Algebraic and combinatorial aspects of tropical geometry : CIEM workshop tropical geometry, December 12-16, 2011, International Centre for Mathematical Meetings, Castro Urdiales, Spain / Erwan Brugallé, María Angélica Cueto, Alice Dickenstein, Eva-Maria Feichtner, Ilia Itenberg, editors

• Record Nr.: UNINA990009787630403321
• Pubbl/distr/stampa: Providence : American Mathematical Society, 2013
• ISBN: 978-0-8218-9146-9
• Descrizione fisica: X, 350 p. ; 25 cm
• Collana: Contemporary mathematics ; 589
• Disciplina: 516.3'5
• Locazione: MA1
• Collocazione: C-1-(589
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia

Clinical atlas of small animal cytology / Andrew Burton

• Record Nr.: UNINA9910348056903321
• Autore: Burton, Andrew G.
• Pubbl/distr/stampa: Hoboken : Wiley, 2018
• ISBN: 9781119215127
• Descrizione fisica: XIII, 364 p. : ill. ; 29 cm
• Disciplina: 636.08910181
• Locazione: FMVBC
• Collocazione: 636.08910181 BUR 1
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia

Knowledge discovery in bioinformatics [[electronic resource] ] : techniques, methods, and applications / / edited by Xiaohua Hu, Yi Pan

• Record Nr.: UNINA9910143415403321
• Pubbl/distr/stampa: Hoboken, N.J., : Wiley-Interscience, c2007
• ISBN: 1-280-90018-0; 9786610900183; 0-470-12464-4; 0-470-12463-6
• Descrizione fisica: 1 online resource (405 p.)
• Collana: Wiley Series in Bioinformatics
• Altri autori (Persone): HuXiaohua <1960->; PanYi <1960->
• Disciplina: 570.285; 570/.285; 572.80285
• Soggetti: Bioinformatics; Computational biology; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di contenuto: KNOWLEDGE DISCOVERY IN BIOINFORMATICS; CONTENTS; Contributors; Preface; 1 Current Methods for Protein Secondary-Structure Prediction Based on Support Vector Machines; 1.1 Traditional Methods; 1.1.1 Statistical Approaches; 1.1.2 Machine Learning Approaches; 1.2 Support Vector Machine Method; 1.2.1 Introduction to SVM; 1.2.2 Encoding Profile; 1.2.3 Kernel Functions; 1.2.4 Tertiary Classifier Design; 1.2.5 Accuracy Measure of SVM; 1.3 Performance Comparison of SVM Methods; 1.4 Discussion and Conclusions; References; 2 Comparison of Seven Methods for Mining Hidden Links; 2.1 Analysis of the Literature on Raynaud's Disease2.2 Related Work; 2.3 Methods; 2.3.1 Information Measures; 2.3.2 Ranking Methods; 2.3.3 Seven Methods; 2.4 Experiment Results and Analysis; 2.4.1 Data Set; 2.4.2 Chi-Square, Chi-Square Association Rule, and Mutual Information Link ABC Methods Compared; 2.4.3 Chi-Square ABC Method: Semantic Check for Mining Implicit Connections; 2.4.4 Chi-Square and Mutual Information Link ABC Methods; 2.5 Discussion and Conclusions; Acknowledgments; References; 3 Voting Scheme-Based Evolutionary Kernel Machines for Drug Activity Comparisons; 3.1 Granular Kernel and Kernel Tree Design3.1.1 Definitions; 3.1.2 Granular Kernel Properties; 3.2 GKTSESs; 3.3 Evolutionary Voting Kernel Machines; 3.4 Simulations; 3.4.1 Data Set and Experimental Setup; 3.4.2 Experimental Results and Comparisons; 3.5 Conclusions and Future Work; Acknowledgments; References; 4 Bioinformatics Analyses of Arabidopsis thaliana Tiling Array Expression Data; 4.1 Tiling Array Design and Data Description; 4.1.1 Data; 4.1.2 Tiling Array Expression Patterns; 4.1.3 Tiling Array Data Analysis; 4.2 Ontology Analyses; 4.3 Antisense Regulation Identification; 4.3.1 Antisense Silencing4.3.2 Antisense Regulation Identification; 4.4 Correlated Expression Between Two DNA Strands; 4.5 Identification of Nonprotein Coding mRNA; 4.6 Summary; Acknowledgments; References; 5 Identification of Marker Genes from High-Dimensional Microarray Data for Cancer Classification; 5.1 Feature Selection; 5.1.1 Taxonomy of Feature Selection; 5.1.2 Evaluation Criterion; 5.1.3 Generation Procedure; 5.2 Gene Selection; 5.2.1 Individual Gene Ranking; 5.2.2 Gene Subset Selection; 5.2.3 Summary of Gene Selection; 5.3 Comparative Study of Gene Selection Methods; 5.3.1 Microarray Data Descriptions5.3.2 Gene Selection Approaches; 5.3.3 Experimental Results; 5.4 Conclusions and Discussion; Acknowledgments; References; 6 Patient Survival Prediction from Gene Expression Data; 6.1 General Methods; 6.1.1 Kaplan-Meier Survival Analysis; 6.1.2 Cox Proportional-Hazards Regression; 6.2 Applications; 6.2.1 Diffuse Large-B-Cell Lymphoma; 6.2.2 Lung Adenocarcinoma; 6.2.3 Remarks; 6.3 Incorporating Data Mining Techniques to Survival Prediction; 6.3.1 Gene Selection by Statistical Properties; 6.3.2 Cancer Subtype Identification via Survival Information; 6.4 Selection of Extreme Patient Samples
• Sommario/riassunto: The purpose of this edited book is to bring together the ideas and findings of data mining researchers and bioinformaticians by discussing cutting-edge research topics such as, gene expressions, protein/RNA structure prediction, phylogenetics, sequence and structural motifs, genomics and proteomics, gene findings, drug design, RNAi and microRNA analysis, text mining in bioinformatics, modelling of biochemical pathways, biomedical ontologies, system biology and pathways, and biological database management.

Brines and evaporites

• Record Nr.: UNINA9910133717803321
• Autore: Sonnenfeld Peter
• Pubbl/distr/stampa: [Place of publication not identified], : American Geophysical Union, 1989
• ISBN: 1-118-66754-9
• Collana: Short course in geology Brines and evaporites
• Disciplina: 552/.5
• Soggetti: Salt; Evaporites; Geology; Earth & Environmental Sciences; Petrology
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Bibliographic Level Mode of Issuance: Monograph