Juan Manuel Corchado participates in the Confluence2023 international conference to discuss biotechnology

This week the 13th International Conference on Cloud Computing, Data Science & Engineering (Confluence2023) is being held at Amity University (Noida, New Delhi), an event that gathers researchers and specialists every year to discuss the latest developments in Data Science, engineering and Cloud Computing.

Juan Manuel Corchado, director of the BISITE Research Group and president of the AIR Institute, participated with a presentation entitled “Data Analytics in the Biotech sector: From Next Generation Sequencing to Reverse Vaccinology”. During his presentation he shared an interesting analysis of next generation sequencing (NGS), with the audience, and discussed the importance of platforms such as DeepNGS in NGS analysis development and practical application.

Next-generation sequencing techniques have revolutionized current genomic research. The use of the latest technologies in NGS, such as cloud computing, artificial intelligence, or machine learning, allow complete human genomes to be sequenced in as little as one day. Previous conventional Sanger technologies used to take more than a decade to complete this process.

However, NGS has yet to become an everyday clinical practice. End-user applications must meet the real needs of every physician, every lab technician, every DNA analysis laboratory and every researcher.

Furthermore, during his presentation he provided insight into how such techniques can be used to create vaccines computationally, known as reverse vaccinology.

Technological solutions for data analysis in the biotech industry

DeepNGS is a fast and automated platform for physicians and researchers. It is a project developed by researchers from AIR Institute, the BISITE Group and the Institute of Biomedical Research of Salamanca (IBSAL). This tool processes sequenced human DNA samples and obtains a set of key genetic variants for the clinical diagnosis of any patient.

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

The result is a set of detected variants, either Single Nucleotide Variations (SNVs) or INDELs and structural variants. Once the alignment, variant detection and annotation steps have been completed, the intuitive DeepNGS interface provides an overview and plenty of visualizations from which conclusions can be drawn immediately.

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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