National Academy of Agricultural Sciences (NAAS)
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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706 Issues : 12 per year Publisher : Excellent Publishers Email : editorijcmas@gmail.com / submit@ijcmas.com Editor-in-chief: Dr.M.Prakash Index Copernicus ICV 2018: 95.39 NAAS RATING 2020: 5.38 |
Cells amaze us by showing remarkable resilience to some serious disturbances, while being surprisingly sensitive to minor changes. Creating a digital twin of a cell, a virtual copy of it, will allow different treatments to be tested on a computer before they are used. This will be particularly revolutionary for the treatment of early-stage pre-clinical diseases. Doctors will be able to simulate how different combinations of drugs that might affect a particular pre-clinical disease might affect, potentially avoiding harmful side effects and finding the most effective treatment faster. Detecting early-stage pre-clinical diseases at the molecular level using virtual cells with artificial intelligence is a hot international interdisciplinary research project. This mammoth project requires collaboration across disciplines, industries and countries. Creating virtual cells requires unprecedented collaboration between biologists, computer scientists, mathematicians and many other specialists. The process starts at the molecular level, creating detailed artificial intelligence models of the interactions of DNA, RNA and proteins. These will then be integrated into larger models that show how entire cells function, and eventually scaled up to show how cells work together in tissues and organs. Medical data is collected to identify specific prenosologies at the molecular level. Molecular microdiagnostics are developed and implemented to collect medical data on prenosologies. Solutions are found to neutralize prenosologies using synthesized virtual cells with artificial intelligence. The functionality of synthesized virtual cells with artificial intelligence is formed on the basis of medical data. Medical information is quite specific. Its main feature is the heterogeneity of data, which can be represented as both quantitative (numeric continuous or discrete) and qualitative (categorical ordinal and nominal) variables. Another feature is the long shelf life of medical data. It is also worth noting that the task of storing medical data is complicated by several aspects: the legal significance of the information, its large volume, heterogeneity and complex structure. Health Level 7 (HL7) — the standard for the exchange, management and integration of electronic medical information works with seven levels of open system interaction (OSI). The organization of the medical data storage system begins with the approval of the concept of creating synthesized virtual cells and their modeling, which is decisive in the choice of software and hardware. The creation of synthesized virtual cells will allow identifying diseases at the earliest stage, collecting the necessary data on the state of organs and the body as a whole, making smart analysis, conducting intelligent microdiagnostics and carrying out molecular and genetic healing.
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