LEADER 00837nac# 22002171i 450 001 UON00337618 005 20231205104245.774 011 $a0398-9992 100 $a20091012f |0itac50 ba 102 $aFR 105 $a|||| ||||| 110 $ab|||||||||| 200 1 $aˆLe ‰Licorne 210 $aRennes$cPresses Universitaires de Rennes 463 1$1001UON00327671$12001 $aˆLe ‰Defi de l'art$ePhilostrate, Callistrate et l'image sophistique$fetudes reunies et presentees par Michel Costantini, Francoise Graziani, Stephane Rolet$1210 $aRennes$cPresses Universitaires de Rennes$d2006$1215 $a286 p.$cill.$d21 cm$v75 620 $aFR$dRennes$3UONL001559 712 $aPresses Universitaires de Rennes$3UONV269369$4650 801 $aIT$bSOL$c20240220$gRICA 912 $aUON00337618 996 $aLicorne$91323870 997 $aUNIOR LEADER 05182nam 22008895 450 001 9910485010303321 005 20251226202837.0 010 $a1-280-86560-1 010 $a9786610865604 010 $a3-540-71037-X 024 7 $a10.1007/978-3-540-71037-0 035 $a(CKB)1000000000284116 035 $a(SSID)ssj0000301137 035 $a(PQKBManifestationID)11235511 035 $a(PQKBTitleCode)TC0000301137 035 $a(PQKBWorkID)10260154 035 $a(PQKB)10121673 035 $a(DE-He213)978-3-540-71037-0 035 $a(MiAaPQ)EBC3036664 035 $a(MiAaPQ)EBC6703001 035 $a(Au-PeEL)EBL6703001 035 $a(PPN)123160588 035 $a(MiAaPQ)EBC302095 035 $a(EXLCZ)991000000000284116 100 $a20100301d2007 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aKnowledge Discovery and Emergent Complexity in Bioinformatics $eFirst International Workshop, KDECB 2006, Ghent, Belgium, May 10, 2006, Revised Selected Papers /$fedited by Karl Tuyls, Ronald Westra, Yvan Saeys, Ann Nowé 205 $a1st ed. 2007. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2007. 215 $a1 online resource (X, 184 p.) 225 1 $aLecture Notes in Bioinformatics,$x2366-6331 ;$v4366 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a3-540-71036-1 327 $aKnowledge Discovery and Emergent Complexity in Bioinformatics -- Boolean Algebraic Structures of the Genetic Code: Possibilities of Applications -- Discovery of Gene Regulatory Networks in Aspergillus fumigatus -- Complexity Measures for Gene Assembly -- Learning Relations from Biomedical Corpora Using Dependency Trees -- Advancing the State of the Art in Computational Gene Prediction -- Enhancing Coding Potential Prediction for Short Sequences Using Complementary Sequence Features and Feature Selection -- The NetGenerator Algorithm: Reconstruction of Gene Regulatory Networks -- On the Neuronal Morphology-Function Relationship: A Synthetic Approach -- Analyzing Stigmergetic Algorithms Through Automata Games -- The Identification of Dynamic Gene-Protein Networks -- Sparse Gene Regulatory Network Identification. 330 $aThis book contains selected and revised papers of the International Symposium on Knowledge Discovery and Emergent Complexity in Bioinformatics (KDECB 2006), held at the University of Ghent, Belgium, May 10, 2006. In February 1943, the Austrian physicist Erwin Schrodi ¨ nger, one of the founding fathers of quantum mechanics, gave a series of lectures at Trinity College in Dublin titled ?What Is Life? The Physical Aspect of the Living Cell and Mind. ? In these l- tures Schrodi ¨ nger stressed the fundamental differencesencountered between observing animate and inanimate matter, and advanced some, at the time, audacious hypotheses aboutthe nature andmolecularstructureof genes, some ten yearsbeforethe discoveries of Watson and Crick. Indeed, the rules of living matter, from the molecular level to the level of supraorganic ocking behavior, seem to violate the simple basic interactions found between fundamental particles as electrons and protons. It is as if the organic molecules in the cell ?know? that they are alive. Despite all external stochastic uct- tions and chaos, process and additive noise, this machinery has been ticking for at least 3. 8 billion years. Yet, we may safely assume that the laws that governphysicsalso steer these complex associations of synchronous and seemingly intentional dynamics in the cell. 410 0$aLecture Notes in Bioinformatics,$x2366-6331 ;$v4366 606 $aBiochemistry 606 $aData mining 606 $aArtificial intelligence 606 $aInformation storage and retrieval systems 606 $aBioinformatics 606 $aComputer science$xMathematics 606 $aMathematical statistics 606 $aBiochemistry 606 $aData Mining and Knowledge Discovery 606 $aArtificial Intelligence 606 $aInformation Storage and Retrieval 606 $aComputational and Systems Biology 606 $aProbability and Statistics in Computer Science 615 0$aBiochemistry. 615 0$aData mining. 615 0$aArtificial intelligence. 615 0$aInformation storage and retrieval systems. 615 0$aBioinformatics. 615 0$aComputer science$xMathematics. 615 0$aMathematical statistics. 615 14$aBiochemistry. 615 24$aData Mining and Knowledge Discovery. 615 24$aArtificial Intelligence. 615 24$aInformation Storage and Retrieval. 615 24$aComputational and Systems Biology. 615 24$aProbability and Statistics in Computer Science. 676 $a006.3 700 $aTuyls$b Karl$01224423 701 $aTuyls$b Karl$01224423 712 12$aKDECB 2006 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910485010303321 996 $aKnowledge discovery and emergent complexity in bioinformatics$92842042 997 $aUNINA