Learning outcomes

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The Erasmus Mundus master degree ChEMoinformatics+ covers all fundamental and applicative aspects of Chemoinformatics. The topics addressed below are considered as the common core present in all tracks:


  • Computer coding of chemical structures (1D, 2D and 3D).
  • Molecules as objects of a chemical space.
  • Measures of structures similarity and diversity among molecules.
  • Chemical libraries, databases and data sources.
  • Chemical libraries analysis: diversity-based, focused on an application, comparison and novelty detection.
  • Molecular descriptors (molecular fragments, fingerprints, topological indices, physical-chemical properties, molecular surfaces and energies, pharmacophores).
  • Hansch and Free-Wilson approaches.
  • Data preprocessing (filtering, standardization of chemical structures, normalization, relevant descriptors selection).
  • Building and validating statistical models (multi-factorial analysis, classification and regression).
  • 3D QSAR (comparative molecular field analysis).
  • Drug Design: chemical libraries of biological interests. Pharmacodynamics. Pharmacokinetics. ADME. Toxicity. Environmental fate.
  • Protein ligand docking and scoring functions.
  • Virtual screening.
  • Profiling of chemical libraries.
  • Structural determination and modelling of macromolecules.
  • Interactions of macromolecules with small molecular weight chemical entities. Biological environment.

Quantum Chemistry

  • Conventional quantum chemical methods (based either on the explicit calculation of the electronic wavefunction or on the electron density).
  • Physical motivations of quantum chemistry calculation methods.
  • Domain of applicability of quantum chemical models.
  • Introduction of main software packages for quantum calculations.

Molecular Modelling

  • Theoretical basics of molecular modelling.
  • Molecular mechanics and molecular dynamics.
  • Force fields and empirical potential energy functions.
  • Molecular modelling as a tool in chemical research.
  • Molecular recognition. Intra- and supra-molecular interactions.
  • Emerging properties at macroscopic scales.
  • Thermodynamics ensembles.
  • Solvation hydrophilic and hydrophobic.
  • Conformational analysis and empirical representations.
  • Practical use of modelling.
  • Rational choice of methods and evaluation of the reliability of results in molecular modelling
  • Comparison to experimental observations.

The EMJM will also cover additional topics that are essential for the technical implementation of Chemoinformatics solutions:

  • Software programming procedural languages (Fortran, C), object oriented (Java, Object Pascal) & functional programming (Maple, Matlab), scripting (bash, Perl, Python), workflow languages (Pipeline Pilot, KNIME)
  • Software engineering compilation & libraries, collaborative development (Git, Subversion), integrative development environment (Eclipse), debugging (GDB, GProf), multi-platform development, Parallel/GPU/cloud computing
  • Databases relational databases. Query languages (SQL). Non-relation databases (NoSQL). Main database management systems (MySQL/MariaDB, PostgreSQL)
  • Web services HTML/CSS (HTML 5), CMS (Spip, Typo3, WordPress), web server (Apache), CGI development, REST and JavaScript.
  • Data mining and artificial intelligence support vector machines, classification and regression trees, neural networks, generative and approaches, bootstrapping, cross-validation, clustering. Tuning method parameters. Ensemble modelling. Active learning. Multi-task learning. Semisupervised learning and transduction. Recommender systems. Generative models and adversarial learning. Autoencoders.
Learning OutcomesLecture
create, manage and use databases on chemistry subjects. Methodology (S1, Strasbourg), Banche dati ed elementi di chemoinformatica (S2, Milan), Numerical methods in chemistry (S1, Ljubljana), Databases (S2, Lisbon), Управління базами даних (S2, Kiyv), Databases (S2, Bar-Ilan)
know and use the most important databases in Chemistry for knowledge or for commercial use.
be able to extract, interpret and analyse chemical information. Chemoinformatics 1 (S3, Strasbourg), Cheminformatics 2 (S3, Strasbourg), Chemoinformatics 3 (S3 Strasbourg), Chemoinformatics (S1, Strasbourg), Data Mining (S3, Strasbourg), Data analysis in drug design (S3, Paris)
understand, build and validate qualitative and quantitative chemical structure-activity relationships (QSAR/QSPR).
understand and use machine learning algorithms.
implement technical solutions to manage and exploit big data sources in chemistry.
implement and use artificial intelligence technologies for solving chemical problems.
understand, use and analyse quantum chemistry models. Molecular Modeling (S1, Strasbourg), Simulation, modeling and biomolecules (S2, Milan), Chim Fis A (S1, Milan), Chim Fis B (S2, Milan), Metodi matematici applicati alla chimica (S1, Milan), Modelling of Chemical Systems (S1, Ljubljana), Applied Computational Chemistry (S2, Lisbon), Комп’ютерне моделювання в природничих науках (S2, Kiyv), Computational Chemistry (S2, Bar-Ilan), Molecular Modeling (S2, Bar-Ilan), Molecular dynamics analysis and drug design (S3, Paris), Structural Biology and molecular modeling (S3, Strasbourg), Molecular dynamics simulation (S3, Strasbourg), Advanced Quantum Chemistry (S3, Strasbourg)
understand, use and analyse molecular mechanics models.
understand, use and analyse heuristics to model inter-molecular recognition, such as docking or pharmacophores. Virtual screening application : Structure and ligand -based (S3, Paris), Structure-based drug design (S3, Strasbourg), Супрамолекулярна хімія (S1, Kiyv), Біоінформатика (S2, Kiyv), Комбінаторна хімія та технологія пошуку біологічно активних речовин (S2, Kiyv), Medicinal Chemistry (S2, Milan), Medicinal Chemistry (S1, Lisbon), Комбінаторна хімія та технологія пошуку біологічно активних речовин (S2, Kiyv)
perform a virtual screening of chemical libraries.
understand the basics of medicinal chemistry
understand and solve medicinal chemistry problems
implement chemical design strategies. Methodology (S1, Strasbourg), Metodi fisici avanzati in chimica organica (S1, Milan), Catalysis and Modern Organic Chemistry (S1, Ljubljana), Modern Methods in Organic Synthesis (S1, Ljubljana), Organic Chemistry (S2, Ljubljana), Modern inorganic materials and catalyst (S2, Ljubljana), Asymmetric Organic Chemistry I (S1, Lisbon), Physical Organic Chemistry (S1, Lisbon), Asymmetric Organic Chemistry II (S2, Lisbon), Applied Organic Synthesis (S2, Lisbon), Вибрані розділи неорганічної та органічної хімії (S2, Kiyv), Комбінаторна хімія та технологія пошуку біологічно активних речовин (S2, Kiyv), Organic Synthesis (S1 or S2, Bar-Ilan), Industrial Organic Chemistry (S1, Bar-Ilan)
understand and write computer software using procedural, object and programming workflow paradigms. C Programming (S2, Milan), Numerical methods in chemistry (S1, Ljubljana), Mathematics II (S1, Ljubljana), Introduction to Programming (S1, Lisbon), Вибрані розділи вищої математики та інформаційних технологій (S1, Kiyv), Програмування на мовах C, C++, Java (S1, Kiyv), Веб-технології в хімії (S2, Kiyv), Цифрові технології в науковому експерименті (S2, Kiyv), Internet Technology (S3, Strasbourg), Programming (S2, Bar-Ilan)
develop and publish internet services for chemistry.
present clearly and unambiguously research results, conclusions and rationale underpinning these; orally or by poster presentation to specialist and non-specialist audiences. Communication (S1, Strasbourg), English proficiency (S2, Milan), Water as Hydrogeological, Ecological and Analytical System (S1, Ljubljana), Entrepreneurship (S1, Lisbon), Laboratory Quality Control (S2, Lisbon), Іноземна мова (S1 / S2, Kiyv), Спеціальний семінар науковий (S2, Kiyv), Research project (S2, Bar-Ilan), Internship (S4, Strasbourg)
independently read and critically interpret the scientific literature, including the patent literature.
continue to learn about their field on their own in a largely self-directed manner.
integrate into a new and unfamiliar research environment, be confronted with a new research problem and to independently develop an experimental plan to tackle the problem.
handle complexity and formulate judgements with incomplete or limited information, including reflecting on social and ethical responsibilities linked to the application of their knowledge and judgements.
Innovate and transfer innovation into public and private domain in the European market
Innovate in line with the European regulation on chemicals


Each track of the master complete the curriculum with specialization topics and skills

SpecializationLearning outcomeLecture
In Silico Design of Bioactive Molecules (Strasbourg - Milan - Paris) Model sites of interaction and biotransformations in proteins Structural biology and enzymology (S2); Target modelling (S3)
Understand the basics of medicinal and biophysical chemistry for the design of bioactive molecules Medicinal Chemistry (S2); Structural Biology and enzymology (S2); Simulation, modeling and biomolecules (S2)
Rationalize biomolecular event with therapeutic effects Medicinal Chemistry (S2); Data analysis in drug design (S3)
Chemoinformatics and Physical Chemistry (Milan - Strasbourg) Understand, build and analyze quantum chemistry and molecular mechanics models Chimica Fisica A (S1/S2); Metodi matematici applicati alla chimica (S1/S2); Simulation, modeling and biomolecules (S1/S2)
Use of databases in Chemistry, Implementation of programming workflows and computer simulation of biomolecules; Modelling physico-chemical processes Banche dati ed elementi di chemoinformatica (S1/S2); Programming C (S1/S2); Simulation, modeling and biomolecules (S1/S2)
Theoretical and practical knowledge of methods for the structural characterization of compounds; Critically assess the experimental results of physical chemistry experiments Chimica Fisica B (S1/S2); Metodi fisici avanzati in chimica organica (S1/S2)
Chemoinformatics for Biophysical & Computational Chemistry (Ljubljana - Strasbourg) Optimize biophysical processes Biophysical chemistry (S1); Physical Chemistry II (Statistical Thermodynamics) (S2)
Model biophysical processes Numerical methods in chemistry (S1); Modelling of Chemical Systems(S1)
Chemoinformatics for Organic Chemistry (Lisbon - Strasbourg) Design innovative organic chemical structures Physical Organic Chemistry (S1); Applied Organic Synthesis (S2)
Design of asymetric chemical libraries Asymmetric Organic Chemistry I (S1); Asymmetric Organic Chemistry II (S2)
Chemoinformatics of chemical reactions (Strasbourg) Rationalize the reactivity of chemical species Механизмы химических реакций (S1); Биоорганическая химия (S1); Современные проблемы органической химии (S1)
Model the reactivity of chemical species Основы компьютерного программирования в приложении к химическим задачам (S1)
Ultra Large Chemical Library Design and Virtual Screening (Kiyv - Strasbourg) Design target oriented chemical libraries Біохімія (S1); Супрамолекулярна хімія (S2); Біоінформатика (S2)
Design ultra-large chemical libraries Комбінаторна хімія та технологія пошуку біологічно активних речовин (S2)
Chemoinformatics and materials informatics (Bar Ilan - Strasbourg) Design innovative new nanomaterials Nanotechnology (S1/S2); Material Sciences (S1/S2); Organometallic Chemistry (S1/S2)
Design innovative new materials for energy production and storage Advanced Analytical Chemistry (S1/S2); Material Sciences (S1/S2); Organometallic Chemistry (S1/S2)