Next generation sequencing research at the DATA 2022 International Conference

The International Conference “Digital Age & Technological Advances for sustainable development” IC-DATA 2022 was held last week. An event organised by the Faculty of Science and Technology of Al-Hoceima in Morocco. DATA is a comprehensive conference focusing on the various aspects of information technology advances for sustainable development.

The main objective of DATA is to enhance research by reaching the maximum capacity and fostering open debates on digitisation and recent technologies for sustainable development.

In this regard, Juan Manuel Corchado, director of the BISITE Research Group and president of the AIR Institute participated in the third DATA conference to present one of the projects that we are developing. It is a project on a next generation sequencing tool called DeepNGS, that automates the genetic analysis workflow and can help in diagnostic procedures.

Next-generation sequencing: from theory to practice

Also known as massively parallel or deep sequencing, Next Generation Sequencing (NGS) techniques have revolutionised genomic research today. The use of the latest NGS technologies (cloud computing, artificial intelligence, machine learning) makes it possible to sequence entire human genomes in a single day. Previous conventional Sanger technologies took more than a decade to complete this process.

However, NGS has not yet become an everyday clinical practice. End-user applications must meet the real needs of every clinician, every lab technician, every DNA analysis lab, every researcher.

DeepNGS is a fast and automated platform for clinicians and researchers. It processes sequenced human DNA samples and obtains a set of key genetic variants for the clinical diagnosis of any patient.

Our platform incorporates all the patient’s genetic data in a highly secure cloud environment and achieves a higher level of accuracy. It is able to digest the information to ensure the accuracy of the final diagnosis and the appropriateness of treatment recommendations. We are progressively incorporating ML algorithms to optimise the analysis process and achieve even better and more reliable results.

Once the alignment, variant detection and annotation stages have been completed, the intuitive DeepNGS interface provides an overview and a large number of visualisations from which conclusions can be drawn immediately.

It has been an excellent opportunity to showcase the work we are doing at both BISITE and AIR Institute for the advancement of scientific research.

Juan Manuel Corchado

Full Professor in Computer Science and Artificial Intelligence, Department of Computer Science and Automation, University of Salamanca, Spain.


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