Ateneo - UPO

Review of the basics of genetics and genomics. Genome structure, DNA replication, flow of genetic information. DNA polymorphisms and mutations, PCR and sequencing techniques: Sanger and Next Generation Sequencing. Applications of Next Generation sequencing: whole exome sequencing, whole genome sequencing and panel analysis (target resequencing). Analysis pipeline of a genomic sequencing run: alignment, variant calling, annotation. Genotyping techniques for known DNA polymorphisms. Genotyping platforms. GWAS studies: techniques, analysis methods. Transcriptomics techniques. Epigenetics and methylation analysis

Knowledge and understanding: - basic notions of descriptive statistics and data presentation in the biostatistic field - logic of statistical inference (frequentist approach, sampling distribution, confidence interval and hypothesis tests). - epidemiological knowledge for the design of an epidemiological study - knowledge to understand and measure the phenomena of health and disease. Ability to apply knowledge and understanding: - ability to solve simple statistical problems using adequate analytical tools. - ability to design a statistical analysis to address an epidemiological problem. - ability to recognize and evaluate appropriate study designs to anserwquestions related to the causality of diseases, assessing possible errors, strengths and weaknesses based on the research question. - ability to use statistical software for statistical and epidemiological analysis purposes Autonomy of judgement: -to be able to define the entire scientific reasoning from the research question to the formulation of the hypothesis - to be able to express epidemiological judgments and evaluations starting from biological data. - to acquire the tools to critically evaluate the results of a statistical analysis and epidemiological literature. Communication skills: - ability of arguing the principles of statistical inference and the reasons for choosing a specific statistical test. - ability of explanation of the limitations and advantages of epidemiological study designs and their fields of application. - ability of description of the stages of planning a scientific research, from the conception to the publication of the results Learning ability: -Gaining of ability to understand the differences between research and scientific research and specifically, the characteristics of epidemiological research from the perspective of evidence based practice (EBP).

1) What is medical research? 2) Why Evidence-Based Medicine? 3) Methodological problems of effectiveness evaluation 4) Conflict of interest and the role of industry 5) Studies for the evaluation of efficacy 6) Dissemination tools 7) Systematic literature reviews (vs narrative reviews) 8) Literature search 9) Data extraction from scientific documents

Haynes, Straus, Glasziou, Richardson. Evidence-based medicine: Come praticare e insegnare la medicina basata sulle prove di efficacia. Il Pensiero Scientifico Editore. Materials shared in DIR Suggested textbook: Evidence-based medicine. Come praticare e insegnare la medicina basata sulle prove di efficacia di Sharon E. Strauss, Walter Scott, e al. Il Pensiero Scientifico

Knowledge and understanding: the aim of the course is to provide the student with theoretical and applicative knowledge on the main omics sciences, in particular on genomic and transcriptomic analysis. Applying knowledge and understanding: ability to interpret genomic and transcriptomic data in the field of diagnostics and research. Autonomy of judgment: autonomy of judgment in critically evaluating the experimental results, with particular attention to data obtained from DNA-sequencing, RNA-sequencing and GWAS. Ability to critically interpret scientific articles in the field of omics sciences. Communication skills: improvement of the disciplinary lexicon in the field of genetics, genomics and transcriptomics. Ability to report on the topics presented during the course with an appropriate scientific language. Learning skills: acquisition of the ability to critically deepen and autonomously update the skills acquired, by reading texts and scientific articles. Ability to use the didactic material for a critical and reasoned study.

Knowledge: - knowledge of the principles of descriptive medical statistics and of the statistical terminology adopted in the scientific field in the description of populations and samples. - knowledge of the probabilistic and inferential bases and of the methodological elements useful for the interpretation of the results of an epidemiological study. - knowledge of the epidemiological relationship and its relationship with causality. -knowledge of the main tools and methods to quantify the relationship between exposure and health outcomes. - knowledge of the main designs of epidemiological studies and the measures of occurrence and association appropriate to the data and context. Competences and Skills: - correct and efficient selection of a statistical sample - choice of valid and reliable tools to measure variables and appropriate analysis techniques according to the hypothesis. -recognition of an epidemiological relationship in the components that determine it and the ability to reason on its causality -identification of the design of an epidemiological study and evaluation of the possible advantages and disadvantages - interpretation of the results of quantitative methods for measuring health problems and the associations between risk factors and diseases. -management of statistical analyzes in R / Stata relating to the main methods used in epidemiology - reading of a scientific article, understanding the methods and learning how to critically evaluate the results

At the end of the course the students will be able, under the supervision of a content expert, to feed an artificial intelligence project related to the treatment or prevention of diseases, with efficacy data. In particular they will be able to: - search for useful reports - select the relevant and best quality ones - identify and extract the necessary data

Basic knowledge of genetics and molecular biology

Teaching methods Lectures, classroom exercises, analysis of materials individually and in groups, individual or group exercises

Students with physical disabilities, Learning Disabilities or Special Education Needs can request specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse e agli Studenti, consulting the University webpage: https://www.uniupo.it/en/services/services- students-physical-or-learning-disabilities Students with disabilities, learning disabilities or special education needs, once they have contacted the University Staff, can refer to the tutor in charge of the course to define the examination modalities, concerning academic aspects.

Oral examination

one of the subjects will include Research, reading and extraction of useful data to feed an AI project from scientific documents

Review of the basics of genetics and genomics. Genome structure, DNA replication, flow of genetic information. DNA polymorphisms and mutations, PCR and sequencing techniques: Sanger and Next Generation Sequencing. Applications of Next Generation sequencing: whole exome sequencing, whole genome sequencing and panel analysis (target resequencing). Analysis pipeline of a genomic sequencing run: alignment, variant calling, annotation. Genotyping techniques for known DNA polymorphisms. Genotyping platforms. GWAS studies: techniques, analysis methods. Transcriptomics techniques. Epigenetics and methylation analysis

Knowledge: - knowledge of the principles of descriptive medical statistics and of the statistical terminology adopted in the scientific field in the description of populations and samples. - knowledge of the probabilistic and inferential bases and of the methodological elements useful for the interpretation of the results of an epidemiological study. - knowledge of the epidemiological relationship and its relationship with causality. -knowledge of the main tools and methods to quantify the relationship between exposure and health outcomes. - knowledge of the main designs of epidemiological studies and the measures of occurrence and association appropriate to the data and context. Competences and Skills: - correct and efficient selection of a statistical sample - choice of valid and reliable tools to measure variables and appropriate analysis techniques according to the hypothesis. -recognition of an epidemiological relationship in the components that determine it and the ability to reason on its causality -identification of the design of an epidemiological study and evaluation of the possible advantages and disadvantages - interpretation of the results of quantitative methods for measuring health problems and the associations between risk factors and diseases. -management of statistical analyzes in R / Stata relating to the main methods used in epidemiology - reading of a scientific article, understanding the methods and learning how to critically evaluate the results

1) What is research? Establish and explain causal relationships between phenomena a. etiological research b. search of the mechanisms of the natural phenomena c. search for efficacy and effectiveness 2) Why Evidence-Based Medicine? 3) Methodological problems of effectiveness evaluation 4) Conflict of interest and the role of industry 5) Studies for the evaluation of efficacy a. primary studies b. secondary studies 6) Dissemination tools a. Guidelines (Grade) b. point of care services (uptodate) 7) Systematic literature reviews (vs narrative reviews) a. Cochrane 8) Literature search a. Medline 9) Data extraction from scientific documents a. identify useful indicators for AI in scientific reports b. extract useful data from scientific reports to feed AI processes c. target disease or condition d. evaluation intervention e. type of study (and validity) f. measure of association g. measures of statistical stability

KNOWLEDGE: during the course the student will learn the basics of the methods employed in genomics and transcriptomics, and acquired the ability to understand and interpret this type of data with the ultimate aim of exploiting its applications in the medical field, both for research and diagnostics purpose. The students will deepen the techniques of Next Generation Sequencing and their applications in genomics and transcriptomics, and will learn the statistical and bio-informatic analysis of data of Next Generation Sequencing and of Genome-Wide Association Studies. COMPETENCES AND SKILLS: ability to interpret genomic and transcriptomic data in the field of diagnostics and research. Ability to critically interpret scientific articles in the field of omics sciences.

Understanding of the language of EBM; Development of skills and abilities useful for actively participating in machine learning projects that require the identification of effective treatments and preventive interventions; ability to interact with healthcare professionals on such projects