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Learning from Nature: Towards a Nucleotidic modeling - part II

Two days ago, my friend Olivier Vallée sent me an article (nytimes) talking about the emerging role of software tools in reducing costs of lawyers’ work by analyzing documents contents. This reminded me the work we did, Olivier and I, some years ago around the use of a nucleotidic approach for analyzing textual data.


So, here again to continue the subject of the earlier post!


In part I, I presented a first view of the analogies between molecular biology elements and other real world problematic. And a probable benefit of using molecular biology’s structures and be behaviors to in data modeling and software solutions architecture.

In this part, I will try to expose a simple and direct application of this approach: language modeling and analysis. There are several advantages for starting with textual analysis as a first application:

·         First, a textual object structure can easily, and somehow directly, be mapped to molecular biology elements (nucleotides, DNA strands, amino acids…);

·         Second, the textual analysis is becoming (re-becoming!) a must know (and probably lucrative as well J) technology  (see nytimes article);

Let us first try to analyze the physical (organic) structure of a textual object:

·         Characters;

·         Composing Words;

·         Composing phrases;

·         Composing paragraphs;

·         … etc;


This same physical structure can be interpreted according to other (different / parallel) logical  components:

·         Symbols (óCharacters);

·         Composing phonemes (ówords);

·         Composing expressions;

·         Composing sense (social / intellectual orientation (or mood) of the text)


Again, this parallel presentation of a same object (encountered in so many data modeling problematics) is one of the important analogies with molecular biology elements (i.e. similar, for example, to nucleotide sequences mapping to amino acids).

To illustrate another aspect of this analogy, let us take a look at the characters / words ó characters / phonemes parallel. To correctly read a phoneme, we need to locate its start-end characters. Which may overlap or be part of the ‘Words’ sequence of our text. In some way, we need to retrieve the reading frame (or phasing) of a sequence of phonemes through our nucleotidic characters structure. This phasing is independent of the characters/words sequence presentation. Which, again, brings to our mind the question of reading frames of an amino acid sequence contained in a nucleotidic sequence.


In the case of our text sequence question, characters, words, phonemes… etc. are, of course, language-dependent. However, for sake of simplicity, let us stay in the context of the English language.


Let us now take an example of how we can read a ‘mood’ sequence inside a physical text sequence (characters, words…) sequence.

The mood (social sense) of a text can be detected through the interpretation (or translation) of specific (predefined) expressions sequence(s).

For example:

“That’s great” can be interpreted differently from “hey… fantastic”

Or “Hello”, differently from “Hi”…

Or “L” differently from “J

… etc.


Social expression of a text sequence is also, in some way, related to its internal phoneme sequence. Text phonemes actually produce a sequence of sounds that give a particular internal ‘music’ to the text. Which participates, in the end, in transmitting the specific social sense of the initial text sequence. That is probably an important aspect of poetry (?)


I will provide a practical coded example in a future post.

Learning from Nature: Towards a 'Nucleotidic' modeling - part I




During several years, I worked on a DNA sequence-analysis software project where I learned about DNA structures and several DNA engineering techniques.

(That is not to be confused with what is commonly called ‘genetic algorithms’ and ‘genetic programming’).


Elements and structures used (and manipulated) in molecular biology engineering sphere are fascinating and, above all, source of interesting knowledge. In some way, they define the representation of ‘Life hood’ structures and mechanisms for every living creature (plant, animal, bacteria, virus…)

Molecular biology teaches us that ‘Life’ is based on few nucleotides: A, T, G and C.

Like in music partitions, sequences composed of these few number of nucleotides can give unlimited number of combinations each representing the structure of a specific biological function and, in the end, a specific individual being.


Here are some sample (random) fragments of DNA sequences:






Note that DNA sequences are read in a specified direction (noted 3’à5’ in the above sequences).

Nucleotides are considered in complementary (attracted) pairs. A is complementary to T, and G to C.

Each DNA sequence strand has a ‘complementary’ sequence strand where complementary nucleotide pairs are arranged face-to-face in reversed direction to compose part of the well-known helicoidal presentation.



The complementary strand for





A DNA sequence has its mapped amino acid (protein) sequence. In this mapping, different combinations of three nucleotides (A, T, G or C) compose codons, each mapped to one amino acid (one amino acid may have several codon mappings… see below).

Here are some codon/amino acid mappings:


Amino acid

Amino acid Symbol
























A sequence may have several “reading frames” in which amino acid codons mapping interpretation may vary. Essentially, to read a sequence, you must first find a starting codon… otherwise; your sequence is the representation of nothing in biological life (real world!)


Another interesting aspect is that a specific DNA sequence (with ‘significant’ length) seems to represent one part of a global ‘predefined’ structure… that is, in a way, similar to a known melody in music. If you start to play the first specific notes of, say, a Beatles’ song, everyone can tell the rest of the melody. If your first notes are not specific enough, the result may lead to so many different melodies.

This phenomenon is used in PCR (Polymerase Chain Reaction) in molecular biology engineering to amplify or clone DNA sequences using partial sequences (rigorously selected!).        


Useful lessons for software design

Many (if not all J) real world problems seem to follow DNA sequences structure and representations:

§  Basic elements (A, T, G, C)

§  Related each to one another (AT, GC)

§  Composing a global sequence (unique for a specific area)

§  The sequence can be presented differently (DNA /Amino acid)

§  The translation between representations is done through specific mappings (codons / amino acids)


PCR technique also seems of great interest to some software areas (OCR recognition for example)


I will continue, in future posts, to explore these fascinating structures and propose some applications that mimic and benefit from their behaviors.