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Medical Biomatics -

Medical Biomatics


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One of the goals of the National Institutes of Health (NIH) Roadmap for Medical Research is to explore biological pathways and networks.  Computer scientists have been studying the analogies between biological networks and computer networks since at least the seventies.  This study has gone by names such as “computational molecular biology” and “Biomatics”.

Biomatics deals with Information processing in molecular systems i.e. Naturally occurring computation.  The processes of molecules such as proteins bear striking similarities to the fundamental processes studied by computer scientists.  The fundamental building blocks of artificial computation are theoretically available to biological systems.  This is a much simpler claim to demonstrate than one would think.  It is well known to computer scientists that the NAND gate is what is known as- “logically complete”- in that any digital logic circuit can be constructed from some network built entirely of NAND gates.  This property is referred to as  “computational completeness”.  A single protein can easily be shown to act in a manner isomorphic to a NAND gate.

At first, the extramolecular (interactions between different molecules) properties of protein networks were studied.  Enzymes, a special class of proteins, controlled information flow in networks by catalyzing reactions in complex lattices. Now it is evident that a structure isomorphic to a NAND gate can at least potentially exist within a single protein molecule.  In 2000, C. David Allis coined the term- “Histone code” -referring to the Histone protein’s apparent ability to be reversibly modified in an on/off way.  

All diseases have a genetic component to some extent. Disorders where genetics play a central role are called genetic diseases. Examples include coronary heart disease, hypertension, stroke, and cancer.  Genetic errors can be of at least two types-  (i) Genetic alterations such as mutations and (ii) errors in modulation of gene expression.  The mechanisms modulating genetic expression are in large part analogous to concepts of electro-mechanical engineering, computer science, and pure mathematics.  Biologists are ever increasingly using vocabulary that intersects with these disciplines: networks, state transitions, systems and modules, multimolecular machines, signaling pathways, and molecular computation.

The characterization of discriminator genes might accelerate the development of new specific and alternative therapies.  The expression of these genes may be governed by biomatical principles.  Conversely, studying the mechanisms of Genetic diseases may shed light on new principles of Biomatics.  Cancer is an especially appealing subject because a good portion of DNA microarray experiments deal with this topic.  In addition many of these experiments when subjected to clustering algorithms yield eight clusters of genes.  While this does not necessarily mean there is a 3 to 8 conversion mechanism occurring here, the possibility should at least be considered.  If it were to be the case, it would result in a great deal of structure in place. This in turn would provide therapeutic possibilities.


Protein misfolding
Life may be thought of as the co-ordinated activity of proteins, and disease as an imbalance of proteins that adversely affects the quality of life – either through too little of a particular protein being present, or too much of a protein, or a protein being produced or rendered dysfunctional, or produced at the wrong place or the wrong time. Biomatics is yet another modality of protein function which can go awry.  Inappropriate folding is one way in which a protein imbalance may arise – the misfolded protein may be nonfunctional or suboptimally functional, or it may be degraded by cellular machinery, or the misfolding may expose epitopes which lead to dysfunctional interactions with other proteins. There are a number of serious diseases which have a common aspect in that they all appear to involve inappropriate folding of a particular protein. These diseases are sometimes lumped together under the heading of the protein misfolding diseases.
Biomatic models deal with computational functioning of proteins.  Proteins are complex machines governed by laws which in great amount intersect those of computer science and mathematics. Proteins are in the domain of computer science as much as they are in biology and chemistry. They are naturally occuring computing machinery. In biomatics the protein is a finite state machine which is a property that they share with their silicon cousins.




Finite State Disease Models

 The human body involves many diverse "systems" occuring at many scales from molecular to populational.  Biomatics involves those biological systems that behave according to principles of Computer Science.  Those systems that can be modeled in a discrete on/off, zero/one way.  In the human body of course, the DNA Machinery, is at the kernel of these systems. The geometry and thermodynamic forces involved in the activities of the carbon atom and chains of such atoms result in a discrete or digital computing machine as a result of rotations about covalent bonds and other possible mechanisms.  Since all conditions and diseases have a genetic component, these automata  based models are essential.  


Protein folding diseases

The process of protein folding is remarkably efficient, but sometimes it can go wrong. This can have harmful consequences, as the incorrect folding of proteins is thought to be the cause of diseases, such as Alzheimer�s disease and cancer. For a long time, protein folding was regarded as simply a theoretical problem. Researchers investigated the mechanisms of protein folding to close the huge gap in our knowledge between the genetic blueprint of a protein and its biological function. Only in the 1990s did it become clear that wrongly folded proteins are involved in the development of many diseases. Now, protein folding has become a focus of attention in pharmaceutical research: it is probable that new approaches to the treatment of diseases such as cancer and Alzheimer�s disease are to be found within its convoluted pathways.

 Protein folding diseases were divided into two groups: in the first, excessive quantities of wrongly folded proteins collect in the form of uncontrolled piles of molecular rubbish. This is the group of diseases known as amyloidoses, of which Alzheimer�s disease is the best-known example. In the other, a small error in the genetic blueprint leads to incomplete folding of a protein, which affects its function. This might, for instance, happen to p53 � the malfunctioning of this central tumour suppressor could cause cancer. Now it is clear that in a third model the proteins may be said to have faulty transitioning between machine states.


Fractal Disorders


Conditions and Diseases

Protein Folding

Computational Oncology

Cancer studies

Tumors involving endothelial cells or B lymphocytes

Growth and Differentiation


Computational Psychology and Psychiatry

Artificial Intelligence

The Microtubule code

Quantitative psychology

Forensic biomatics

Network biology

Biological information objects


DNA Microarray Analysis and Gene Expression Profiling

The Amino Acid Code


The Histone Code

Histone proteins

Histone Stoichiometry

Histone COC

Hox genes

The damage-induced gene set

P53 induction

Classification of CMV genes into four kinetic classes


Posttranslational modification




Computational or Information Processing Proteins

The Protein Folding Problem

Stages in Cellular Processes

Transport Proteins


Molecular Robotics

Quine-McCluskey algorithm

Development of human machine interfaces

Biomatics Graphics and  Animation

Development of artificial organs and appendages

Bio-mechanical organism


Protein chip

Cellular and Tissue Architecture

Biomatics Based Biomedical Imaging Systems



Rational drug design

Methyltransferase inhibitors





Acetyltransferase COC

Histone  deacetylase  inhibitors


Dose-responses to estrogens

External LInks:

Researchers at Wake Forest University School of Medicine and the University of Virginia hope to reset part of the "epigenetic code" in lupus patients and thus improve treatment.
       Researchers at the University of Pennsylvania School of Medicine discovered that proteins carrying chemical cargo in nerve cells react differently when exposed to the tau protein, which plays an important role in Alzheimer’s disease.


 High-throughput technologies for DNA sequencing and for analyses of transcriptomes, proteomes and metabolomes have provided the foundations for deciphering the structure, variation and function of the human genome and relating them to health and disease states. The increased efficiency of DNA sequencing opens up the possibility of analyzing a large number of individual genomes and transcriptomes, and complete reference proteomes and metabolomes are within reach using powerful analytical techniques based on chromatography, mass spectrometry and nuclear magnetic resonance. Computational and mathematical tools have enabled the development of systems approaches for deciphering the functional and regulatory networks underlying the behavior of complex biological systems.




Dynein and kinesin proteins transport cellular cargo towards opposite ends of tracks called microtubules. Tau binds to the microtubule surface and acts like a speed bump to regulate protein traffic, the group found. “But it is a smart speed bump because it impedes these different motor proteins to different degrees,”

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