, 2012): 4607–18. http://dx.doi.org/10.2174/138161212802651599.

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Zhang, Ming, and Wei Chen. "Hot Spot Data Prediction Model Based on Wavelet Neural Network." Mathematical Problems in Engineering 2018 (October 30, 2018): 1–10. http://dx.doi.org/10.1155/2018/3719564.

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The novel hybrid multilevel storage system will be popular with SSD being integrated into traditional storage systems. To improve the performance of data migration between solid-state hard disk and hard disk according to the characteristics of each storage device, identifying the hot data block is significant issue. The hot data block prediction model based on wavelet neural network is built and trained by using historical data. This prediction model can overcome the cumulative effect of traditional statistical methods and has strong sensitivity to I/O loads with random variations. The experim

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Thèses sur le sujet "Hot spot prediction"

Karaca, Haldun. "Prediction Of Hot-spot And Top-oil Temperatures Of Power Transformers According To Ieee Standards C57.110-1998 And C57.91-1995." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12609140/index.pdf.

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In this thesis, the effects of Harmonics on the Top Oil and Hot Spot Temperatures of Power Transformers used in Turkish Electricity Transmission System have been investigated. Due to the solid state equipment, the harmonic levels increase. This effect raises the losses and temperatures in the transformer windings. None of the power transformers currently used in Turkey has measuring equipment suitable for measuring the Hot-Spot temperatures. In this study, a computer program is written in LABVIEW which measures the harmonics and calculates the temperatures in accordance with the methods recomm

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Pradhan, Manoj Kumar. "Conformal Thermal Models for Optimal Loading and Elapsed Life Estimation of Power Transformers." Thesis, Indian Institute of Science, 2004. http://hdl.handle.net/2005/97.

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Power and Generator Transformers are important and expensive elements of a power system. Inadvertent failure of Power Transformers would cause long interruption in power supply with consequent loss of reliability and revenue to the supply utilities. The mineral oil impregnated paper, OIP, is an insulation of choice in large power transformers in view of its excellent dielectric and other properties, besides being relatively inexpensive. During the normal working regime of the transformer, the insulation thereof is subjected to various stresses, the more important among them are, electrical,

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Kašpárek, Jan. "Predikce aktivních míst v proteinech." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220054.

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Knowledge of protein hot spots and the ability to successfully predict them while using only primary protein structure has been a worldwide scientific goal for several decades. This thesis describes the importance of hot spots and sums up advances achieved in this field of study so far. Besides that we introduce hot spot prediction algorithm using only a primary protein structure, based primarily on signal processing techniques. To convert protein sequence to numerical signal we use the EIIP attribute, while further processing is carried out via means of S-transform. The algorithm achieves sen

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Vestin, Albin, and Gustav Strandberg. "Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.

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Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, i

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Chung, Hsin-Line, and 鍾欣霖. "Building Integrated and Hybrid Prediction Systems for Computational Identification of Protein-Protein Interaction Hot Spot Residues by Using Motif Recognition, Sequential and Spatial Properties." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/833svr.

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碩士 國立中央大學 資訊工程學系 103 In a protein–protein interface, a small subset of residues contribute to the majority of the binding free energy, called the “hot spot”. Identifying and understanding hot spots and their mechanisms would have significant implications for bioinformatics and practical applications. Recently, many differences approaches have been used for predicted hot spot residues. We present an effective hot spot residues prediction system, HotSpotFinder, which contains motif recognition, sequential and spatial features and integrates feature set by two-step feature selection m

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João, Paulo Abel de Almeida. "Modelo preditivo da criminalidade – georeferenciação ao concelho de Lisboa." Master's thesis, 2010. http://hdl.handle.net/10362/3424.

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Dissertação apresentada como requisito parcial para a obtenção do grau de Mestre em Estatística e Gestão de Informação Pretende-se elaborar um modelo preditivo ou processo analítico e sistemático de descoberta do conhecimento, orientado segundo os princípios da pertinência e da oportunidade, que detecte os hot spots da criminalidade, que faça uma previsão e propensão de ocorrência e ainda, que faça uma previsão da sua evolução, estagnação ou redução, sendo realizado a partir do estabelecimento de correlações entre conjuntos de dados criminais ocorridos no primeiro semestre do ano de

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Livres sur le sujet "Hot spot prediction"

Railsback, Steven F., and Bret C. Harvey. Modeling Populations of Adaptive Individuals. Princeton University Press, 2020. http://dx.doi.org/10.23943/princeton/9780691195285.001.0001.

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Ecologists now recognize that the dynamics of populations, communities, and ecosystems are strongly affected by adaptive individual behaviors. Yet until now, we have lacked effective and flexible methods for modeling such dynamics. Traditional ecological models become impractical with the inclusion of behavior, and the optimization approaches of behavioral ecology cannot be used when future conditions are unpredictable due to feedbacks from the behavior of other individuals. This book provides a comprehensive introduction to state- and prediction-based theory, or SPT, a powerful new approach t

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Reichmann, Werner. The Interactional Foundations of Economic Forecasting. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198820802.003.0005.

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How do economic forecasters produce legitimate and credible predictions of the economic future, despite most of the economy being transmutable and indeterminate? Using data from a case study of economic forecasting institutes in Germany, this chapter argues that the production of credible economic futures depends on an epistemic process embedded in various forms of interaction. This interactional foundation—through ‘foretalk’ and ‘epistemic participation’ in networks of internal and external interlocutors—sharpens economic forecasts in three ways. First, it brings to light new imaginaries of t

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Llewellyn, Sue. What Do Dreams Do? Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198818953.001.0001.

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What is a dream? It’s a complex, non-obvious pattern derived from your experience. But you haven’t actually experienced it. Strange. Revealing complex, hidden patterns makes dreams odd. Dreams associate elements of different experiences to make something new: a pattern you didn’t know was there until you dreamt it. Patterns are discernible forms in the way something happens or is done. Some patterns are easy to spot, being certain and obvious: night follows day. Patterns in human/animal experiences are less obvious because, first, the patterned elements appear at different times or places and,

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McCrea, Michael A., and Lindsay D. Nelson. Effects of Multiple Concussions. Edited by Ruben Echemendia and Grant L. Iverson. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199896585.013.10.

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There is growing concern that suffering multiple sport-related concussions may increase an athlete’s risk of cumulative neurocognitive and neurobehavioral impairment. Many concerns have not been well-validated, however, owing to limited samples of repeatedly concussed players. In this article, we review the theoretical risks and current evidence regarding the extent to which repeat concussions impact players’ experience of and recovery following successive injuries. Concussion effects are considered at multiple levels (e.g., self-reported physical and psychiatric symptoms, neuropsychological p

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Chapitres de livres sur le sujet "Hot spot prediction"

Park, Jong Ho, Sung Chil Jung, Changlei Zhang, and Kil To Chong. "Neural Network Hot Spot Prediction Algorithm for Shared Web Caching System." In Web Technologies Research and Development - APWeb 2005, 795–806. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31849-1_76.

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Liu, Qian, and Jinyan Li. "Protein Binding Interfaces and Their Binding Hot Spot Prediction: A Survey." In Translational Bioinformatics, 79–106. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-7975-4_5.

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Corcoran, Jonathan, Ian D. Wilson, Owen M. Lewis, and J. Andrew Ware. "Data Clustering and Rule Abduction to Facilitate Crime Hot Spot Prediction." In Computational Intelligence. Theory and Applications, 807–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45493-4_80.

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Pulisheru, Kumara Swamy, and Anil Kumar Birru. "Prediction of Hot Spot and Hot Tear of the Al–Cu Cast Alloy by Casting Simulation Software." In Lecture Notes on Multidisciplinary Industrial Engineering, 459–67. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9072-3_40.

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Deshmukh, Shilpa S., and Basava Annappa. "Prediction of Crime Hot Spots Using Spatiotemporal Ordinary Kriging." In Integrated Intelligent Computing, Communication and Security, 683–91. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8797-4_70.

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Hart, Timothy C. "Hot Spots of Crime: Methods and Predictive Analytics." In Geographies of Behavioural Health, Crime, and Disorder, 87–103. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33467-3_5.

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Preto, António J., Pedro Matos-Filipe, José G. de Almeida, Joana Mourão, and Irina S. Moreira. "Predicting Hot Spots Using a Deep Neural Network Approach." In Methods in Molecular Biology, 267–88. New York, NY: Springer US, 2020. http://dx.doi.org/10.1007/978-1-0716-0826-5_13.

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Zhang, Wenjuan, Lin Wang, Zhiwei Sun, Bianqiang Zhang, Qiaoqiao Tang, and Qiang Gao. "Prediction of Hot Spots in Dimer Interface of Green Fluorescent Protein." In Lecture Notes in Electrical Engineering, 349–55. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4801-2_35.

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Gan, Haomin, Jing Hu, Xiaolong Zhang, Qianqian Huang, and Jiafu Zhao. "Accurate Prediction of Hot Spots with Greedy Gradient Boosting Decision Tree." In Intelligent Computing Theories and Application, 353–64. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95933-7_43.

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Sun, Zhen, Jun Zhang, Chun-Hou Zheng, Bing Wang, and Peng Chen. "Accurate Prediction of Protein Hot Spots Residues Based on Gentle AdaBoost Algorithm." In Intelligent Computing Theories and Application, 742–49. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42291-6_74.

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Actes de conférences sur le sujet "Hot spot prediction"

Bender, Christopher J., and Robert G. Dean. "Erosional Hot Spot Prediction through Wave Analysis." In Fourth International Symposium on Ocean Wave Measurement and Analysis. Reston, VA: American Society of Civil Engineers, 2002. http://dx.doi.org/10.1061/40604(273)132.

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Moreira, Irina, José Almeida, António Preto, Rita Melo, Zeynep Gümüş, Joaquim Costa, and Alexandre Bonvin. "Co-evolution importance on binding Hot-Spot prediction methods." In MOL2NET 2016, International Conference on Multidisciplinary Sciences, 2nd edition. Basel, Switzerland: MDPI, 2017. http://dx.doi.org/10.3390/mol2net-02-03889.

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Repantis, Thomas, and Vana Kalogeraki. "Hot-spot prediction and alleviation in distributed stream processing applications." In 2008 IEEE International Conference on Dependable Systems and Networks With FTCS and DCC (DSN). IEEE, 2008. http://dx.doi.org/10.1109/dsn.2008.4630103.

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Vidja, Akash, Harshad Nayakpara, Raghavendra Bhalera, and Kshitij Bhargava. "Methods for Calculating the Transformer Hot-Spot Temperature and Lifetime Prediction." In 2018 3rd International Conference for Convergence in Technology (I2CT). IEEE, 2018. http://dx.doi.org/10.1109/i2ct.2018.8529398.

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Saripalli, P., G. V. R. Kiran, R. R. Shankar, H. Narware, and N. Bindal. "Load Prediction and Hot Spot Detection Models for Autonomic Cloud Computing." In 2011 IEEE 4th International Conference on Utility and Cloud Computing (UCC 2011). IEEE, 2011. http://dx.doi.org/10.1109/ucc.2011.66.

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Yoo, Sung Goo, and Kil To Chong. "Hot Spot Prediction Algorithm for Shared Web Caching System Using NN." In 2007 International Symposium on Information Technology Convergence (ISITC 2007). IEEE, 2007. http://dx.doi.org/10.1109/isitc.2007.33.

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Ali, Hasnain, Raphael Delair, Duc-Thinh Pham, Sameer Alam, and Michael Schultz. "Dynamic Hot Spot Prediction by Learning Spatial- Temporal Utilization of Taxiway Intersections." In 2020 International Conference on Artificial Intelligence and Data Analytics for Air Transportation (AIDA-AT). IEEE, 2020. http://dx.doi.org/10.1109/aida-at48540.2020.9049186.

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Wang, Shoufeng, Fan Li, Hao Ni, Lexi Xu, Meifang Jing, Junyi Yu, and Xidong Wang. "Rush Hour Capacity Enhancement in 5G Network Based on Hot Spot Floating Prediction." In 2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS). IEEE, 2019. http://dx.doi.org/10.1109/iucc/dsci/smartcns.2019.00137.

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Tetzlaff, Dirk, and Sabine Glesner. "Static prediction of recursion frequency using machine learning to enable hot spot optimizations." In 2012 IEEE 10th Symposium on Embedded Systems for Real-time Multimedia (ESTIMedia). IEEE, 2012. http://dx.doi.org/10.1109/estimedia.2012.6507027.

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Janicki, Marcin, Zbigniew Kulesza, and Andrzej Napieralski. "Distributed network of remote sensors for real time prediction of hot spot temperature values." In 2010 Ninth IEEE Sensors Conference (SENSORS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icsens.2010.5690097.

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