LEADER 04469nam 22006975 450 001 996465498803316 005 20200704024522.0 010 $a3-642-41491-5 024 7 $a10.1007/978-3-642-41491-6 035 $a(CKB)3710000000024422 035 $a(SSID)ssj0001049388 035 $a(PQKBManifestationID)11550222 035 $a(PQKBTitleCode)TC0001049388 035 $a(PQKBWorkID)11019138 035 $a(PQKB)11269121 035 $a(DE-He213)978-3-642-41491-6 035 $a(MiAaPQ)EBC3093156 035 $a(PPN)176116419 035 $a(EXLCZ)993710000000024422 100 $a20131004d2013 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aChinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data$b[electronic resource] $e12th China National Conference, CCL 2013 and First International Symposium, NLP-NABD 2013, Suzhou, China, October 10-12, 2013, Proceedings /$fedited by Maosong Sun, Min Zhang, Dekang Lin, Haifeng Wang 205 $a1st ed. 2013. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2013. 215 $a1 online resource (XIV, 354 p. 87 illus.) 225 1 $aLecture Notes in Artificial Intelligence ;$v8202 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-642-41490-7 327 $aWord Segmentation -- Open-Domain Q&A -- Discourse, Coreference and Pragmatics -- Statistical and Machine Learning Methods in NLP -- Semantics -- Text Mining, Open-Domain Information Extraction and Machine Reading of the Web -- Sentiment Analysis, Opinion Mining and Text Classification -- Lexical semantics and Ontologies -- Language Resources and Annotation -- Machine Translation -- Speech Recognition and Synthesis -- Tagging and Chunking -- Large-scale Knowledge Acquisition and Reasoning. . 330 $aThis book constitutes the refereed proceedings of the 12th China National Conference on Computational Linguistics, CCL 2013, and of the First International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2013, held in Suzhou, China, in October 2013. The 32 papers presented were carefully reviewed and selected from 252 submissions. The papers are organized in topical sections on word segmentation; open-domain question answering; discourse, coreference and pragmatics; statistical and machine learning methods in NLP; semantics; text mining, open-domain information extraction and machine reading of the Web; sentiment analysis, opinion mining and text classification; lexical semantics and ontologies; language resources and annotation; machine translation; speech recognition and synthesis; tagging and chunking; and large-scale knowledge acquisition and reasoning. 410 0$aLecture Notes in Artificial Intelligence ;$v8202 606 $aNatural language processing (Computer science) 606 $aArtificial intelligence 606 $aComputers 606 $aNatural Language Processing (NLP)$3https://scigraph.springernature.com/ontologies/product-market-codes/I21040 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aNatural Language Processing (NLP)$3https://scigraph.springernature.com/ontologies/product-market-codes/I21040 606 $aInformation Systems and Communication Service$3https://scigraph.springernature.com/ontologies/product-market-codes/I18008 615 0$aNatural language processing (Computer science). 615 0$aArtificial intelligence. 615 0$aComputers. 615 14$aNatural Language Processing (NLP). 615 24$aArtificial Intelligence. 615 24$aNatural Language Processing (NLP). 615 24$aInformation Systems and Communication Service. 676 $a495.1 702 $aSun$b Maosong$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aZhang$b Min$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLin$b Dekang$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWang$b Haifeng$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996465498803316 996 $aChinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data$92199626 997 $aUNISA LEADER 05122nam 2200649 a 450 001 9910779363403321 005 20230803020134.0 010 $a1-283-85621-2 010 $a0-19-165428-0 035 $a(CKB)2550000000707366 035 $a(EBL)1100081 035 $a(OCoLC)821965264 035 $a(SSID)ssj0000811604 035 $a(PQKBManifestationID)12349368 035 $a(PQKBTitleCode)TC0000811604 035 $a(PQKBWorkID)10850675 035 $a(PQKB)10605251 035 $a(MiAaPQ)EBC1100081 035 $a(Au-PeEL)EBL1100081 035 $a(CaPaEBR)ebr10631208 035 $a(CaONFJC)MIL416871 035 $a(MiAaPQ)EBC7037592 035 $a(Au-PeEL)EBL7037592 035 $a(EXLCZ)992550000000707366 100 $a20121210d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aPhysical principles in sensing and signaling$b[electronic resource] $ewith an introduction to modeling in biology /$fRobert G. Endres 210 $aOxford $cOxford University Press$d2013 215 $a1 online resource (158 p.) 300 $aDescription based upon print version of record. 311 $a0-19-960064-3 311 $a0-19-960063-5 320 $aIncludes bibliographical references and index. 327 $aCover; Contents; 1 Introduction; Chapter summary; Further reading; 2 Chemotaxis in bacterium Escherichia coli; 2.1 Chemical gradient sensing; 2.2 "Nose and brain": the receptor cluster; 2.3 E. coli chemotaxis pathway; 2.4 Experimental approaches; 2.5 Time-course data and dose-response curves; Chapter summary; Further reading; 3 Physical concepts; 3.1 Diffusion; 3.2 Boltzmann distribution; 3.3 Ligand-receptor binding; 3.4 Fluctuation-dissipation theorem; Chapter summary; Further reading; 4 Mathematical tools; 4.1 Ordinary differential equations; 4.2 Kinetic laws; 4.3 Master equation 327 $a4.4 Poisson distribution4.5 Waiting-time distribution; 4.6 Langevin small-noise approximation; 4.7 Information theory; Chapter summary; Further reading; 5 Signal amplification and integration; 5.1 Cooperativity by allostery; 5.2 Emergence of allostery from microscopic details; 5.3 Two-state equilibrium receptor model; 5.4 Monod-Wyman-Changeux model for receptor signaling; 5.5 Alternative Ising model for receptor cluster; Chapter summary; Further reading; 6 Robust precise adaptation; 6.1 Energy-landscape picture of adaptation; 6.2 Dynamics of adaptation; 6.3 Chemotactic response function 327 $a6.4 Integral-feedback control6.5 Assistance neighborhoods; Chapter summary; Further reading; 7 Polar receptor localization and clustering; 7.1 Trimer of dimers; 7.2 Elastic cluster-membrane model; 7.3 Polar receptor clustering; Chapter summary; Further reading; 8 Accuracy of sensing; 8.1 Perfectly absorbing sphere; 8.2 Perfectly monitoring sphere; 8.3 Sensing with cell-surface receptors; Chapter summary; Further reading; 9 Motor impulse response; 9.1 Impulse response; 9.2 Time and frequency domains; 9.3 Minimal pathway model; 9.4 Linear response approximation; 9.5 Noise power spectra 327 $aChapter summaryFurther reading; 10 Optimization of pathway; 10.1 Optimal receptor-complex size; 10.2 Optimal adaptation dynamics; Chapter summary; Further reading; 11 "Seeing like a bacterium"; 11.1 Typical chemical gradients; 11.2 Weber's law; 11.3 Perception; 11.4 Fold-change detection; 11.5 Matching relations; 11.6 Predicting typical stimuli; Chapter summary; Further reading; 12 Beyond E. coli chemotaxis; Chapter summary; Further reading; Appendix More techniques; A.1 Derivation of the fluctuation-dissipation theorem; A.2 Variational principles and the Euler-Lagrange equation 327 $aA.3 Gillespie simulationsA.4 Fokker-Planck approximation; A.5 Derivation of the Langevin noise; A.6 Time versus frequency domain; A.7 Model fitting to data; A.8 Principal component analysis; Chapter summary; Further reading; Index; A; B; C; D; E; F; G; H; I; L; M; N; O; P; Q; R; S; T; V; W 330 $aAlthough invisible to the bare eye, bacterial cells are large enough to make complex decisions. Cells are composed of thousands of different molecular species including DNA, proteins, and smaller molecules, allowing them to sense their environment, to process this information, and to respond accordingly. Such responses include expression of genes or the control of their movement. Despite these properties, a living cell exists in the physical world and follows its laws. Keeping thisin mind can help answer questions such as how cells work and why they implement solutions to problems the way they 606 $aBiology$xSimulation methods 606 $aBiology$xMathematical models 615 0$aBiology$xSimulation methods. 615 0$aBiology$xMathematical models. 676 $a571.43 676 $a571.634 700 $aEndres$b Robert G$0239841 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910779363403321 996 $aPhysical principles in sensing and signaling$93848893 997 $aUNINA