Overview of Cellular Computing-Basic Principles and Applications

Introduction

Computers, especially the modern day desktops and workstations, owing to their massive processing power and speed, have been traditionally used for deeper understanding of several biological phenomena. Techniques essential for high through put processing of genetic (gene sequencing), transcriptomic (micro-array), proteomic (mass spectroscopy) and imaging (microscopy and diagnostic techniques like CT-Scan, PET, MRI etc.) data, heavily rely on traditional silicon chip based computing systems (Kuznetsov et al., 2013). However at the heart of every computer, lies a processor which ultimately understands Boolean logic and rely on direct or modified form of Von Neumann architecture. This basic simplistic core of a computer also resembles the behavior of an individual cell which responds to certain input parameters (signals) through the generation of an output based on certain sets of logic. This common feature between a computer and a cell gives rise to a relatively new field of study, termed as ‘Cellular Computing’ (CC) which focuses on harnessing the power and characteristics of biological entities like cells for the purpose of computation rather than using traditional in-silico network analogy based methods for better understanding of complex systems (Sipper, 1999; C Teuscher, 2012). In case of CC, the word ‘computation’ does not necessarily restrict its meaning to ‘adding numbers’ only, rather it is used to describe achievable outcomes through direct or engineered (or synthetic) exploitation of bio-molecular / cellular logic sets which have been evolutionarily selected.

The two following example will provide better understanding of the analogy between computer and cellular logic processing system and a couple of the advantages of CC:

• 1.

  The bacterial growth scenario:

Logics like IF/ELSE or AND/OR are a common part of almost every kind of algorithm and rarely requires any introduction. Now it is remarkable to highlight that even the miniature scale cellular biological entity i.e. a bacteria is always responding to its surrounding environment based on such logics and that too is related to its primary aim which is bacterial growth and division (Figure 1). For example IF nutrition is present in the surrounding medium, then continue growth ELSE suspend growth and prepare for tough situation. So it is clear that, without going into any underlying biological pathway details, it is possible to find to similarity between a cell (or bacteria) and a computer. To make a little complex scenario lets add one more factor in the bacterial growth scenario i.e. the temperature. IF nutrition is present in surroundings AND temperature is favorable, continue growth ELSE suspend growth (Figure 1).

Figure 1.

Flow diagram of the series of logical behaviors which a bacterial cell undertakes to make a decision on the suitability of its division

Like any computer program which assess the input values based on predefined conditions and logics to generate the output, bacterial cells also undergoes similar logical steps to make a decision on their division. First the bacterial sensing machinery senses the environmental conditions (mainly temperature and food) and based on their sensing outcome a decision is made on whether division favorable conditions exist or not. While in reality, several parameters are assessed, a two factor (temperature and food) conditions determination system shows that four different possible outcome of the sensing machinery, only one of which is favorable to continue with bacterial division.

The underlying molecular details of this bacterial sensing and growth regulation are also an outcome of series of events of such logic and thereby can be specifically categorized as ‘Molecular Computing’ which although related but for the better understanding of the readers are discussed in details in a separate chapter and thereby carefully kept outside the scope of this chapter.

• 2.

  The traveling salesman problem: