Issue |
ITM Web Conf.
Volume 56, 2023
First International Conference on Data Science and Advanced Computing (ICDSAC 2023)
|
|
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Article Number | 02001 | |
Number of page(s) | 11 | |
Section | Data Science | |
DOI | https://doi.org/10.1051/itmconf/20235602001 | |
Published online | 09 August 2023 |
Validation of genome information in real time, including illness mapping and polymorphism
Department of Computer Science Engineering, Sathyabama Institute of Science and Technology, India
The world of genetics is on the threshold of a new era. With real-time genetic sequencing, researchers can quickly and accurately verify genetic sequences in real time, providing rich information for disease diagnosis and treatment. This technology, combined with disease mapping and genetic polymorphism analysis, is the key to unlocking the mysteries of genetic disorders and developing more effective treatments. This article explores the exciting opportunities and challenges of real-time genetic sequencing and provides a glimpse into the future of personalized medicine and precision medicine. In the present framework, gene dependency networks often change in response to differences in disease types. A main goal of genomic research is to determine if and how these networks are formed between the two disease states. An innovative asymmetric network inference method is proposed to detect the alteration of gene networks by integrating information about gene expression and mutations. The subgroup bridge penalty mechanism is used to distinguish commonalities and differences between different data types. The goal of the modification process is to identify individuals at high risk of disease and then recommend either a specific diet or other natural remedies based on the results of the genetic screening procedure.
Key words: Classification / evolutionary multi-objective optimization / network construction / Disease module identification
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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