Statistical modelling of molecular descriptors in QSAR/QSPR:
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| Format: | Book |
| Language: | English |
| Published: |
Weinheim, Bergstr
Wiley-VCH
2012
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| Edition: | 1. Aufl. |
| Series: | Quantitative and network biology
2 |
| Subjects: | |
| Online Access: | Inhaltstext Inhaltsverzeichnis |
| Physical Description: | XIX, 436 S. Ill., graph. Darst. 240 mm x 170 mm |
| ISBN: | 9783527324347 3527324348 |
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| 245 | 1 | 0 | |a Statistical modelling of molecular descriptors in QSAR/QSPR |c ed. by Matthias Dehmer ... |
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| 300 | |a XIX, 436 S. |b Ill., graph. Darst. |c 240 mm x 170 mm | ||
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IMAGE 1
V
CONTENTS
PREFACE X I I I
LIST O F CONTRIBUTORS X V
1 CURRENT MODELING METHODS USED IN QSAR/QSPR 1
LIEW CHIN YEE AND YAP CHUN WEI 1.1 INTRODUCTION 1
1.2 MODELING METHODS 3
1.2.1 METHODS FOR REGRESSION PROBLEMS 3
1.2.1.1 MULTIPLE LINEAR REGRESSION 3 1.2.1.2 PARTIAL LEAST SQUARES 4
1.2.1.3 FEEDFORWARD BACKPROPAGATION NEURAL NETWORK 5 1.2.1.4 GENERAL
REGRESSION NEURAL NETWORK 7 1.2.1.5 GAUSSIAN PROCESSES 9
1.2.2 METHODS FOR CLASSIFICATION PROBLEMS 10 1.2.2.1 LOGISTIC REGRESSION
10 1.2.2.2 LINEAR DISCRIMINANT ANALYSIS 11 1.2.2.3 DECISION TREE AND
RANDOM FOREST 12
1.2.2.4 K-NEAREST NEIGHBOR 14 1.2.2.5 PROBABILISTIC NEURAL NETWORK 15
1.2.2.6 SUPPORT VECTOR MACHINE 16 1.3 SOFTWARE FOR QSAR DEVELOPMENT 18
1.3.1 STRUCTURE DRAWING OR FILE CONVERSION 19 1.3.2 3D STRUCTURE
GENERATION 19
1.3.3 DESCRIPTOR CALCULATION 20
1.3.4 MODELING 21
1.3.5 GENERAL PURPOSE 23
1.4 CONCLUSION 24
REFERENCES 26
HTTP://D-NB.INFO/1015578330
IMAGE 2
VI C O N T E N T S
2 DEVELOPING BEST PRACTICES FOR DESCRIPTOR-BASED PROPERTY
PREDICTION: APPROPRIATE MATCHING O F DATASETS, DESCRIPTORS, METHODS, AND
EXPECTATIONS 33 MICHAEL KREIN, TAO-WEI HUANG, LISA MORKOWCHUK, DIMITRIS
K. AGRAFIOTIS, AND CURT M. BRENEMAN 2.1 INTRODUCTION 33
2.1.1 POSING THE QUESTION 3 4
2.1.2 VALIDATING THE MODELS 35
2.1.3 INTERPRETING THE MODELS 36
2.2 LEVERAGING EXPERIMENTAL DATA AND UNDERSTANDING THEIR LIMITATIONS 36
2.3 DESCRIPTORS: THE LEXICON O F QSARS 3 7
2.3.1 CLASSICAL QSAR DESCRIPTORS AND USES 3 8
2.3.2 EXPERIMENTALLY DERIVED DESCRIPTORS 3 8 2.3.2.1 BIODESCRIPTORS 39
2.3.2.2 DESCRIPTORS FROM SPECTROSCOPY/SPECTROMETRY AND MICROSCOPY 40
2.3.3 OD, I D AND 2D COMPUTATIONAL DESCRIPTORS 40 2.3.4 3D DESCRIPTORS
AND BEYOND 41
2.3.5 LOCAL MOLECULAR SURFACE PROPERTY DESCRIPTORS 42 2.3.6 QUANTUM
CHEMICAL DESCRIPTORS 42
2.4 MACHINE LEARNING METHODS: THE GRAMMAR O F QSARS 44 2.4.1 PRINCIPAL
COMPONENT ANALYSIS 44
2.4.2 FACTOR ANALYSIS 4 5
2.4.3 MULTIDIMENSIONAL SCALING, STOCHASTIC PROXIMITY EMBEDDING, AND
OTHER NONLINEAR DIMENSIONALITY REDUCTION METHODS 4 5 2.4.4 CLUSTERING 46
2.4.5 PARTIAL LEAST SQUARES (PLS) 4 7
2.4.6 FC-NEAREST NEIGHBORS (KNN) 4 7
2.4.7 NEURAL NETWORKS 4 8
2.4.8 ENSEMBLE MODELS 49
2.4.9 DECISION TREES AND RANDOM FORESTS 49
2.4.10 KERNEL METHODS 5 0
2.4.11 RANKING METHODS 52
2.5 DEFINING MODELING STRATEGIES: PUTTING IT ALL TOGETHER 52 2.6
CONCLUSIONS 56
REFERENCES 5 7
3 MOLD 2 MOLECULAR DESCRIPTORS FOR QSAR 65
HUIXIAO HONG, SVETOSLAV SLAVOI/, WEIGONG CE, FENG QIAN, ZHENQIANG SU,
HONG FANG, YIYU CHENG, ROGER PERKINS, LEMING SHI, AND WEIDA TONG 3.1
BACKGROUND 65
3.1.1 HISTORY O F QSAR 65
3.1.2 INTRODUCTION TO QSAR 67
3.1.3 MOLECULAR DESCRIPTORS: BRIDGE FOR QSAR 68 3.1.3.1 MOLECULAR
DESCRIPTORS 69 3.1.3.2 ROLE O F MOLECULAR DESCRIPTORS 70
IMAGE 3
CONTENTS V I I
3.1.3.3 TYPES O F MOLECULAR DESCRIPTORS 71
3.1.3.4 CALCULATION O F MOLECULAR DESCRIPTORS (SOFTWARE PACKAGES) 71 3.2
MOLD 2 MOLECULAR DESCRIPTORS 71
3.2.1 DESCRIPTION O F MOLD 2 DESCRIPTORS 73 3.2.1.1 TOPOLOGICAL
DESCRIPTORS 73 3.2.1.2 CONSTITUTIONAL DESCRIPTORS 94 3.2.1.3 INFORMATION
CONTENT-BASED DESCRIPTORS 94 3.2.2 CALCULATION O F MOLD2 DESCRIPTORS 94
3.2.3 EVALUATION O F MOLD 2 DESCRIPTORS 96
3.2.3.1 INFORMATION CONTENT BY SHANNON ENTROPY ANALYSIS 96 3.2.3.2
CORRELATIONS BETWEEN DESCRIPTORS 98 3.3 QSAR USING MOLD 2 DESCRIPTORS 99
3.3.1 CLASSIFICATION MODELS BASED ON MOLD 2 DESCRIPTORS 100 3.3.2
REGRESSION MODELS BASED ON MOLD2 DESCRIPTORS 102 3.4 CONCLUSION REMARKS
105
REFERENCES 105
4 MULTIVARIATE ANALYSIS O F MOLECULAR DESCRIPTORS 111 VIVIANA CONSONNI
AND ROBERTO TODESCHINI 4.1 INTRODUCTION 111
4.2 2D MATRIX-BASED DESCRIPTORS 114
4.3 GRAPH-THEORETICAL MATRICES 120
4.3.1 VERTEX WEIGHTING SCHEMES 122
4.4 MULTIVARIATE SIMILARITY ANALYSIS O F CHEMICAL SPACES 122 4.5
ANALYSIS O F CHEMICAL INFORMATION O F DESCRIPTORS FROM GRAPH-THEORETICAL
MATRICES 124 4.5.1 DATA SETS 124
4.5.2 COMPARISON O F GRAPH-THEORETICAL MATRICES 125 4.5.2.1 COMPARISON O
F WEIGHTED GRAPH-THEORETICAL MATRICES 130 4.5.3 COMPARISON O F MATRIX
OPERATORS 133 4.5.4 COMPARISON O F SINGLE OPERATORS FROM DIFFERENT
GRAPH-THEORETICAL MATRICES 137 4.6 CONCLUSIONS 143
REFERENCES 143
5 PARTIAL-ORDER RANKING AND LINEAR MODELING: THEIR USE IN PREDICTIVE
QSAR/QSPR STUDIES 149 ANDREW C. MERCADER AND EDUARDO A. CASTRO 5.1
INTRODUCTION 149
5.2 LINEAR QSAR METHODOLOGY, ERM, RM AND GA 150 5.2.1 REPLACEMENT METHOD
153
5.2.2 ENHANCED REPLACEMENT METHOD 154 5.2.3 GENETIC ALGORITHM 154
5.2.4 MAIN DIFFERENCES BETWEEN MRM AND RM 156 5.3 PRINCIPLES O F RANKING
METHODS 159
IMAGE 4
VIII C O N T E N T S
5.4 SELECTION O F THE MOLECULAR DESCRIPTORS FOR RANKING 163
5.5 QSAR BASED ON HASSE DIAGRAMS 165
5.6 DISCUSSION 165
5.7 CONCLUSIONS 169
REFERENCES 170
6 GRAPH-THEORETICAL DESCRIPTORS FOR BRANCHED POLYMERS 275 KOH-HEI NITTA
6.1 INTRODUCTION 175
6.2 ALGEBRAIC GRAPH THEORY 176
6.3 IDEAL CHAIN MODELS 180
6.4 GRAPH-THEORETICAL APPROACH TO CHAIN DYNAMICS AND STATISTICS 182
6.4.1 RADIUS O F GYRATION 182
6.4.2 ROUSE DYNAMICS 185
6.4.3 INTRINSIC VISCOSITY 188
6.4.4 SCATTERING FUNCTION 190
6.4.5 HIGH MOMENTS O F RELAXATION TIME AND RADIUS O F GYRATION 191 6.5
APPLICATIONS 193
6.6 FINAL REMARKS 194
REFERENCES 196
7 STRUCTURAL-SIMILARITY-BASED APPROACHES FOR THE DEVELOPMENT O F
CLUSTERING AND QSPR/QSAR MODELS IN CHEMICAL DATABASES 201 IRENE LUQUE
RUIZ, CONZALO CERRUELA GARCIA, AND MIGUEL ANGEL COMEZ-NIETO
7.1 CHEMICAL STRUCTURAL SIMILARITY 201
7.1.1 MOLECULAR GRAPH AND STRUCTURAL SIMILARITY 203 7.1.2
DESCRIPTOR-BASED STRUCTURAL SIMILARITY 203 7.1.3 COMBINING STRUCTURAL
SIMILARITY APPROACHES 204 7.1.4 APPROXIMATE STRUCTURAL SIMILARITY 205
7.2 CLUSTERING MODELS BASED O N STRUCTURAL SIMILARITY 207 7.2.1
CLUSTERING O F CHEMICAL DATABASES 211 7.2.1.1 PATTERN REPRESENTATION O F
CHEMICALS STRUCTURES 211 7.2.1.2 CLUSTERING O F CHEMICAL DATABASES 212
7.3 QSPR/QSAR MODELS BASED ON STRUCTURAL SIMILARITY 217 7.3.1 DATASET
SELECTION 219
7.3.2 DATASET REPRESENTATION 220
7.3.3 FITTING O F THE DATASET REPRESENTATION 221
7.3.4 BUILDING AND VALIDATION O F THE QSAR MODEL 221 REFERENCES 223
8 STATISTICAL METHODS FOR PREDICTING COMPOUND RECOVERY RATES FOR LIGAND-
BASED VIRTUAL SCREENING AND ASSESSING THE PROBABILITY O F ACTIVITY 229
MARTIN VOGT ANDJURGEN BAJORATH 8.1 INTRODUCTION 229
8.2 THEORY 231
IMAGE 5
CONTENTS IX
8.2.1 BAYESIAN APPROACH TO VIRTUAL SCREENING 231
8.2.2 PREDICTING THE PERFORMANCE O F BAYESIAN SCREENING 235 8.2.3
PRACTICAL PREDICTION O F COMPOUND RECALL 236 8.2.4 EXEMPLARY RESULTS 238
8.3 ALTERNATIVE APPROACHES TO THE PREDICTION O F COMPOUND RECALL 238 8.4
CONCLUSIONS 240
REFERENCES 241
9 MOLECULAR DESCRIPTORS AND THE ELECTRONIC STRUCTURE 245
BOGEL HORST
9.1 INTRODUCTION 245
9.2 THE STRUCTURE O F MOLECULES 246
9.2.1 GENERAL REMARKS 246
9.2.2 STRUCTURE CODING 247
9.2.3 STRUCTURAL FEATURES 248
9.2.4 STRUCTURE AND ENERGY 250
9.3 THE ELECTRONIC STRUCTURE 251
9.4 DIVIDING MOLECULES IN ATOMS AND BONDS 254
9.4.1 BONDING I N MOLECULES 254
9.4.2 ENERGY PARTITIONING 255
9.4.3 ENERGY AND THE HIICKEL APPROACH 255
9.4.4 ENERGY COMPONENTS O F ATOMS AND BONDS 256 9.4.5 PERTURBATION
TREATMENT O F THE ELECTRONIC STRUCTURE 257 9.4.6 THERMODYNAMIC
EQUILIBRIUM 258
9.4.7 MODEL O F "ATOM IN MOLECULES" 258
9.5 STRUCTURE AND DYNAMICS 259
9.5.1 MOLECULAR FLEXIBILITY 259
9.5.2 MOLECULAR DYNAMICS SIMULATION 259 9.5.3 CONFORMATIONAL SPACE 260
9.6 STRUCTURE AND PROPERTIES 262
9.6.1 STRUCTURE PROPERTY RELATIONSHIPS 262
9.6.2 TYPE O F MOLECULAR PROPERTIES 262
9.6.3 MOLECULAR COMMONALITY AND SIMILARITY 263 9.6.4 MULTILINEAR
REGRESSION 263
9.6.5 SELECTION O F MOLECULAR DESCRIPTORS 265 9.7 MODELING O F
PHYSICOCHEMICAL PROPERTIES O F THE ISOMERS O F HEXANE 265 9.8 MODELING O
F THE PROTON AFFINITY 275
9.8.1 PROTON AFFINITY O F PYRIDINES 275
9.8.1.1 DATA AND MECHANISM 275
9.8.1.2 MODEL I 277
9.8.1.3 MODEL II 278
9.8.1.4 MODEL III 280
9.8.1.5 MODEL IV 281
9.8.1.6 MODEL V 281
9.8.1.7 MODEL VI 282
IMAGE 6
X CONTENTS
9.8.2 BASICITY O F N-HETEROCYCLIC AROMATICS 283
9.9 MOLECULAR SURFACE PROPERTIES 285
9.10 CONCLUSIONS 290
REFERENCES 291
10 NEW TYPES O F DESCRIPTORS AND MODELS IN QSAR/QSPR 293 CHRISTIAN
KRAMER AND TIMOTHY CLARK 10.1 INTRODUCTION 293
10.2 LOCAL PROPERTIES 294
10.2.1 MOLECULAR ELECTROSTATIC POTENTIAL 294 10.2.2 ELECTRON DENSITY 295
10.2.3 LOCAL POLARIZABILITY 295
10.2.4 LOCAL IONIZATION ENERGY AND LOCAL ELECTRON AFFINITY 296 10.3
DESCRIPTORS DERIVED FROM LOCAL PROPERTIES 297 10.3.1 PEST METHODOLOGY
297
10.4 MEP AS DESCRIPTOR FOR HYDROGEN-BONDING STRENGTHS 298 10.5 PARASURF
(POLITZER-MURRAY) DESCRIPTORS 298 10.6 4D: CONFORMATIONAL-ENSEMBLE-BASED
DESCRIPTORS 299 10.7 PROPER VALIDATION/GENERATION O F QSA(P)R MODELS 300
10.8 CONCLUSIONS 302
REFERENCES 303
H CONSENSUS MODELS O F ACTIVITY LANDSCAPES 307
JOSE L MEDINA-FRANCO, AUSTIN B. YONGYE, AND FABIAN LOPEZ-VALLEJO 11.1
INTRODUCTION 307
11.2 CHARACTERIZATION O F THE ACTIVITY LANDSCAPE 309 11.3 CONSENSUS
MODELS O F ACTIVITY LANDSCAPE 312 11.3.1 CHEMICAL SPACE AND MOLECULAR
REPRESENTATION 312 11.3.2 ACTIVITY LANDSCAPE WITH MULTIPLE
REPRESENTATIONS 316 11.4 CONCLUSIONS AND FUTURE PERSPECTIVES 322
REFERENCES 323
12 REVERSE ENGINEERING CHEMICAL REACTION NETWORKS FROM TIME SERIES DATA
327 DOMINIC P. SEARSON, MARK J. WILLIS, AND ALLEN WRIGHT 12.1
INTRODUCTION 327
12.2 PROBLEM DEFINITION 329
12.3 RECONSTRUCTION O F ELEMENTARY REACTION NETWORKS FROM DATA BY
NETWORK SEARCH 331
12.3.1 NETWORK SEARCH AS A NONLINEAR INTEGER PROGRAMMING PROBLEM 332
12.3.2 ESTIMATION O F THE RATE COEFFICIENTS FOR TRIAL REACTION NETWORKS
333 12.4 FORMULATION O F THE OBJECTIVE FUNCTION FOR NETWORK SEARCH 335
12.4.1 PHYSICAL/CHEMICAL INFORMATION AVAILABLE 336
12.4.2 NO PHYSICAL/CHEMICAL INFORMATION AVAILABLE 336
IMAGE 7
12.5
12.5.1 12.5.2 12.6 12.6.1
12.6.2
12.6.3 12.6.4 12.7
13
13.1 13.2 13.3 13.4 13.5
14
14.1 14.2 14.3
14.4
15
15.1 15.2
15.2.1
15.2.1.1 15.2.1.2
CONTENTS X I
DIFFERENTIAL EVOLUTION FOR SEARCHING THE SPACE O F REACTION
NETWORKS 337 BASIC DE OPTIMIZATION METHOD 338 SELF-ADAPTIVE DE WITH
INTEGER VARIABLES 339 NETWORK IDENTIFICATION CASE STUDIES 340 ESTIMATION
O F TIME DERIVATIVES 342 DE SETTINGS 343 MODEL SELECTION METHODOLOGY 343
RESULTS 344 CONCLUSIONS 346 REFERENCES 347
REDUCTION O F DIMENSIONALITY, ORDER, AND CLASSIFICATION IN SPACES O F
THEORETICAL DESCRIPTIONS O F MOLECULES: AN APPROACH BASED ON METRICS,
PATTERN RECOGNITION TECHNIQUES, AND GRAPH THEORETIC CONSIDERATIONS 349
GEORGE MAROULIS INTRODUCTION 349 THEORY 351 METHODS AND COMPUTATIONAL
STRATEGY 354
RESULTS AND DISCUSSION 358 CONCLUSIONS 363 REFERENCES 363
THE ANALYSIS O F ORGANIC REACTION PATHWAYS BY BROWNIAN PROCESSING 365
DANIEL J. GRAHAM INTRODUCTION 365 ELECTRONIC MESSAGES, INFORMATION, AND
ENERGY 366 MOLECULAR MESSAGES, CONVERSIONS, AND STATE SPACE
REPRESENTATIONS 374 CLOSING 389 REFERENCES 390
GENERATION O F CHEMICAL TRANSFORMATIONS: REACTION PATHWAYS PREDICTION
AND SYNTHESIS DESIGN 393 GRAZYNA NOWAK AND GRZEGORZ FIC INTRODUCTION 393
THE GRAPH TRANSFORMATION RULES FOR GENERATION O F CHEMICAL
REACTIONS 396 THE GRAPH-THEORETIC REACTION RULES AND FORMAL-LOGICAL
APPROACH FOR REACTION GENERATION 397 THE CHEMICAL REACTION GRAPH 399
UGI AND DUGUNDJI FORMAL THEORY FOR REACTIONS AND REACTION MECHANISMS 400
IMAGE 8
XII CONTENTS
15.2.2 THE EMPIRICAL REACTION RULES AND KNOWLEDGE-BASED APPROACH
FOR REACTION GENERATION. AUTOMATED CREATION O F RULES BY LEARNING AND
REACTION DATABASE MINING 404 15.2.2.1 AUTOMATICALLY DERIVED REACTION
RULES 404 15.2.2.2 FUNCTIONAL GROUP TRANSFORMATIONS 406 15.2.2.3
SUBSTRUCTURE-BASED TRANSFORMATIONS 406
15.3 COMBINATORIAL COMPLEXITY PROBLEM: STRATEGIES FOR THE DIRECTED
REACTION GENERATION 409 15.3.1 RETROSYNTHETIC GENERATION O F CHEMICAL
TRANSFORMATIONS: COMPUTER-ASSISTED SYNTHESIS DESIGN 410 15.3.1.1
RECOGNITION O F GUIDING PATTERNS, MOLECULAR SYMMETRY, OR
ISOMORPHIC SUBSTRUCTURES 411 15.3.1.2 COMPLEXITY-BASED DISCONNECTIVE
STRATEGIES 412 15.3.1.3 CONCEPT O F THE STRATEGIC BOND TREE FOR
DISCONNECTIONS 413 15.3.2 FORWARD GENERATION O F CHEMICAL
TRANSFORMATIONS: COMPUTER-ASSISTED
REACTION PREDICTION 414 15.3.2.1 QUANTITATIVE MODELS FOR REACTIVITY
PREDICTION 416 15.3.2.2 FORMAL-LOGICAL APPROACH TO THE SEARCH SPACE O F
POSSIBLE CHEMICAL TRANSFORMATIONS 418
15.4 CONCLUSION 419
REFERENCES 420
INDEX 427 |
| any_adam_object | 1 |
| author2 | Dehmer, Matthias 1968- |
| author2_role | edt |
| author2_variant | m d md |
| author_GND | (DE-588)129565245 |
| author_facet | Dehmer, Matthias 1968- |
| building | Verbundindex |
| bvnumber | BV039951858 |
| classification_rvk | WC 7700 |
| ctrlnum | (OCoLC)782967519 (DE-599)DNB1015578330 |
| dewey-full | 572.80285 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 572 - Biochemistry |
| dewey-raw | 572.80285 |
| dewey-search | 572.80285 |
| dewey-sort | 3572.80285 |
| dewey-tens | 570 - Biology |
| discipline | Biologie |
| edition | 1. Aufl. |
| format | Book |
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| id | DE-604.BV039951858 |
| illustrated | Illustrated |
| indexdate | 2024-09-06T00:22:16Z |
| institution | BVB |
| isbn | 9783527324347 3527324348 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-024809764 |
| oclc_num | 782967519 |
| open_access_boolean | |
| owner | DE-11 DE-706 |
| owner_facet | DE-11 DE-706 |
| physical | XIX, 436 S. Ill., graph. Darst. 240 mm x 170 mm |
| publishDate | 2012 |
| publishDateSearch | 2012 |
| publishDateSort | 2012 |
| publisher | Wiley-VCH |
| record_format | marc |
| series | Quantitative and network biology |
| series2 | Quantitative and network biology |
| spelling | Statistical modelling of molecular descriptors in QSAR/QSPR ed. by Matthias Dehmer ... 1. Aufl. Weinheim, Bergstr Wiley-VCH 2012 XIX, 436 S. Ill., graph. Darst. 240 mm x 170 mm txt rdacontent n rdamedia nc rdacarrier Quantitative and network biology 2 QSAR (DE-588)4205429-1 gnd rswk-swf QSPR (DE-588)4645304-0 gnd rswk-swf Mathematische Modellierung (DE-588)7651795-0 gnd rswk-swf QSAR (DE-588)4205429-1 s QSPR (DE-588)4645304-0 s Mathematische Modellierung (DE-588)7651795-0 s DE-604 Dehmer, Matthias 1968- (DE-588)129565245 edt Quantitative and network biology 2 (DE-604)BV037388746 2 X:MVB text/html http://deposit.dnb.de/cgi-bin/dokserv?id=3887206&prov=M&dok_var=1&dok_ext=htm Inhaltstext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024809764&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Statistical modelling of molecular descriptors in QSAR/QSPR Quantitative and network biology QSAR (DE-588)4205429-1 gnd QSPR (DE-588)4645304-0 gnd Mathematische Modellierung (DE-588)7651795-0 gnd |
| subject_GND | (DE-588)4205429-1 (DE-588)4645304-0 (DE-588)7651795-0 |
| title | Statistical modelling of molecular descriptors in QSAR/QSPR |
| title_auth | Statistical modelling of molecular descriptors in QSAR/QSPR |
| title_exact_search | Statistical modelling of molecular descriptors in QSAR/QSPR |
| title_full | Statistical modelling of molecular descriptors in QSAR/QSPR ed. by Matthias Dehmer ... |
| title_fullStr | Statistical modelling of molecular descriptors in QSAR/QSPR ed. by Matthias Dehmer ... |
| title_full_unstemmed | Statistical modelling of molecular descriptors in QSAR/QSPR ed. by Matthias Dehmer ... |
| title_short | Statistical modelling of molecular descriptors in QSAR/QSPR |
| title_sort | statistical modelling of molecular descriptors in qsar qspr |
| topic | QSAR (DE-588)4205429-1 gnd QSPR (DE-588)4645304-0 gnd Mathematische Modellierung (DE-588)7651795-0 gnd |
| topic_facet | QSAR QSPR Mathematische Modellierung |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=3887206&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024809764&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV037388746 |
| work_keys_str_mv | AT dehmermatthias statisticalmodellingofmoleculardescriptorsinqsarqspr |