Roots and promises of chemical-based computing.

General principles of information processing by chemical-based biomolecular systems (pseudobiological information processing paradigm) are discussed. These principles include very large scale parallelism of information processing, high behavioral complexity, complementarity of information features, self-organization, and multilevel architecture. Chemical-based information processing devices using these principles seem to be able to solve effectively problems of high computational complexity.     

Nonlinear dynamics of the distributed biochemical systems functioning in the dissipative structure formation mode

Nonlinear dynamical biomolecular systems can evidently be considered as prototypes of information processing devices at molecular level capable to solve problems of high computational complexity. Keeping in mind this goal the dynamics of biochemical system based on enzymatic oxidation of uric acid was considered. The system was studied in the version of distributed biomolecular structure having predetermined geometry of enzyme distribution on a porous planar medium. Being in the regime of stepwise dissipative structure formation this system demonstrated complicated modes of behaviour.     

Biomolecular computing systems: principles, progress and potential

The task of information processing, or computation, can be performed by natural and man-made 'devices'. Man-made computers are made from silicon chips, whereas natural 'computers', such as the brain, use cells and molecules. Computation also occurs on a much smaller scale in regulatory and signalling pathways in individual cells and even within single biomolecules. Indeed, much of what we recognize as life results from the remarkable capacity of biological building blocks to compute in highly sophisticated ways. Rational design and engineering of biological computing systems can greatly enhance our ability to study and to control biological systems. Potential applications include tissue engineering and regeneration and medical treatments. This Review introduces key concepts and discusses recent progress that has been made in biomolecular computing.     

Cell and tissue based technologies for environmental detection and medical diagnostics.

We are in the midst of a biotechnology revolution. Significant advances have been made in sensors and diagnostics based on interrogation of biomolecular arrays. The surface conjugation of nucleic acids, antibodies and proteins onto 'chip' formats has resulted in new classes of high information content devices. This compilation of articles presents the emergence of a new class of such devices based on the ability to interrogate cellular or tissue microarrays. Unlike nucleic acid or antibody-based approaches, these systems enable the interrogation of more complex biological responses, and offer the potential to gather higher information content from measuring physiologic, metabolic, or network processes and responses. This endeavor presents many technological challenges but offers the promise of collecting information more closely correlated to human response and as such represents the opportunity to fabricate new sensors and diagnostics for environmental detection and medical diagnostics.     

Capacitive microsystems for biological sensing

The growing interest in personalized medicine leads to the need for fast, cheap and portable devices that reveal the genetic profile easily and accurately. To this direction, several ideas to avoid the classical methods of diagnosis and treatment through miniaturized and label-free systems have emerged. Capacitive biosensors address these requirements and thus have the perspective to be used in advanced diagnostic devices that promise early detection of potential fatal conditions. The operation principles, as well as the design and fabrication of several capacitive microsystems for the detection of biomolecular interactions are presented in this review. These systems are micro-membranes based on surface stress changes, interdigitated micro-electrodes and electrode-solution interfaces. Their applications extend to DNA hybridization, protein-ligand binding, antigen-antibody binding, etc. Finally, the limitations and prospects of capacitive microsystems in biological applications are discussed.     

Computer‐aided biochemical programming of synthetic microreactors as diagnostic devices

Biological systems have evolved efficient sensing and decision‐making mechanisms to maximize fitness in changing molecular environments. Synthetic biologists have exploited these capabilities to engineer control on information and energy processing in living cells. While engineered organisms pose important technological and ethical challenges, de novo assembly of non‐living biomolecular devices could offer promising avenues toward various real‐world applications. However, assembling biochemical parts into functional information processing systems has remained challenging due to extensive multidimensional parameter spaces that must be sampled comprehensively in order to identify robust, specification compliant molecular implementations. We introduce a systematic methodology based on automated computational design and microfluidics enabling the programming of synthetic cell‐like microreactors embedding biochemical logic circuits, or protosensors, to perform accurate biosensing and biocomputing operations in vitro according to temporal logic specifications. We show that proof‐of‐concept protosensors integrating diagnostic algorithms detect specific patterns of biomarkers in human clinical samples. Protosensors may enable novel approaches to medicine and represent a step toward autonomous micromachines capable of precise interfacing of human physiology or other complex biological environments, ecosystems, or industrial bioprocesses.     

Digital and biological computing in organizations.

Michael Conrad unveiled many of the fundamental characteristics of biological computing. Underlying the behavioral variability and the adaptability of biological systems are these characteristics, including the ability of biological information processing to exploit quantum features at the atomic level, the powerful 3-D pattern recognition capabilities of macromolecules, the computational efficiency, and the ability to support biological function. Among many other things, Conrad formalized and explicated the underlying principles of biological adaptability, characterized the differences between biological and digital computing in terms of a fundamental tradeoff between adaptability and programmability of information processing, and discussed the challenges of interfacing digital computers and human society. This paper is about the encounter of biological and digital computing. The focus is on the nature of the biological information processing infrastructure of organizations and how it can be extended effectively with digital computing. In order to achieve this goal effectively, however, we need to embed properly digital computing into the information processing aspects of human and social behavior and intelligence, which are fundamentally biological. Conrad's legacy provides a firm, strong, and inspiring foundation for this endeavor.     

Thermodynamic Costs of Information Processing in Sensory Adaptation

Biological sensory systems react to changes in their surroundings. They are characterized by fast response and slow adaptation to varying environmental cues. Insofar as sensory adaptive systems map environmental changes to changes of their internal degrees of freedom, they can be regarded as computational devices manipulating information. Landauer established that information is ultimately physical, and its manipulation subject to the entropic and energetic bounds of thermodynamics. Thus the fundamental costs of biological sensory adaptation can be elucidated by tracking how the information the system has about its environment is altered. These bounds are particularly relevant for small organisms, which unlike everyday computers, operate at very low energies. In this paper, we establish a general framework for the thermodynamics of information processing in sensing. With it, we quantify how during sensory adaptation information about the past is erased, while information about the present is gathered. This process produces entropy larger than the amount of old information erased and has an energetic cost bounded by the amount of new information written to memory. We apply these principles to the E. coli''s chemotaxis pathway during binary ligand concentration changes. In this regime, we quantify the amount of information stored by each methyl group and show that receptors consume energy in the range of the information-theoretic minimum. Our work provides a basis for further inquiries into more complex phenomena, such as gradient sensing and frequency response.     

Do biomolecules process information differently than synthetic organic molecules?

This paper compares information/signal processing in synthetic and biological molecules. The role of conformation-based (shape-based) mechanisms and electrostatic interactions in molecular recognition is discussed. In biological electron transfer, the 'electron shuttle'-mediated mechanism is contrasted with the mechanism based on pre-formed 'electron wires'. While biological information processing is thought to be more distributed (less discrete), an example of molecular switch is presented: visual transduction. We further speculate that visual transduction may be implemented in the form of a switch based on electrostatic interactions. The concept of intelligent materials is discussed with the well-known Bohr effect of hemoglobin oxygenation. Based on these examples, we argue that there are no fundamental differences between synthetic and biological molecules in their mode of information processing. In the pursuit of novel paradigms of molecular information processing, we also perceive no conflicts in developing molecular devices that emulate the switching function of conventional microelectronic devices.     

Rewiring cell signaling: the logic and plasticity of eukaryotic protein circuitry

Living cells rival computers in their ability to process external information and make complex behavioral decisions. Many of these decisions are made by networks of interacting signaling proteins. Ongoing structural, biochemical and cell-based studies have begun to reveal several common principles by which protein components are used to specifically transmit and process information. Recent engineering studies demonstrate that these relatively simple principles can be used to rewire signaling behavior in a process that mimics the evolution of new phenotypic responses.     

Interfacing external quantum devices to a universal quantum computer

We present a scheme to use external quantum devices using the universal quantum computer previously constructed. We thereby show how the universal quantum computer can utilize networked quantum information resources to carry out local computations. Such information may come from specialized quantum devices or even from remote universal quantum computers. We show how to accomplish this by devising universal quantum computer programs that implement well known oracle based quantum algorithms, namely the Deutsch, Deutsch-Jozsa, and the Grover algorithms using external black-box quantum oracle devices. In the process, we demonstrate a method to map existing quantum algorithms onto the universal quantum computer.     

Towards computing with proteins

Can proteins be used as computational devices to address difficult computational problems? In recent years there has been much interest in biological computing, that is, building a general purpose computer from biological molecules. Most of the current efforts are based on DNA because of its ability to self‐hybridize. The exquisite selectivity and specificity of complex protein‐based networks motivated us to suggest that similar principles can be used to devise biological systems that will be able to directly implement any logical circuit as a parallel asynchronous computation. Such devices, powered by ATP molecules, would be able to perform, for medical applications, digital computation with natural interface to biological input conditions. We discuss how to design protein molecules that would serve as the basic computational element by functioning as a NAND logical gate, utilizing DNA tags for recognition, and phosphorylation and exonuclease reactions for information processing. A solution of these elements could carry out effective computation. Finally, the model and its robustness to errors were tested in a computer simulation. Proteins 2006. © 2006 Wiley‐Liss, Inc.     

Towards the preparative and large-scale precision manufacture of virus-like particles

Virus-like particles (VLPs) are of interest in vaccination, gene therapy and drug delivery, but their potential has yet to be fully realized. This is because existing laboratory processes, when scaled, do not easily give a compositionally and architecturally consistent product. Research suggests that new process routes might ultimately be based on chemical processing by self-assembly, involving the precision manufacture of precursor capsomeres followed by in vitro VLP self-assembly and scale-up to required levels. A synergistic interaction of biomolecular design and bioprocess engineering (i.e. biomolecular engineering) is required if these alternative process routes and, thus, the promise of new VLP products, are to be realized.     

Data mining and predictive modeling of biomolecular network from biomedical literature databases

In this paper, we present a novel approach Bio-IEDM (biomedical information extraction and data mining) to integrate text mining and predictive modeling to analyze biomolecular network from biomedical literature databases. Our method consists of two phases. In phase 1, we discuss a semisupervised efficient learning approach to automatically extract biological relationships such as protein-protein interaction, protein-gene interaction from the biomedical literature databases to construct the biomolecular network. Our method automatically learns the patterns based on a few user seed tuples and then extracts new tuples from the biomedical literature based on the discovered patterns. The derived biomolecular network forms a large scale-free network graph. In phase 2, we present a novel clustering algorithm to analyze the biomolecular network graph to identify biologically meaningful subnetworks (communities). The clustering algorithm considers the characteristics of the scale-free network graphs and is based on the local density of the vertex and its neighborhood functions that can be used to find more meaningful clusters with different density level. The experimental results indicate our approach is very effective in extracting biological knowledge from a huge collection of biomedical literature. The integration of data mining and information extraction provides a promising direction for analyzing the biomolecular network     

Understanding the brain by controlling neural activity

Causal methods to interrogate brain function have been employed since the advent of modern neuroscience in the nineteenth century. Initially, randomly placed electrodes and stimulation of parts of the living brain were used to localize specific functions to these areas. Recent technical developments have rejuvenated this approach by providing more precise tools to dissect the neural circuits underlying behaviour, perception and cognition. Carefully controlled behavioural experiments have been combined with electrical devices, targeted genetically encoded tools and neurochemical approaches to manipulate information processing in the brain. The ability to control brain activity in these ways not only deepens our understanding of brain function but also provides new avenues for clinical intervention, particularly in conditions where brain processing has gone awry.     

Information processing mechanisms in microtubules at physiological temperature: Model predictions for experimental tests

Both direct and indirect experimental evidence has shown signaling, communication and conductivity in microtubules (MTs). Theoretical models have predicted that MTs can be potentially used for both classical and quantum information processing although controversies arose in regard to physiological temperature effects on these capabilities. In this paper, MTs have been studied using well-established principles of classical statistical physics as applied to information processing, information storage and signal propagation. To investigate the existence of information processing in MTs we used cellular automata (CA) models with neighbor rules based on the electrostatic properties of the molecular structure of tubulin, and both synchronous and asynchronous updating methods. We obtained a phase diagram of possible dynamic behaviors in MTs that depend on the values of characteristic physical parameters that can be experimentally verified.     

Analysis of intentional head gestures to assist computer access by physically disabled people

Any human-computer interface requires both a means of transducing information flowing from the person and a way of classifying this information in a form that can be used by an application program. Since several interface devices exploit the head movements of disabled people to control computers, this paper includes a discussion of existing technologies based on head movements. As an alternative to simple techniques based on pointing to classify this information, this paper studies the possibility of using a combination of pointing and movement gestures to control an application program. By using hidden Markov models to classify movements into ‘yes’, ‘no’ and spurious gestures, it was possible to control a simple graphics application program. Subsequent analysis showed that the hidden Markov models achieved a 74% success rate.     

Finding paths in a labyrinth based on reaction-diffusion media.

During the past few decades, many proposals were made on how to take an effective solution for finding a path in a labyrinth, one of the most well known problems of high computational complexity inherent in information processing by biomolecular and biological entities. In particular, attempts were made to use a technique attractive enough for solving this problem based on wave processes in reaction-diffusion media. Trigger waves in reaction diffusion systems spread simultaneously through all paths of the labyrinth in a highly parallel mode. Regretfully, the velocity of these waves is extremely low which gave no way for the practical implementation of this technique until now. An effective 'hardware' system was designed which was capable of finding a path in a labyrinth using fast phase waves. Three principal points were assumed as a basis for this design, i.e. (1) hybrid architecture that combined an information processing reaction-diffusion medium which performs operations of high computational complexity with a digital computer carrying out supplementary image processing operations; (2) light-sensitive information processing media of Belousov-Zhabotinsky type that enables the simulation of the labyrinth and spreading wave evolution by their images stored in the medium and reduces the problem to the image processing operations; (3) fast light-induced phase wave processes that spreads through the labyrinth in several seconds instead of hours which is typical for trigger waves inherent in reaction-diffusion media. These fundamentals along with the additional procedure of testing for labyrinth fragment connectness provided us with the opportunity to solve labyrinth problems.     

Recent trends in studies of biomolecular phase separation

Biomolecular phase separation has recently attracted broad in-terest, due to its role in the spatiotemporal compartmentalization of living cells. It governs the formation, regulation, and dissociation of biomolecular condensates, which play multiple roles in vivo, from activating specific biochemical reactions to organizing chromatin. Interestingly, biomolecular phase separation seems to be a mainly passive process, which can be ex-plained by relatively simple physical principles and reproduced in vitro with a minimal set of components. This Mini review focuses on our current understanding of the fundamental principles of biomolecular phase separation and the recent progress in the research on this topic.