An analytical biology aims to leverage the power of physics, data science, machine learning and AI to extract information from fundamental biological objects (such as DNA, RNA and proteins) to enable predictions about biological phenomena that are akin to those available in other natural sciences such as physics and chemistry, in spite of the enormous difference in complexity of the phenomena of interest (e.g., life in general.) For example, recent advances in elucidating important geometric properties of DNA in the references below have shown that such models do exist and such advances are possible. This evolution has produced models that scale the power of phenotypic, phylogenetic, genomic and evolutionary analysis in silico, and potentialy in vitro.

For example, metric approximations of Gibbs energy of hybridization were introduced in (Garzon et al, 1997) and have been explored in a series of papers by various authors since. Another example is models of morphogenesis and development that show how many emergent properties of living organisms (such as self-reproduction and self-healing) area a logical and inevitable consequence of more fundamental properties such as self-assembly and self-organization. Details of results, publications, software and data that can be used for this type of research can be found on these pages.

• Metric models of Hybridization and Gibbs Energy Landscapes
  + A Geometric Approach to Gibbs Energy Landscapes and Optimal DNA Codeword Design. Max H. Garzon. Kiran C. Bobba. Proc DNA18, Springer-Verlag Lecture Notes in Computer Science 7433 (D. Stefanovic and A. Turberfield, eds.) (2012), 73-85.
  + On Codeword Design in Metric DNA Spaces. Vinhthuy Phan, Max H. Garzon. J. Natural Computing, 8:3 (2009), 571 - 588.
  + A New Metric for DNA Computing. Max Garzon, P. Neathery, R. Deaton, R.C. Murphy, D. Franceschetti, Proc. 2nd Annual Genetic Programming Conference, Morgan Kaufmann (1997), 472-478.
  
• Next-Gen Microarray (nxh DNA chips) and Codeword Design
  + Towards Reliable Microarray Analysis and Design. M. Garzon and S. Mainali . BICoB’17-Int Conference on Bioinformatics and Computational Biology, Int. Society for Computer Applications ISCA (2017). 6 pp.
  + Theory and Applications of DNA Codeword Design. Max H. Garzon. Proc. First Int Conference (TPNC 2012) on Theory and Practice of Natural Computing, Tarragona, Spain, Springer-Verlag Lecture Notes in Computer Science 7505 (2012), (A.H. Dediu, C. Martín-Vide, and B. Truthe, eds), 11-26.
  + Optimal Codes for Computing and Self-Assembly, Max H. Garzon. Vinhthuy Phan, Andrew Neel. Int. J. of Nanotechnology and Molecular Computation 1:1 (2009), 1-17.
  + Characterization of Non-Crosshybridizing DNA Oligonucleotides Manufactured in vitro. J. Chen, R. Deaton, Max Garzon , D.H. Wood, H. Bi, D. Carpenter, Y.Z. Wang. J. of Natural Computing 5:2 (2006), 165-181.
  + Test Tube Selection of Large Independent Sets of DNA Oligonucleotides. R. Deaton, J. Chen, Max Garzon , D.H. Wood. In: Nanotechnology; Science and Computation (J. Chen, J. Jonoska, G. Rozenberg, eds) Springer-Verlag Natural Computing Series (2005), 147-164.
  + Codeword Design and Information Encoding in DNA Ensembles. Max H. Garzon, Russell Deaton. J. of Natural Computing 3:3 (2004), 253-292.
  + Biomolecular Computing in silico. Max H. Garzon. Bulletin of the EATCS 79 (2003), 129-145.
  + The Reliability and Efficiency of a DNA-based Computation. R. Deaton, Max H. Garzon, R. Murphy, J. Rose, D. Franceschetti, E. Stevens Jr. Physical Review Letters 80:2 (1998), 417-420.
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• Phylogenetics
  + Genomic Solutions to Hospital-Acquired Bacterial Infection Identification. Max Garzon and Duy Pham (2018). Proc. IWBBIO’17-Int. Work-Conference on Bioinformatics and Biomedical Engineering Lecture Notes in Bioinformatics-LNBI 10813, 486-497. DOI-DOI-978-3-319-78722-0.
  + Towards a Universal Genomic Positioning System: Phylogenetics and Species Identification. Max Garzon and Sambriddhi Mainali (2017). Proc. IWBBIO’17-Int. Work-Conference on Bioinformatics and Biomedical Engineering Lecture Notes in Bioinformatics -LNBI 10209, 469-479. DOI-10.1007/978-3-319-56154-7_42.
  + Genomic Positioning Systems for DNA and the Tree of Life. Max H. Garzon, Proc. of the 300th OMICS Int Conference on Transcriptomics, Orlando, Florida (2015), 63 (invited).
  + DNA Chips for Species Identification and Biological phylogenies. Max H. Garzon, Tit-Yee Wong, Vinhthuy Phan. Proc. DNA15, Springer-Verlag Lecture Notes in Computer Science 5877 (R. Deaton, A. Suyama, eds.) (2009), 55-66.
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• Semantic Analysis and DNA-based Indexing
  + DNA-Based Indexing. Max H. Garzon, Kiran C. Bobba, Andrew Neel, Vinhthuy Phan. Int. J. of Nanotechnology and Molecular Computation 2:3 (2010), 25-45.
  + Semantic Methods for Textual Entailment: How Much World Knowledge is Enough? A. Neel and M. Garzon Proc. Twenty-Third Int. AI Research Symposium. FLAIRS, AAAI-2010. Daytona Beach, Florida, USA. 253-258. (2010).
  + Semantic Methods for Textual Entailment: Old and New. Andrew J. Neel, Max H. Garzon. FLAIRS Conference, AAAI-MIT Press (2010).
  + Semantic Retrieval in DNA-based Memories with Gibbs Energy Models. Andrew Neel, Max H. Garzon. Biotechnology Progress 22:1(2006), 86-90.
  
• DNA Self-Assembly and DNA Nanotechnology
  + DNA-based Memories: A Survey. Andrew J. Neel and Max H. Garzon. Springer-Verlag Studies in Computational Intelligence 113 (G. Bel-Enguix, M.D. Jimenez-Lopez, C. Martin-Vide, eds.) (2008), 259-275.
  + Codeword Design and Information Encoding in DNA Ensembles. Max H. Garzon, Russell Deaton. J. of Natural Computing 3:3 (2004), 253-292.
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A software package hermes has been created to explore and develop new applications based on Genomic Positioning Systems and structural bioinformatics.
If you find a problem with the simulation or visualization engines, please report it to mgarzon@memphis.edu.