Tecnologia e innovazione al servizio della salute dell'uomo e della sicurezza dell'ambiente
SILVANA CASTANO , responsabile dell'insegnamento
Corso di laurea in SAFETY ASSESSMENT OF XENOBIOTICS AND BIOTECHNOLOGICAL PRODUCTS (Classe LM9) For students enrolled from 2015/16 academic year  Laurea Magistrale  2018/2019
Insegnamento obbligatorio  Sì 

Anno di corso  2s 
Periodo di svolgimento  primo semestre 
Settori scientifico disciplinari 

Crediti (CFU) obbligatori  6 
Crediti (CFU) facoltativi   
Introduction to databases. Information systems, information and data. Database and Database
Management System (DBMS). Data models. Schemas and instances. Abstraction levels in DBMSs.
Database languages and users.
Relational databases. The relational model. Relations and tables. Relations with attributes. Relations
and databases. Incomplete information and null values. Integrity constraints. Definitions and properties
of keys. Primary key and foreign key constraints.
Query languages for relational databases. Relational algebra. Union, intersection, difference,
selection, projection, join. Queries in relational algebra.
Query languages for relational databases. SQL. The declarative nature of SQL. Simple SQL
queries. Aggregate queries. Group by queries. Set queries. Nested queries.
Conceptual database modeling. Data conceptualization and aggregation mechanisms. The Entity
relationship model. Basic constructs of the model: entity, relationship, attribute. Generalization
hierarchies. Identifiers. Simple mapping rules from ER to relational tables.
Biological databases. Direct access to relational biological databases. The Ensembl database and its
structure (db schema). Use of SQL to query biological data. Application to the Ensembl database for
the extraction of genomic annotations.
 P. Atzeni, S. Ceri, S. Paraboschi, R. Torlone, Database Systems – Concepts, Languages and Architectures  McGraw Hill, Available online at http://dbbook.dia.uniroma3.it/
Chapters: 1(whole), 2 (whole), 3(until §3.1.6 included)4 (only § 4.2. and related subparagraphs)5 (only § 5.2. and related subparagraphs)
 Teaching stuff (lecture slides) downloadable from the course web site (only for signedup students).
Main criteria for the evaluation of scientific studies. Definitions: descriptive statistics, inferential statistics. Collecting data sets: populations and samples. Frequency tables, line graphs, bar graphs, frequency polygons, relative frequency graphs, pie charts, grouped data and histograms, the problem of the bin size selection. Sample mean, geometric sample mean, sample mode, sample deviations, sample absolute deviations, mean absolute deviation, sample variance, alternative expression for the sample variance, sample standard deviation. Accuracy and precision.
Sets of paired data, scatter diagram, best fitting line 'by eye'. Least squares regression line (vertical offsets, horizontal offsets): slope (linear regression coefficient), intercept, centre of the distribution. Qualitative and quantitative evaluation of linear regression. The correlation coefficient: definition, sign convention, covariance, range, alternative expressions. The coefficient of determination: definition, range, significance (for linear regression), geometric interpretation (proportion of variation explained by the linear regression). Interpreting correlation: Evans' guide (1996). Hints of nonlinear regression (exponential, logarithmic, trigonometric, power,etc.). Odd ratio.
Necessity and sufficiency in logic. 'Correlation does not imply causation'. Spurious relationships. True positives, true negatives, false positives, false negatives. Graphical representation. Sensitivity, specificity.
Probability. Experiment and outcomes, sample space, events, union, intersection, Venn diagram, null event, disjoint events, complement event, extension to more then two events. Properties of probability (for disjoint and nondisjoint events), experiments having equally likely outcomes, conditional probability and independence, the Bayes’ theorem, the Monty Hall problem.
Discrete random variables: probability distribution, expected value, properties of the expected value, variance, alternative expression for the variance, properties of the variance, standard deviation. Continuous random variables, probability density function. Normal continuous random variables, normal probability density function (Gaussian distribution). Standard normal continuous random variables, standard normal probability density function. Properties of the density functions, approximation rule, standardizing normally distributed random variables.
Population and sample: population mean and population variance, sample mean, expected value of the sample mean, variance of the sample mean, standard deviation of the sample mean, central limit theorem. Applications to measurement errors and to biological data sets.
Confidence intervals. Pvalue, null hypothesis, hypothesis testing and statistical significance, statistical power, sample size issues, dependence of the statistical power on the sample size, rules for the determination of the sample size.
Types of epidemiological studies. Observational studies: ecological, crosssectional, casecontrol, cohort. Experimental studies: randomized controlled trials, field trials, community trials. Potential errors in epidemiological studies.
 Introductory Statistics  Sheldon M.Ross  Elsevier AP (Third Edition)
 Basic epidemiology  R. Bonita, R. Beaglehole, T. Kjellström  World Health Organization (2nd edition)
Esame in un'unica volta o suddiviso in parti  unico 

Modalità di accertamento conoscenze  Esame 
Giudizio  voto verbalizzato in trentesimi 
Prerequisiti e modalità di esame Regarding Informatics and Databases:
no prerequisites. The exam is written (approximately 1 hour and 30 minutes), it covers all the topics presented during lectures, and it will consist in multiplechoice questions and exercises. The exam aims to verify that the course objectives have been achieved, namely, that students have learned the basic concepts related to the relational data model and to the relational query languages, also with application to biological databases.
Regarding Statistics applied to epidemiology:
basic concepts of mathematics and logic are needed for this module. The examination consists of a written test (approximately 1 hour and 30 minutes) including questions and problems related to all the topics developed during the course. Students are allowed to consult their own material during the examination and the use of a portable calculator is recommended (any device connected to the internet is prohibited).
obbligatorio
ObiettiviThe course is aimed at providing the basic concepts of databases, with focus on relational data modeling and query languages. To develop a deeper understanding of the topics covered in the course, relational data model and relational query languages will be derived and presented along with many worked examples related to biological databases.
Settori e relativi crediti
Lectures: 24 ore
obbligatorio
ObiettiviThe course is aimed at providing the basic concepts of statistics needed in epidemiology. To develop a deeper understanding of the topics covered in the course, the equations of the statistical methods will be derived and presented along with many worked examples related to epidemiology. The main types of epidemiological studies will be presented and discussed. The course provides also some fundamental concepts of logics necessary to assess if the presented techniques are properly applied within epidemiological studies and to recognize possible data manipulation.
Settori e relativi crediti
Lectures: 24 ore
Docente  Orario di ricevimento  Luogo di ricevimento 

SILVANA CASTANO , responsabile dell'insegnamento  Ricevimento su appuntamento tramite email  
ALESSANDRO DI DOMIZIO  Su appuntamento  Dipartimento di Scienze Farmacologiche e Biomolecolari, Via Giuseppe Balzaretti, 9  20133 Milano 