1.

Record Nr.

UNISA990005754980203316

Autore

DOR, Joel

Titolo

1: L'  incoscient structuré comme un langage / Joel Dor

Pubbl/distr/stampa

Paris : Denoel, c1985

Descrizione fisica

265 p. ; 23 cm.

Disciplina

150.195

Soggetti

Lacan, Jacques - Psicanalisi

Collocazione

CC 150.195 DOR

Lingua di pubblicazione

Francese

Formato

Materiale a stampa

Livello bibliografico

Monografia

2.

Record Nr.

UNINA9910785785403321

Autore

Diekmann O

Titolo

Mathematical tools for understanding infectious diseases dynamics [[electronic resource] /] / Odo Diekmann, Hans Heesterbeek, and Tom Britton

Pubbl/distr/stampa

Princeton, : Princeton University Press, 2012

ISBN

1-283-57875-1

9786613891204

1-4008-4562-9

Edizione

[Course Book]

Descrizione fisica

1 online resource (517 p.)

Collana

Princeton series in theoretical and computational biology

Classificazione

SCI008000MAT003000MED022090

Altri autori (Persone)

HeesterbeekHans <1960->

BrittonTom

Disciplina

614.4

Soggetti

Epidemiology - Mathematical models

Communicable diseases - Mathematical models

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.



Nota di contenuto

Front matter -- Contents -- Preface -- Part I. The bare bones: Basic issues in the simplest context -- Part II. Structured populations -- Part III. Case studies on inference -- Part IV. Elaborations -- Bibliography -- Index

Sommario/riassunto

Mathematical modeling is critical to our understanding of how infectious diseases spread at the individual and population levels. This book gives readers the necessary skills to correctly formulate and analyze mathematical models in infectious disease epidemiology, and is the first treatment of the subject to integrate deterministic and stochastic models and methods. Mathematical Tools for Understanding Infectious Disease Dynamics fully explains how to translate biological assumptions into mathematics to construct useful and consistent models, and how to use the biological interpretation and mathematical reasoning to analyze these models. It shows how to relate models to data through statistical inference, and how to gain important insights into infectious disease dynamics by translating mathematical results back to biology. This comprehensive and accessible book also features numerous detailed exercises throughout; full elaborations to all exercises are provided. Covers the latest research in mathematical modeling of infectious disease epidemiology Integrates deterministic and stochastic approaches Teaches skills in model construction, analysis, inference, and interpretation Features numerous exercises and their detailed elaborations Motivated by real-world applications throughout



3.

Record Nr.

UNINA9910557545103321

Autore

Willaert Ronnie G

Titolo

Yeast Biotechnology 3.0

Pubbl/distr/stampa

Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020

Descrizione fisica

1 online resource (240 p.)

Soggetti

Technology: general issues

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Sommario/riassunto

Yeasts are truly fascinating microorganisms. Due to their diverse and dynamic activities, they have been used for the production of many interesting products, such as beer, wine, bread, biofuels and biopharmaceuticals. Saccharomyces cerevisiae (bakers' yeast) is the yeast species that is surely the most exploited by man. Saccharomyces is a top choice organism for industrial applications, although its use for producing beer dates back to at least the 6th millennium BC. Bakers' yeast has been a cornerstone of modern biotechnology, enabling the development of efficient production processes for antibiotics, biopharmaceuticals, technical enzymes, and ethanol and biofuels. Today, diverse yeast species are explored for industrial applications, such as e.g. Saccharomyces species, Pichia pastoris and other Pichia species, Kluyveromyces marxianus, Hansenula polymorpha, Yarrowia lipolytica, Candida species, Phaffia rhodozyma, wild yeasts for beer brewing, etc. This Special Issue is focused on recent developments of yeast biotechnology with topics including recent techniques for characterizing yeast and their physiology (including omics and nanobiotechnology techniques), methods to adapt industrial strains (including metabolic, synthetic and evolutionary engineering) and the use of yeasts as microbial cell factories to produce biopharmaceuticals, enzymes, alcohols, organic acids, flavours and fine chemicals, and advances in yeast fermentation technology and industrial fermentation processes.