Data analysis and navigation in high-dimensional chemical and biological spaces

The goal of this master thesis is to develop and validate a visual data-mining approach suitable for the screening of chemicals in the context of REACH [Registration, Evaluation, Authorization and Restriction of Chemicals]. The proposed approach will facilitate the development and validation of non-testing methods via the exploration of environmental endpoints and their relationship with the chemical structure and physicochemical properties of chemicals. The use of an interactive chemical space data exploration tool using 3D visualization and navigation will enrich the information available with additional variables like size, texture and color of the objects of the scene (compounds). The features that distinguish this approach and make it unique are (i) the integration of multiple data sources allowing the recovery in real time of complementary information of the studied compounds, (ii) the integration of several algorithms for the data analysis (dimensional reduction, generation of composite variables and clustering) and (iii) direct user interaction with the data through the virtual navigation mechanism. All this is achieved without the need for specialized hardware or the use of specific devices and high-cost virtual reality and mixed reality

Data analysis and navigation in high-dimensional chemical and biological spaces

The goal of this master thesis is to develop and validate a visual data-mining approach suitable for the screening of chemicals in the context of REACH [Registration, Evaluation, Authorization and Restriction of Chemicals]. The proposed approach will facilitate the development and validation of non-testing methods via the exploration of environmental endpoints and their relationship with the chemical structure and physicochemical properties of chemicals. The use of an interactive chemical space data exploration tool using 3D visualization and navigation will enrich the information available with additional variables like size, texture and color of the objects of the scene (compounds). The features that distinguish this approach and make it unique are (i) the integration of multiple data sources allowing the recovery in real time of complementary information of the studied compounds, (ii) the integration of several algorithms for the data analysis (dimensional reduction, generation of composite variables and clustering) and (iii) direct user interaction with the data through the virtual navigation mechanism. All this is achieved without the need for specialized hardware or the use of specific devices and high-cost virtual reality and mixed reality

Data analysis and navigation in high-dimensional chemical and biological spaces

The goal of this master thesis is to develop and validate a visual data-mining approach suitable for the screening of chemicals in the context of REACH [Registration, Evaluation, Authorization and Restriction of Chemicals]. The proposed approach will facilitate the development and validation of non-testing methods via the exploration of environmental endpoints and their relationship with the chemical structure and physicochemical properties of chemicals. The use of an interactive chemical space data exploration tool using 3D visualization and navigation will enrich the information available with additional variables like size, texture and color of the objects of the scene (compounds). The features that distinguish this approach and make it unique are (i) the integration of multiple data sources allowing the recovery in real time of complementary information of the studied compounds, (ii) the integration of several algorithms for the data analysis (dimensional reduction, generation of composite variables and clustering) and (iii) direct user interaction with the data through the virtual navigation mechanism. All this is achieved without the need for specialized hardware or the use of specific devices and high-cost virtual reality and mixed reality