General Info

Learning objectives

The course aims to provide basic concepts of programming in Python and R languages, as well as an introduction to the Linux environment, in which these languages can be used to develop programs for the analysis and management of huge amounts of biological data.
The ability to work in a Linux environment and to develop programs in Python and R is considered, in the scientific community, an indispensable set of knowledge for:
• supporting study and research in the field of biomedical sciences;
• dealing with and manage the analysis of huge amounts of biological data from current "High throughput" experimental platforms;
• acquiring the tools for modeling biological big data.
• acquiring HPC (High-Performance-Computing) computing skills for the analysis of biological problems that cannot be solved on standard computing resources.
EXPECTED LEARNING RESULTS:
KNOWLEDGE AND UNDERSTANDING. At the end of the training activity, the student will be able to apply their knowledge to design and develop pipelines for the analysis of biological big data in Python or R running in a linux computing environment both on a single server node and on a multi-node cluster (HPC) .
ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING. The knowledge acquired by the students will be useful to be able to analyze and manipulate biological big data in order to understand and model the molecular mechanisms contained in the data.
AUTONOMY OF JUDGMENT. Students must be able to critically interpret the results obtained through the development and execution of the programs discussed in class, as well as choose the most suitable programming language to pursue a specific goal.
COMMUNICATION SKILLS. Students must have the ability to transmit the knowledge acquired in a clear and understandable way, for example by associating each developed program with a pseudo-code, and must demonstrate the ability to present programs to external users through detailed documentation.
LEARNING ABILITY. Students must be able to describe the fundamental topics of Programming, in oral form. This ability will be developed through active involvement through oral discussions in the classroom and exercises carried out in the computer room on specific topics related to the course.

• Emanuele SANTINAMI

Learning objectives

The course provides the theoretical bases of proteomics, interatomics and matabolomics as relevant scientific disciplines able to provide useful structural and dynamic information about the proteoma and metaboloma. The course will introduce students to the principles and the experimental approaches, and the learning objectives will be achieved by presenting students with the state of innovation in the specific field with a substantial presence in the laboratories. Particular attention will be given to the study of mass spectrometry techniques for the identification of proteins, metabolites and alterations of protein expression, thus enabling them to shed light on the biological complexity of a tissue in order to differentiate / identify a pathological state from the physiological one.
LEARNING OUTCOMES
1) Knowledge and understanding. The student will develop the knowledge of the principles of proteomics and metabolomics. Indispensable for experimental analysis and interpretation of results in biochemical and molecular biological disciplines.
2) Applying knowledge and understanding. The student will also be introduced to the knowledge of the major classes of small biological molecules and metabolites and will learn the basic metabolic pathways through which these molecules are degraded and synthesized. He will be familiar with the main separation methods (2Dgel, HPLC), will use high performance instrumentation (such as MALDI TOF / TOF, ESI-TRAP, ORBITRAP MS) for the identification of proteins and metabolites and will deal with bioinformatic tools for data visualization and interpretation.
3) Making judgments. Students will be able to independently carry out observations and experiments in the field of Proteomics or metabolomics. They will also have critical thinking and evaluation skills to rationalize them in an interpretative model.
4) Communicative skills. Students will be able to work in groups and communicate clearly their knowledge or the results of their research.
5) Learning skills. Students will need to learn autonomously by using advanced texts in Italian and English. English texts will be provided during the year. Students will also be able to perform bibliographic research even at advanced level, selecting relevant topics of proteomics and metabolomics.

• Anna Maria TIMPERIO

Learning objectives

Specifically, it is intended to provide students with specific skills for the manipulation and analysis of nucleic acids and proteins (mutagenesis and genome editing techniques), for the analysis of gene expression levels (qPCR, microarrays, differential transcriptomic) and gene expression regulation (study of epigenetic modifications and protein-DNA interactions), for the study of transduction signal pathways by protein-protein interaction analysis. The advances in the field of the sequencing of whole genomes and the application of biomolecular techniques in diagnostic field will be also discussed. Bioinformatics tools will be used for in silico prediction of interaction between biomolecules, or as complementary for the use of the discussed techniques (for input or output analysis). Finally, laboratory practical experiences will be organized to acquire techniques for studying nucleic acids and proteins.
EXPECTED LEARNING OUTCOMES:
1) Knowledge and understanding: To know the basic techniques used in the field of fundamental and applied research. They will have an in-depth knowledge of molecular and advanced techniques and the related bioinformatics tools to support them; they will know the importance of statistical validation of the results of an experiment and of the controls that make an experiment scientifically reliable.
2) Applying knowledge and understanding: At the end of the course the students will be able to use the acquired knowledge to evaluate and interpret the results of an experiment, identify its strengths and weaknesses and optimize it by evaluating the possible impact of variations in key experimental parameters; orient themselves among the main qualitative and quantitative methods to select the most suitable ones for studying the biological problem of interest; perform the experiments carried out during the practical part of the course.
3) Making judgements: Students will be able to interpret and discuss the scientific papers presented during the course and be able to design and express new proteins with different characteristics. Students will have to acquire the ability to understand and critically discuss the experimental results obtained in the laboratory and use them as a starting point for planning subsequent experiments.
4) Comunication skills: Students should have the ability to convey the acquired knowledge in a clear and comprehensible manner, even to people who are not in the field, and must demonstrate the ability to present information also with schemes and formulas.
5) Learning skills: Students will have to be able to describe scientific topics related to the course. This skill will be developed through the active involvement of students during class discussions and practical experiences during the hours dedicated to the experimental laboratory.

Learning objectives

The English language course aims to familiarize students with the techniques of writing in the English language which differs from writing in Italian. This course also allows students to produce documents and/or short essays which are relevant for their course of study. The course therefore focuses on two of the four language skills - writing and reading - without forgetting listening and speaking. To achieve these objectives, classes are exclusively taught in English. It is for this reason that the grammatical basis of the language and its phonological aspects are not neglected but analyzed whenever the need arises. The final goal is the achievement of level B2 of the Common European Framework of Reference (CEFR), adopted by the Council of Europe.
KNOWLEDGE AND UNDERSTANDING. The learner is able to know and understand the topics set out relating to the syntax and vocabulary of the English language for level B2, which concern the structures to be used for detailed descriptions and presentations on topics related to his/her field of interest, both personal and academic. He/she is also able to understand the salient points as well as the details of topics covering a wide range of topics within his/her field of interest.
ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING. The learner is able to communicate clearly and methodically, emphasising salient points and relevant elements to justify their speech. He/she is able to use linguistic structures in a spontaneous and natural way to respond to any objections from their interlocutors.
AUTONOMY OF JUDGMENT. The learner is able to independently deepen, by means of information and communication technologies, what he/she has learnt with regard to particular aspects of language use concerning not only their precise field of study, but a wide range of topics.
COMMUNICATION SKILLS. The learner has acquired the ability to produce argumentative texts in a methodical manner, emphasising important points and relevant details that support their argumentation. He/she can evaluate different ideas and can propose solutions to different problems.
LEARNING ABILITY. The learner is able to manage their own learning, to search for examples and materials that support their ideas and arguments.

• Felicetta RIPA

Learning objectives

The course aims to train students in various sectors of Bioinformatics, with particular attention to the knowledge of innovative tools used to support research in the biological field.
In detail, the training objectives concern:
1) Basic knowledge of biological databases
2) Query of biological databases in a programmatic way (examples of programmatic query of the various NCBI databases, https://www.ncbi.nlm.nih.gov/guide/all/, through the use of API- application programming interface)
3) Pairwise alignment algorithms of nucleotide and amino acid sequences
4) Substitution matrices
5) Heuristic algorithms for local alignment of sequences against sequence databases
6) Multiple sequence alignment algorithms
7) Methods for the construction of phylogenetic trees
8) Algorithms for the prediction of RNA structure
9) Algorithms for the prediction of secondary structure of proteins
10) Methods for the comparison between protein structures
11) Classical algorithms for the prediction of protein folding
12) Algorithms based on machine learning for the prediction of protein folding

LEARNING OUTCOMES:
KNOWLEDGE AND UNDERSTANDING. Students must show that they have learned bioinformatics topics included in the course, namely: acquisition of the basic principles of bioinformatics; how biological databases are designed, managed and populated; how sequence similarity searches and alignments of single or multiple sequences are performed; how evolutionary analysis of sequence data is performed through multiple alignments and construction of phylogenetic trees; how secondary and tertiary protein structure predictions are made.
ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING. Students should have an understanding of the computational approaches discussed in class and be able to apply them to specific biological problems.
AUTONOMY OF JUDGMENT. Students must be able to critically interpret the results obtained through the bioinformatics tools discussed in class, as well as choose the most suitable ones to reach a specific goal.
COMMUNICATION SKILLS. Students must have the ability to transmit the knowledge acquired in a clear and understandable way, even to non-competent people, and must demonstrate the ability to present the acquired information.
LEARNING ABILITY. Students should be able to describe the various topics of Bioinformatics, in oral form. This ability will be developed through active involvement in oral discussions in the classroom and exercises carried out in the computer room on specific topics related to the course.

• TIZIANA CASTRIGNANO

Learning objectives

The course is aimed at providing students with theoretical and practical knowledge on the main methodologies used in a biology laboratory (centrifugation, spectrophotometric and spectrofluorimetric methods, microscopy, histochemical and immunohistochemical analyses). The course will also allow students to know the main classes of environmental contaminants in terms of chemical/physical characteristics, distribution in environmental matrices, bioaccumulation, bioavailability and biomagnification; to know and understand the physiological mechanisms underlying the biotransformation of the main environmental contaminants. Students will learn to use the main toxicity tests for the characterization of the quality of different environmental matrices, including soils, sediments and waters. They will also learn the meaning of the use of bioindicator organisms and biomarkers. Finally, the student will be able to prepare and manage a dataset for the analysis of experimental data.

EXPECTED LEARNING RESULTS
1. KNOWLEDGE AND UNDERSTANDING. The student will therefore be able to apply the main toxicity tests using the most appropriate test species and interpret the results obtained from the different end-points analyzed. Students will be able to apply the knowledge acquired through the use of appropriate ecological risk analysis models, which provide for the weighted integration of chemical and biological parameters.
2. ABILITY TO APPLIED KNOWLEDGE AND UNDERSTANDING. At the end of the course, the student will be able to use the main equipment provided in a biology laboratory and will be able to perform basic biological analyses for biochemical, cytological, and histological applications.
3. AUTONOMY OF JUDGMENT. Acquisition of autonomy of judgment in reference to the evaluation and interpretation of experimental data produced in the laboratory and reported in scientific articles
4. COMMUNICATION SKILLS. Acquisition of appropriate scientific terminology. Acquisition of adequate instrumental skills for the production of scientific data with reference to the processing and presentation of data.
5. ABILITY TO LEARN. Acquisition of adequate skills for the in-depth study of further skills and knowledge, with reference to the consultation of bibliographical material and the drafting of a scientific paper.

• Maria Luisa VANNUCCINI

Learning objectives

The use of molecular and bioinformatic tools has significantly contributed to our understanding of ecological and evolutionary processes underlying the genesis of biodiversity and the fundamental principles of modern conservation biology. The course aims to provide the student with a thorough understanding of these tools and the main ecological and evolutionary issues that can be addressed through their application. The course will also investigate the molecular mechanisms underlying the adaptation of organisms to environmental changes, both current and past, the molecular methods for monitoring the different hierarchical levels of biodiversity, and elements of molecular demography.
EXPECTED LEARNING OUTCOMES
1) Knowledge and understanding. Students who complete this course will be able to solve ecological and evolutionary problems using molecular ecology tools. In general, they will develop the ability to understand the application of the tools of molecular ecology proper for understanding the main eco-evolutionary processes that shape diversity in natural populations.
2) Applying knowledge and understanding. Students who complete this course will be able to apply the knowledge obtained using experimental and bioinformatics tools typical of molecular ecology for solving problems in the ecological and evolutionary fields. In particular, this knowledge will be applied in conservation biology and in invasion biology.
3) Making judgements. Students who complete this course will be able to apply critical reading of scientific literature to formulate informative hypotheses of experimental data.
4) Communication skills. Students will be stimulated to discuss and compare opinions during the course to develop their communication skills. At the end of the course, students will have the ability to communicate the knowledge acquired clearly and understandably.
5) Learning skills. At the end of the course, students will be able to formulate solid scientific questions based on evidence and develop experimental paths by gradually integrating scientific literature and acquired technical knowledge.

• Roberta BISCONTI

Learning objectives

The main educational objective of the Chemistry of Natural Organic Substances consists in providing the student with general concepts, specific knowledge, and adequate examples to classify natural organic substances on the basis of their chemical structure, to evaluate their biosynthetic origin and the corresponding biological properties, also analyzing the most important classes of organic compounds of natural origin produced in the course of secondary metabolism by the animal and plant cells. The training objective will also be achieved thanks to the description and use of examples relating to the application of computational chemistry and bioinformatic techniques in order to predict structure-activity relationships and identify the main pharmacophores present in the molecule. Thanks to this information, the student will be able to recognize the biosynthetic origin and the structural family to which a natural organic substance belongs, and to place it in a general context relating to its possible cellular functions and application in the pharmaceutical, nutraceutical and cosmetic field. Knowledge will also be provided to understand the main and most recent applications of natural organic substances in the bio-nanotechnology sector, with particular attention to renewable and biodegradable materials, bioplastics and bio-inks, and the design of novel biocatalysts and biosensors. The student will possess critical tools to associate the presence of specific structural characteristics in the molecule with the mechanism of action exerted by the substance at the molecular level, highlighting the relationships between structure and activity, so as to be able to predict, in a critical sense, the biological activities associated with a specific molecular architecture.

LEARNING OUTCOMES
• KNOWLEDGE AND UNDERSTANDING. Knowledge of the structural reasons that allow the classification of a natural organic substance. Knowledge of the main biological activities associated with the different families of natural organic substances also involving computational and bioinformatic analyses. Knowledge of the biosynthesis pathways of secondary metabolites in animal and plant cells. Knowledge of the relationships between chemical structure and biological activity. Knowledge of the application of natural organic substances in biotechnology.
• APPLYING KNOWLEDGE AND UNDERSTANDING. In addition to the knowledge acquired through the study of the chemistry of natural organic substances, students will be able to deepen the concepts by reading scientific publications and by the use of dedicated software for the classification of organic substances based on their chemical structure, thus linking the topics covered in the course to experimental research.
• MAKING JUDGMENTS. At the end of the course the student will have acquired the necessary training for a complete autonomy of judgment regarding the possibility of using natural organic substances for the development of service, process, or product in the pharmaceutical, nutraceutical, cosmeceutical, cosmetic, materials science and bio-nanotechnology fields.
• COMMUNICATION SKILLS. Students will be continuously and constantly invited to actively participate in the lesson in order to deepen the subject and to collect proposals for possible solutions in the case of complex scenarios. In this activity, students will be asked to confront each other in order to support their ideas also by making use of bioinformatic tools, such as software dedicated to the 3D representation and nomenclature of chemical structures. The teaching tool is aimed at increasing communication skills and the ability to know how to work and discuss in a group, all aimed at consolidating the concepts acquired.
• LEARNING SKILLS. The learning skills of the students will be assessed during the course by discussing the contents of scientific publications that will allow them to follow the state of art, highlighting the ability of restitution and of problem solving of the student.

• Raffaele SALADINO