Knowledge Engineering Platform Using a Biomimetic Digital Twin Ecosystem in Biomedicine - Free Initial Analysis on Your Data

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Artificial intelligence (AI) and other technologies, such as machine learning (ML), particularly Large Language Models (LLMs) hold tremendous promise for driving advances in biomedical research, but, along with their benefits, these technologies have limitations.


Traditional AI normalizes data and removes outliers, thus hindering the identification of hidden or “dark” data. AI and LLMs also require a test training set to perform the analysis, and this introduces bias into the process.


On July 5, 2023, former Google CEO Eric Schmidt wrote in MIT Technology Review, “we should be cognizant of the limitations—and even hallucinations—of current LLMs before we offload much of our paperwork, research, and analysis to them.” The huge datasets required by traditional AI and the associated scale of combinatorial math limit the ability of the algorithms to explore biological complexity1, relegating most key relationships and critical interactions into what the technology company Gartner has coined “dark data” – data that is unseen, unexplored and as a result, unanalyzed (https://www.gartner.com/en/information-technology/glossary/dark-data).


To address these issues and to provide guidance to the biomedical community, the National Academies of Sciences, Engineering and Medicine (NAS), sponsored by the National Institutes of Health (NIH), the National Science Foundation (NSF) and the Department of Energy (DOE), began advocating research into the use of biomimetic digital twins technology to more effectively model multidimensional and multi-scale biological complexity (https://www.nationalacademies.org/event/01-30-2023/opportunities-and-challenges-for-digital-twins-in-biomedical-sciences-a-workshop). The NAS also published a Physics of Life Report (http://nap.edu/26403)2 which concluded, “An important lesson from the long and complex history of neural networks and artificial intelligence is that revolutionary technology can be based on ideas and principles drawn from an understanding of life, rather than on direct harnessing of life’s mechanisms or hardware.”


To address these issues, we incorporated a biomimetic digital twin ecosystem into our advanced genomics experimental protocol. We will do a preliminary analysis on your data, and provide you a report on the presence of any hidden data in your analysis. Our analysis can include results from:

Whole Genome or Clinical Exome sequencing.

Targeted Panel sequencing.

Enriched sequencing.

High throughput RNA sequencing (RNA-Seq)

Copy number variants (CNVs)\

Proteomics

Metabolomics

Optical Genome Mapping (OGM) (With a combined clinical report on OGM for chromosomal aberrations and either whole genome or clinical exome sequencing.)

Morphology or Imaging

Methylome (Methylation patterns).

Microarrays

Drug Development

Clinical Trials


Dr. William G. Kearns
Chief Executive Officer
Chief Scientific Officer
Email: wgkearns@genzeva.com



Additional Info

Expiration Date : 3/1/2024

Promo Code : WGKMDTechCouncil

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