NEXTCHROM: Virtual advanced chromatography for an integral management of analytical and molecular data
The NEXTCHROM project deals with the development of new computational tools for chemical laboratories, including two main lines: the computational analysis and management of chemical data, and the multi-objective optimization of the sample separation process by means of two-dimensions liquid chromatography (2D-LC) using Artificial Intelligence techniques.
This project is led by Mestrelab Research, a technological leader in the development of software for analytical chemistry. It also involves the CiTIUS, which provides its experience in the areas of Artificial Intelligence, Information Management and Cloud Computing, as well as the research group CHROMCHEM, whose members are expert in the development and optimization of chromatographic separations.
The main application fields of this project will play a key role in every process including the analysis or identification of chemical structures. Main application fields of the project are related with the analysis and identification of chemical structures, such as environment, health, food, toxicology, forensics, industrial quality, etc.
Objectives
The goals of the project are the following:
- To develop tools for the efficient management of large amount of analitic data and chemical structures. This objective involves the development of representational models, retrieving technologies and cloud solutions.
- To develop a computer simulation system to facilitate the separation of complex samples in chemical chromatography 1d-LC (one column), 2D-LC (two columns) and s2D-LC (two selective columns). The simulation of separations will be mainly addresed through multiobjective optimization schemes based on Articial Intelligence techniques, as Evolutionary Computation.
Project
/research/projects/cromatografia-virtual-avanzada-e-xestion-integral-de-datos-analiticos-e-moleculares
<p>The NEXTCHROM project deals with the development of new computational tools for chemical laboratories, including two main lines: the computational analysis and management of chemical data, and the multi-objective optimization of the sample separation process by means of two-dimensions liquid chromatography (2D-LC) using Artificial Intelligence techniques.<br />This project is led by Mestrelab Research, a technological leader in the development of software for analytical chemistry. It also involves the CiTIUS, which provides its experience in the areas of Artificial Intelligence, Information Management and Cloud Computing, as well as the research group CHROMCHEM, whose members are expert in the development and optimization of chromatographic separations.<br />The main application fields of this project will play a key role in every process including the analysis or identification of chemical structures. Main application fields of the project are related with the analysis and identification of chemical structures, such as environment, health, food, toxicology, forensics, industrial quality, etc.</p><p>The goals of the project are the following:</p><ul><li>To develop tools for the efficient management of large amount of analitic data and chemical structures. This objective involves the development of representational models, retrieving technologies and cloud solutions.</li><li>To develop a computer simulation system to facilitate the separation of complex samples in chemical chromatography 1d-LC (one column), 2D-LC (two columns) and s2D-LC (two selective columns). The simulation of separations will be mainly addresed through multiobjective optimization schemes based on Articial Intelligence techniques, as Evolutionary Computation.<strong><br></strong></li></ul> - <p><strong><u>Main objective of the project</u>: To promote technological development, innovation and quality research.</strong></p> - RTC-2015-3812-2-P01 - Manuel Mucientes Molina, Alberto José Bugarín Diz, José Ramón Ríos Viqueira - José Manuel Cotos Yáñez, Tomás Fernández Pena
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