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Virgo GMO: An open-source approach to genetically modify organism
by Ray Hermann Angossio Liwa
Ray Hermann Angossio Liwa
Virgo GMO: An open-source approach to genetically modify organism
by Ray Hermann Angossio Liwa
Ray Hermann Angossio Liwa
199.0
In Stock
Overview
GeneSIS BioActives is at the crossing line between medicine or biology and computer science, for what we have named computational biology to be able to build computerized systems for laboratory based processes. And this part of the Genesis Research Program for the development of our tree (3) principal web applications, the GeneSIS BioActives Academic, GeneSIS BioActives standard and GeneSIS BioActives Enterprise. But for years to come this will be used on applications like building a human robot portrait with a set of collected DNA on crime scene, for Bio-printing of organs, open-source GMO applications and other for the well being of the MANKIND.
Computational biology is a branch of biology that uses data analysis, mathematical modeling, and computational simulations to study biological systems and processes. It's an interdisciplinary field that combines computer science, biology, and big data, with foundations in applied mathematics, chemistry, and genetics. Computational biology develops and applies computational methods to analyze large collections of biological data, such as genetic sequences, cell populations, or protein samples. These models can describe what biological tasks are carried out by particular nucleic acid or peptide sequences. Computational biology is a broader field that includes both biotechnology and bioinformatics. It's possible to succeed in this field with dedication and the right resources.
Imagine if we succeed to fit the power of our most powerful computers into a computerized system to find a solution to any kind of known or unknown pathogens. From protocols and procedure to gather sample by robots and send them into the most advance of that kind models for a fit to be able to find solutions for any kind of pathology or if not, it could supporting a findings for a rapid and starting response on an event of an epidemic, endemic or pandemic situation. That's the power I'm working so hard to build with the GeneSIS Research Program, together with the Futurists Society.
Computational biology is a branch of biology that uses data analysis, mathematical modeling, and computational simulations to study biological systems and processes. It's an interdisciplinary field that combines computer science, biology, and big data, with foundations in applied mathematics, chemistry, and genetics. Computational biology develops and applies computational methods to analyze large collections of biological data, such as genetic sequences, cell populations, or protein samples. These models can describe what biological tasks are carried out by particular nucleic acid or peptide sequences. Computational biology is a broader field that includes both biotechnology and bioinformatics. It's possible to succeed in this field with dedication and the right resources.
Imagine if we succeed to fit the power of our most powerful computers into a computerized system to find a solution to any kind of known or unknown pathogens. From protocols and procedure to gather sample by robots and send them into the most advance of that kind models for a fit to be able to find solutions for any kind of pathology or if not, it could supporting a findings for a rapid and starting response on an event of an epidemic, endemic or pandemic situation. That's the power I'm working so hard to build with the GeneSIS Research Program, together with the Futurists Society.
Product Details
| BN ID: | 2940185794869 |
|---|---|
| Publisher: | Futurists Society |
| Publication date: | 01/04/2024 |
| Sold by: | Barnes & Noble |
| Format: | eBook |
| File size: | 14 KB |
About the Author
I'm Ray Hermann Angossio Liwa and I'm an Amazon Author Central with a portfolio of ebooks and paperback books as a writer with copyright, a certified US Tax professional, and a Scientist, also the Owner and Strategist behind the Futurists Society. For the past ten years, I have been through many leadership programs, and I have been guided closely in private with some people through my skills and abilities.
My background is based on IoT (Internet Of Things) for the most part, with 7+ professional experience in information security and digital services. Expert and highly familiar with various online service security, engineering, and computer science or networking.
I work well with tools like Bio-conductor, Bio-strings, or others using the R programming language; I have a great level of Python and Shell (CLI) applied to Genomics; With interesting insight on Biotechnology Analytics, Advanced Biostatistics, Algorithms for DNA Sequencing, Boyer Moore algorithm, Naive exact matching algorithm, Fisher exact test, Z-test, T-test, chi-square, Chebyshev's inequality, P-Value, Computational Genomic, Clinical trial, and epidemiology mostly from the University of Arizona and the Johns Hopkins Bloomberg school of public health.
I'm a problem solver with outstanding skills in Artificial intelligence, Data Science, Machine, and Deep Learning concepts, and algorithmic methodology throughout the Stanford University online (Machine Learning by Andrew Ng) and the IBM Developer Program on Coursera as well as other platforms. I specialize with Google in UX design and project management using Waterfall, Agile Six Sigma, and Scrum methodologies, and I'm 100% functional with software like Asana and Jira.
For the record, as part of the IRS Stakeholder Liaison as a Tax Practitioner, I hold 130 CPE credits ( Federal and State Tax Law) with wit 7 credits on Forensic Fraud detection training from the Internal Revenue Service (IRS) and the State of California Tax Education Council (CTEC) as well as in other states like New York and Maryland.
My background is based on IoT (Internet Of Things) for the most part, with 7+ professional experience in information security and digital services. Expert and highly familiar with various online service security, engineering, and computer science or networking.
I work well with tools like Bio-conductor, Bio-strings, or others using the R programming language; I have a great level of Python and Shell (CLI) applied to Genomics; With interesting insight on Biotechnology Analytics, Advanced Biostatistics, Algorithms for DNA Sequencing, Boyer Moore algorithm, Naive exact matching algorithm, Fisher exact test, Z-test, T-test, chi-square, Chebyshev's inequality, P-Value, Computational Genomic, Clinical trial, and epidemiology mostly from the University of Arizona and the Johns Hopkins Bloomberg school of public health.
I'm a problem solver with outstanding skills in Artificial intelligence, Data Science, Machine, and Deep Learning concepts, and algorithmic methodology throughout the Stanford University online (Machine Learning by Andrew Ng) and the IBM Developer Program on Coursera as well as other platforms. I specialize with Google in UX design and project management using Waterfall, Agile Six Sigma, and Scrum methodologies, and I'm 100% functional with software like Asana and Jira.
For the record, as part of the IRS Stakeholder Liaison as a Tax Practitioner, I hold 130 CPE credits ( Federal and State Tax Law) with wit 7 credits on Forensic Fraud detection training from the Internal Revenue Service (IRS) and the State of California Tax Education Council (CTEC) as well as in other states like New York and Maryland.
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