GGF Global Genomics
GGF Geneseeker
GGF Codeweaver
What is GGF Genomics?
A GGF (Generative Genome Function) takes a DNA sequence and seeks to identify and simulate the genetic mechanisms underpinning life and its variations.
For this reason a software module –GGF Geneseeker- has been developed to enable any bioinformatics researcher to input a chosen DNA sequence and output a 2D image (or extrapolated 3D image) that represents the protein, tissues or morphology that synthesizes from that DNA sequence. The image is generated from the raw DNA code sequence and uses no pre-loaded images ie the GGF is blind as to what the DNA sequence is producing.
The GGF is analytical – not statistical- in that it is mathematically formulated as an algorithm designed to simulate how the code in DNA geometrically drives protein synthesis, as well as many other mechanisms such as epigenetic regulation, non-coding RNAs functions and other yet-to-be discovered mechanisms.
What if the GGF is reversed?
Our GGF Algorithm Can Work BOTH Ways.
If we know how to generate a GGF image profile mathematically then can the inverse of that mathematics be used to take the profile of a cancer protein, a virus or any biotic component and predict the DNA sequence that made it?
More importantly can we predict the DNA sequence of a biologic that could fit the antigen and neutralize or eradicate it?
We believe we can and are developing our GGF Codeweaver software for that purpose, namely, to develop biologics, pharmaceuticals or vaccines for clinical use.
This tool might also be used to develop biologics such as novel peptides or enzymes. For instance, GGF Codeweaver might be used in conjunction with directed evolution techniques such as SELEX to develop peptides for use in cancer treatment pharmaceuticals.
Mathematical theory to model DNA’s protein synthesis mechanisms?
We have already developed concepts around the GGF Geneseeker and GGF Codeweaver software in tandem with mathematical theory.
We believe the theory builds on the geometry of DNA, Voronoi Tessellation, Penrose Tiling, the Golden Ratio, symmetry and the work of Kauffman, Turing and Prigonine in relation to differentiation and morphology.
How does GGF theory aid genomics?
Unlike transcription factors conducting gene splicing to trigger transcription of exons to express those genes into proteins and morphology, the GGF traverses both exons and introns in DNA sequences regardless of where exons lie (yet still produce meaningful profiles in intergenic regions).
This may be because DNA contains a hidden manifold for those genes that allows splicing for protein synthesis. If so GGF may be decoding the manifold to extract enough fragments of those key genes to reproduce the profiles of proteins, tissues or morphologies. We have developed GGF algorithms, equations, theory and software which we hope can advance science, clinical medicine and biotechnology.
Author of top image above, ‘DNA methylation’: Christoph Bock, Max Planck Institute for Informatics – the image was altered by placing text upon it as shown. This image is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported (https://creativecommons.org/licenses/by-sa/3.0/deed.en) license.