Nanoinformatics

Garant předmětu:

Lecturer:

Tutor:

Supervisor:

Department of Natural Sciences

Synopsis:

he aim of the Nanoinformatics course is to introduce to students the areae of nanomaterials and nanostructures and data collection in this environment. Follow-up lectures will introduce students to the issue of data representation and information about materials, structures and properties, data sources, more complex forms of representation in the form of ontologies. Further lectures will focus on machine learning methods applicable to data from the nanoworld. At the end, students will get information about the latest trends in nanoinformatics.

Requirements:

Compulsory attendance at seminars, active participation in task solutions, submission of protocols and results with a minimum gain of 25 points (maximum 50), passing examination with a total minimum profit of 25 points (maximum 50). Total score: 50-59 points = E (3), 60-69 points = D (2.5) 70-79 points = C (2), 80-89 points = B (1.5), A = 90-100 points ( 1)

Syllabus of lectures:

1.Introduction to nanoinformatics, context definition, basic terms

2.Data collection in nanomaterial and nanostructure environment, data quality and completeness

3.Representation of materials, structures and properties

4.Data sources, metadata, open databases in nanoworld

5.Ontologies in general, ontologies of nanoparticles, eNanoMapper ontologies, NanoDatabank ontologies

6.Statistical modeling, descriptors

7.Unsupervised machine learning methods for similarity analysis, profiling and grouping (PCA, cluster analysis, selforganizing maps)

8.Supervised machine learning methods for adding missing data (quantitative structure activity relationshis, trend analysis, read-across)

9.Modeling properties and interactions of nanomaterials

10.Relation to nanobioinformatics and nanotoxikology. Perspectives

Syllabus of tutorials:

Topics of seminars and computer exercise will be adjusted according to current trends and will follow content of lectures.

The students will solve independent tasks using open source and open access sources in the area of nanoinformatics, e.g. eNanoMapper (https://data.enanomapper.net/, http://www.enanomapper.net/nsc-modelling-tools, http://www.jaqpot.org/), for example:

Data selection, model training and properties prediction (Experiment 1)

Validation of an existing model using selected methods (Experiment 2)

1. – 2. Introduction to eNanoMapper tools and others, task principle, search for suitable literature to the topic

3. discussion on literature and development of experimental protocol

4. - 6. experiment realization and data processing (Experiment 1)

7. – 8. experiment realization and data processing (Experiment 2)

9. task evaluation and result presentation

10. final assessment

Study Objective:

Study materials:

Tanaka, Isao (Ed.): Nanoinformatics. Springer, 2018, Open Access

Mark D Hoover, Nathan A Baker, Frederick Klaessig, Stacey Harper, Juli Klemm, Victor Maojo, William Andrew, Nanoinformatics: Principles and Practice, Computers, 2018

EU US Roadmap Nanoinformatics 2030 (dostupné z https://www.nanosafetycluster.eu/outputs/eu-us-roadmap-nanoinformatics-2030/)

Tutoriály k nástrojům eNanoMapper: http://www.enanomapper.net/enm-tutorials

Vybrané publikace z elektronické knihovny projektu eNanoMapper: http://www.enanomapper.net/library

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Nanotechnology (compulsory course)