Gotowa bibliografia na temat „Hot spot prediction”
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Artykuły w czasopismach na temat "Hot spot prediction"
Zhang, Sijia, Le Zhao, Chun-Hou Zheng i Junfeng Xia. "A feature-based approach to predict hot spots in protein–DNA binding interfaces". Briefings in Bioinformatics 21, nr 3 (8.04.2019): 1038–46. http://dx.doi.org/10.1093/bib/bbz037.
Pełny tekst źródłaKenneth Morrow, John, i Shuxing Zhang. "Computational Prediction of Protein Hot Spot Residues". Current Drug Metabolism 18, nr 9 (1.03.2012): 1255–65. http://dx.doi.org/10.2174/138920012799362909.
Pełny tekst źródłaKenneth Morrow, John, i Shuxing Zhang. "Computational Prediction of Protein Hot Spot Residues". Current Pharmaceutical Design 18, nr 9 (1.03.2012): 1255–65. http://dx.doi.org/10.2174/138161212799436412.
Pełny tekst źródłaNair B.J, Bipin, i Lijo Joy. "A hybrid approach for hot spot prediction and deep representation of hematological protein – drug interactions". International Journal of Engineering & Technology 7, nr 1.9 (1.03.2018): 145. http://dx.doi.org/10.14419/ijet.v7i1.9.9752.
Pełny tekst źródłaTuncbag, N., O. Keskin i A. Gursoy. "HotPoint: hot spot prediction server for protein interfaces". Nucleic Acids Research 38, Web Server (5.05.2010): W402—W406. http://dx.doi.org/10.1093/nar/gkq323.
Pełny tekst źródłaLiu, Siyu, Chuyao Liu i Lei Deng. "Machine Learning Approaches for Protein–Protein Interaction Hot Spot Prediction: Progress and Comparative Assessment". Molecules 23, nr 10 (4.10.2018): 2535. http://dx.doi.org/10.3390/molecules23102535.
Pełny tekst źródłaRoll, Uri, Lewi Stone i Shai Meiri. "Hot-Spot Facts and Artifacts-Questioning Israel's Great Biodiversity". Israel Journal of Ecology and Evolution 55, nr 3 (6.05.2009): 263–79. http://dx.doi.org/10.1560/ijee.55.3.263.
Pełny tekst źródłaWang, Ao, i Yimin Xuan. "Multiscale prediction of localized hot-spot phenomena in solar cells". Renewable Energy 146 (luty 2020): 1292–300. http://dx.doi.org/10.1016/j.renene.2019.07.073.
Pełny tekst źródłaGrosdidier, Solene, i Juan Fernandez-Recio. "Protein-protein Docking and Hot-spot Prediction for Drug Discovery". Current Pharmaceutical Design 18, nr 30 (23.08.2012): 4607–18. http://dx.doi.org/10.2174/138161212802651599.
Pełny tekst źródłaZhang, Ming, i Wei Chen. "Hot Spot Data Prediction Model Based on Wavelet Neural Network". Mathematical Problems in Engineering 2018 (30.10.2018): 1–10. http://dx.doi.org/10.1155/2018/3719564.
Pełny tekst źródłaRozprawy doktorskie na temat "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.
Pełny tekst źródłaPradhan, 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.
Pełny tekst źródłaKašpárek, 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.
Pełny tekst źródłaVestin, Albin, i 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.
Pełny tekst źródłaChung, Hsin-Line, i 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.
Pełny tekst źródła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 method. Through the two predictor of the system, called HotSpotFinder-Integrated and HotSpotFinder-Hybrid, to predict PPI hot spot residues. A total 38 optimal integrated feature and a novel system designed concept are provided and compared with other computational hot spot prediction models, HotSpotFinder offers significant performance improvement in terms of precision, MCC, F1 score and sensitivity, even in the independent dataset.
João, Paulo Abel de Almeida. "Modelo preditivo da criminalidade – georeferenciação ao concelho de Lisboa". Master's thesis, 2010. http://hdl.handle.net/10362/3424.
Pełny tekst źródłaPretende-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 2007 no concelho de Lisboa. Este modelo poderá posteriormente ser aplicado a outras regiões do país.
Książki na temat "Hot spot prediction"
Railsback, Steven F., i Bret C. Harvey. Modeling Populations of Adaptive Individuals. Princeton University Press, 2020. http://dx.doi.org/10.23943/princeton/9780691195285.001.0001.
Pełny tekst źródłaReichmann, Werner. The Interactional Foundations of Economic Forecasting. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198820802.003.0005.
Pełny tekst źródłaLlewellyn, Sue. What Do Dreams Do? Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198818953.001.0001.
Pełny tekst źródłaMcCrea, Michael A., i Lindsay D. Nelson. Effects of Multiple Concussions. Redaktorzy Ruben Echemendia i Grant L. Iverson. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199896585.013.10.
Pełny tekst źródłaCzęści książek na temat "Hot spot prediction"
Park, Jong Ho, Sung Chil Jung, Changlei Zhang i Kil To Chong. "Neural Network Hot Spot Prediction Algorithm for Shared Web Caching System". W 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.
Pełny tekst źródłaLiu, Qian, i Jinyan Li. "Protein Binding Interfaces and Their Binding Hot Spot Prediction: A Survey". W Translational Bioinformatics, 79–106. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-7975-4_5.
Pełny tekst źródłaCorcoran, Jonathan, Ian D. Wilson, Owen M. Lewis i J. Andrew Ware. "Data Clustering and Rule Abduction to Facilitate Crime Hot Spot Prediction". W Computational Intelligence. Theory and Applications, 807–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45493-4_80.
Pełny tekst źródłaPulisheru, Kumara Swamy, i Anil Kumar Birru. "Prediction of Hot Spot and Hot Tear of the Al–Cu Cast Alloy by Casting Simulation Software". W Lecture Notes on Multidisciplinary Industrial Engineering, 459–67. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9072-3_40.
Pełny tekst źródłaDeshmukh, Shilpa S., i Basava Annappa. "Prediction of Crime Hot Spots Using Spatiotemporal Ordinary Kriging". W Integrated Intelligent Computing, Communication and Security, 683–91. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8797-4_70.
Pełny tekst źródłaHart, Timothy C. "Hot Spots of Crime: Methods and Predictive Analytics". W 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.
Pełny tekst źródłaPreto, António J., Pedro Matos-Filipe, José G. de Almeida, Joana Mourão i Irina S. Moreira. "Predicting Hot Spots Using a Deep Neural Network Approach". W Methods in Molecular Biology, 267–88. New York, NY: Springer US, 2020. http://dx.doi.org/10.1007/978-1-0716-0826-5_13.
Pełny tekst źródłaZhang, Wenjuan, Lin Wang, Zhiwei Sun, Bianqiang Zhang, Qiaoqiao Tang i Qiang Gao. "Prediction of Hot Spots in Dimer Interface of Green Fluorescent Protein". W Lecture Notes in Electrical Engineering, 349–55. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4801-2_35.
Pełny tekst źródłaGan, Haomin, Jing Hu, Xiaolong Zhang, Qianqian Huang i Jiafu Zhao. "Accurate Prediction of Hot Spots with Greedy Gradient Boosting Decision Tree". W Intelligent Computing Theories and Application, 353–64. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95933-7_43.
Pełny tekst źródłaSun, Zhen, Jun Zhang, Chun-Hou Zheng, Bing Wang i Peng Chen. "Accurate Prediction of Protein Hot Spots Residues Based on Gentle AdaBoost Algorithm". W Intelligent Computing Theories and Application, 742–49. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42291-6_74.
Pełny tekst źródłaStreszczenia konferencji na temat "Hot spot prediction"
Bender, Christopher J., i Robert G. Dean. "Erosional Hot Spot Prediction through Wave Analysis". W 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.
Pełny tekst źródłaMoreira, Irina, José Almeida, António Preto, Rita Melo, Zeynep Gümüş, Joaquim Costa i Alexandre Bonvin. "Co-evolution importance on binding Hot-Spot prediction methods". W MOL2NET 2016, International Conference on Multidisciplinary Sciences, 2nd edition. Basel, Switzerland: MDPI, 2017. http://dx.doi.org/10.3390/mol2net-02-03889.
Pełny tekst źródłaRepantis, Thomas, i Vana Kalogeraki. "Hot-spot prediction and alleviation in distributed stream processing applications". W 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.
Pełny tekst źródłaVidja, Akash, Harshad Nayakpara, Raghavendra Bhalera i Kshitij Bhargava. "Methods for Calculating the Transformer Hot-Spot Temperature and Lifetime Prediction". W 2018 3rd International Conference for Convergence in Technology (I2CT). IEEE, 2018. http://dx.doi.org/10.1109/i2ct.2018.8529398.
Pełny tekst źródłaSaripalli, P., G. V. R. Kiran, R. R. Shankar, H. Narware i N. Bindal. "Load Prediction and Hot Spot Detection Models for Autonomic Cloud Computing". W 2011 IEEE 4th International Conference on Utility and Cloud Computing (UCC 2011). IEEE, 2011. http://dx.doi.org/10.1109/ucc.2011.66.
Pełny tekst źródłaYoo, Sung Goo, i Kil To Chong. "Hot Spot Prediction Algorithm for Shared Web Caching System Using NN". W 2007 International Symposium on Information Technology Convergence (ISITC 2007). IEEE, 2007. http://dx.doi.org/10.1109/isitc.2007.33.
Pełny tekst źródłaAli, Hasnain, Raphael Delair, Duc-Thinh Pham, Sameer Alam i Michael Schultz. "Dynamic Hot Spot Prediction by Learning Spatial- Temporal Utilization of Taxiway Intersections". W 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.
Pełny tekst źródłaWang, Shoufeng, Fan Li, Hao Ni, Lexi Xu, Meifang Jing, Junyi Yu i Xidong Wang. "Rush Hour Capacity Enhancement in 5G Network Based on Hot Spot Floating Prediction". W 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.
Pełny tekst źródłaTetzlaff, Dirk, i Sabine Glesner. "Static prediction of recursion frequency using machine learning to enable hot spot optimizations". W 2012 IEEE 10th Symposium on Embedded Systems for Real-time Multimedia (ESTIMedia). IEEE, 2012. http://dx.doi.org/10.1109/estimedia.2012.6507027.
Pełny tekst źródłaJanicki, Marcin, Zbigniew Kulesza i Andrzej Napieralski. "Distributed network of remote sensors for real time prediction of hot spot temperature values". W 2010 Ninth IEEE Sensors Conference (SENSORS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icsens.2010.5690097.
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