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1. |
Record Nr. |
UNINA9910548300403321 |
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Autore |
Shpuza Saimir |
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Titolo |
La Romanisation de l’Illyrie méridionale et de la Chaônie / / Saimir Shpuza |
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Pubbl/distr/stampa |
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Rome, : Publications de l’École française de Rome, 2021 |
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ISBN |
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Descrizione fisica |
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1 online resource (312 p.) |
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Collana |
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Collection de l'École française de Rome |
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Soggetti |
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Romans - Illyria |
Romans - Epirus (Greece and Albania) |
Inscriptions - Illyria |
Inscriptions - Epirus (Greece and Albania) |
Coins - Illyria |
Coins - Epirus (Greece and Albania) |
Pottery - Illyria |
Pottery - Epirus (Greece and Albania) |
Illyria Antiquities, Roman |
Epirus (Greece and Albania) Antiquities, Roman |
Rome History, Military |
Illyria Antiquities |
Epirus (Greece and Albania) Antiquities |
Illyria Civilization Roman influences |
Epirus (Greece and Albania) Civilization Roman influences |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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La romanisation est pour les archéologues une question complexe qui touche tant à la notion d’identité qu’aux problèmes inhérents à l’interprétation des témoins de la culture matérielle. Durant les vingt dernières années, l’étude de la romanisation s’est enrichie de bon nombre de publications importantes traitant de presque toutes les provinces de l’Empire romain, marquant une avancée significative dans |
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l’élucidation des modalités diverses de ce processus. Le territoire retenu comme objet d’étude par le présent travail se situe à la charnière des provinces balkano-danubiennes et grecques. Le matériel archéologique disponible, à la fois volumineux et diversifié (monnaies, céramiques, inscriptions), confronté aux structures urbaines mises au jour par les fouilles et à la dynamique de l’habitat rural permet de renouveler nos connaissances de plusieurs aspects de la vie quotidienne durant la période romaine. L’examen de l’ensemble de ces éléments permet d’offrir non seulement de nouvelles analyses de caractère archéologique, mais également une synthèse historique dont l’objectif essentiel est la mise en évidence du processus d’intégration des Illyriens et des Épirotes à l’Empire romain et qui marque alors leur civilisation. |
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2. |
Record Nr. |
UNINA9910823650003321 |
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Autore |
Chen Luonan <1962-> |
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Titolo |
Biomolecular networks : methods and applications in systems biology / / Luonan Chen, Rui-Sheng Wang, Xiang-Sun Zhang |
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Pubbl/distr/stampa |
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Hoboken, NJ, : Wiley, c2009 |
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ISBN |
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9786612186028 |
9781282186026 |
1282186027 |
9780470488065 |
0470488069 |
9780470488058 |
0470488050 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (420 p.) |
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Collana |
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Wiley series on bioinformatics |
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Altri autori (Persone) |
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WangRui-Sheng |
ZhangXiang-Sun <1943-> |
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Disciplina |
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Soggetti |
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Molecular biology - Data processing |
Computational biology |
Bioinformatics |
Biological systems - Research - Data processing |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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BIOMOLECULAR NETWORKS; CONTENTS; PREFACE; ACKNOWLEDGMENTS; LIST OF ILLUSTRATIONS; ACRONYMS; 1 Introduction; 1.1 Basic Concepts in Molecular Biology; 1.1.1 Genomes, Genes, and DNA Replication Process; 1.1.2 Transcription Process for RNA Synthesis; 1.1.3 Translation Process for Protein Synthesis; 1.2 Biomolecular Networks in Cells; 1.3 Network Systems Biology; 1.4 About This Book; I GENE NETWORKS; 2 Transcription Regulation: Networks and Models; 2.1 Transcription Regulation and Gene Expression; 2.1.1 Transcription and Gene Regulation; 2.1.2 Microarray Experiments and Databases |
2.1.3 ChIP-Chip Technology and Transcription Factor Databases2.2 Networks in Transcription Regulation; 2.3 Nonlinear Models Based on Biochemical Reactions; 2.4 Integrated Models for Regulatory Networks; 2.5 Summary; 3 Reconstruction of Gene Regulatory Networks; 3.1 Mathematical Models of Gene Regulatory Network; 3.1.1 Boolean Networks; 3.1.2 Bayesian Networks; 3.1.3 Markov Networks; 3.1.4 Differential Equations; 3.2 Reconstructing Gene Regulatory Networks; 3.2.1 Singular Value Decomposition; 3.2.2 Model-Based Optimization; 3.3 Inferring Gene Networks from Multiple Datasets |
3.3.1 General Solutions and a Particular Solution of Network Structures for Multiple Datasets3.3.2 Decomposition Algorithm; 3.3.3 Numerical Validation; 3.4 Gene Network-Based Drug Target Identification; 3.4.1 Network Identification Methods; 3.4.2 Linear Programming Framework; 3.5 Summary; 4 Inference of Transcriptional Regulatory Networks; 4.1 Predicting TF Binding Sites and Promoters; 4.2 Inference of Transcriptional Interactions; 4.2.1 Differential Equation Methods; 4.2.2 Bayesian Approaches; 4.2.3 Data Mining and Other Methods; 4.3 Identifying Combinatorial Regulations of TFs |
4.4 Inferring Cooperative Regulatory Networks4.4.1 Mathematical Models; 4.4.2 Estimating TF Activity; 4.4.3 Linear Programming Models; 4.4.4 Numerical Validation; 4.5 Prediction of Transcription Factor Activity; 4.5.1 Matrix Factorization; 4.5.2 Nonlinear Models; 4.6 Summary; II PROTEIN INTERACTION NETWORKS; 5 Prediction of Protein-Protein Interactions; 5.1 Experimental Protein-Protein Interactions; 5.2 Prediction of Protein-Protein Interactions; 5.2.1 Association Methods; 5.2.2 Maximum-Likelihood Estimation; 5.2.3 Deterministic Optimization Approaches |
5.3 Protein Interaction Prediction Based on Multidomain Pairs5.3.1 Cooperative Domains, Strongly Cooperative Domains, Superdomains; 5.3.2 Inference of Multidomain Interactions; 5.3.3 Numerical Validation; 5.3.4 Reconstructing Complexes by Multidomain Interactions; 5.4 Domain Interaction Prediction Methods; 5.4.1 Statistical Method; 5.4.2 Domain Pair Exclusion Analysis; 5.4.3 Parsimony Explanation Approaches; 5.4.4 Integrative Approaches; 5.5 Summary; 6 Topological Structure of Biomolecular Networks; 6.1 Statistical Properties of Biomolecular Networks |
6.2 Evolution of Protein Interaction Networks |
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Sommario/riassunto |
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Alternative techniques and tools for analyzing biomolecular networks With the recent rapid advances in molecular biology, high-throughput experimental methods have resulted in enormous amounts of data that can be used to study biomolecular networks in living organisms. With this development has come recognition of the fact that a complicated living organism cannot be fully understood by merely analyzing individual components. Rather, it is the interactions of components or biomolecular networks that are ultimately responsible for an organism's |
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form and function. This book addresses the impor |
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