RNA secondary structure as a reusable interface to biological information resources

The dissemination of biological information has become critically dependent on the Internet and World Wide Web (WWW), which enable distributed access to information in a platform independent manner. The mode of interaction between biologists and on-line information resources, however, has been mostly limited to simple interface technologies such has hypertext links, tables and forms. The introduction of platform-independent runtime environments facilitates the development of more sophisticated WWW-based user interfaces. Until recently, most such interfaces have been tightly coupled to the underlying computation engines, and not separated as reusable components. We believe that many subdisciplines of biology have intuitive and familiar graphical representations of knowledge that can serve as multipurpose user interface elements. We call such graphical idioms “domain graphics”. In order to illustrate the power of such graphics, we have built a reusable interface based on the standard two dimensional (2D) layout of RNA secondary structure. The interface can be used to represent any pre-computed layout of RNA, and takes as a parameters the sets of actions to be performed as a user interacts with the interface. It can provide to any associated application program information about the base, helix, or subsequence selected by the user. We show the versatility of this interface by using it as a special purpose interface to BLAST, Medline and the RNA MFOLD search/compute engines. These demonstrations are available at: ir|url|http://www-smi.stanford.edu/projects/helix/pubs/ gene-combis-96/     

Quantum mechanics in the present progressive mode and its significance in biological information processing

Quantum mechanics practiced in the present progressive mode can incorporate into itself the propagation of a signal of a local character. It is possible to view that any movement in the present progressive mode is mutli-agential in the sense of internal interactions due to the absence of an external agency coordinating the global situation simultaneously. The idea of living memory is discussed as carrying the leftover from those actions completed and registered in the present perfect mode and surviving at any present moment. The occurrence of both the signal propagation of a local character and living memory is upheld upon exchange interaction of a quantum mechanical origin. Empirical evidence suggesting the likelihood of such an exchange interaction is found in the neurotransmitter-gated ion channels located on the plasma membrane of the muscle cell in the vicinity of secretory vesicles containing acetylcholine near the nerve terminal. Another case from the empirical evidence is seen in the actomyosin system demonstrating the unidirectional propagation of variations in the acceleration of the displacement of an actin filament sliding on myosin molecules in the presence of ATP molecules.     

The information processing organisms

In spite of the tremendous progress in recent decades of biological science, many aspects of the behaviour of organisms in general and of humans in particular remain still somewhat obscure. A new approach towards the study of the behaviour of man was presented by Heisenberg when he emphasized that a Cartesian view of nature as an object “out there” is an illusion in so far as “the observer is always part of the formula, the man viewing nature must be figured in, the experimenter into his experiment and the artist in the scene he paints.” (Heisenberg, 1969). The present study is an attempt to make a step forward in this direction by focusing on the ways and means of involvement of the observer which make him an indelible part of the observation. To get a fresh start let us have a look at the physical universe. Although showing an immense variety, all objects, living and non-living, have some characteristics in common. They all obey the physical laws and they all are engaged in perpetual interactions. How do we tell then the difference between living and non-living objects? According to the traditional concept it is the capacity for reproduction that distinguishes living from non-living objects. (Luria et al., 1981). The non-traditional concept presented in this study stresses the way in which objects interact as the crucial point of difference between living and non-living objects. This concept claims that living objects assert themselves as such only when and while interacting in terms of information processing. Under such conditions only, living objects are able to display relative independence of the physical laws, for instance active movement. This display of relative independence is governed by biological laws and defines the behaviour of the living objects as active in principle. All objects who share these characteristics are called living, they behave as wholes assessing themselves as individuals. The definition suggests that they all share the same internal organization which is principally dynamic.     

Evolution of biological information

How do genetic systems gain information by evolutionary processes? Answering this question precisely requires a robust, quantitative measure of information. Fortunately, 50 years ago Claude Shannon defined information as a decrease in the uncertainty of a receiver. For molecular systems, uncertainty is closely related to entropy and hence has clear connections to the Second Law of Thermodynamics. These aspects of information theory have allowed the development of a straightforward and practical method of measuring information in genetic control systems. Here this method is used to observe information gain in the binding sites for an artificial ‘protein’ in a computer simulation of evolution. The simulation begins with zero information and, as in naturally occurring genetic systems, the information measured in the fully evolved binding sites is close to that needed to locate the sites in the genome. The transition is rapid, demonstrating that information gain can occur by punctuated equilibrium.     

Adaptive information processing in microtubule networks

Microtubule networks provide a wide range of microskeletal and micromuscular functionalities. Evidence from a number of directions suggests that they can also serve as a medium for intracellular signaling processing. The model presented here comprises an empirically motivated representation of microtubule growth dynamics, an abstract representation of signal processing, and a feedback learning mechanism that we refer to as adaptive self-stabilization. The growth model mimics the dynamic instability picture of microtubule formation and decomposition, but as modulated by the binding activity of microtubule associated proteins (or MAPs). The signal processing submodel treats each microtubule as a string of linked discrete oscillators capable of propagating signals that are introduced, manipulated, and extracted by bound MAP activity. Adaptive self-stabilization is essentially feedback acting on signal processing capabilities via the growth dynamics. The network is presented with a training set of patterns. If the input-output behavior is satisfactory MAP binding affinity increases, thereby stabilizing the network structure; otherwise the binding affinity decreases, allowing for more structural variation. The results obtained suggest that adaptive capabilities are practically inevitable in microtubule networks, a conclusion strengthened by the fact that the signal processing and growth dynamics mechanisms available in nature are undoubtedly much richer than those represented in the model.     

New perspectives in brain information processing

Brain cortex activity, as variously recorded by scalp or cortical electrodes in the electroencephalography (EEG) frequency range, probably reflects the basic strategy of brain information processing. Various hypotheses have been advanced to interpret this phenomenon, the most popular of which is that suitable combinations of excitatory and inhibitory neurons behave as assemblies of oscillators susceptible to synchronization and desynchronization. Implicit in this view is the assumption that EEG potentials are epiphenomena of action potentials, which is consistent with the argument that voltage variations in dendritic membranes reproduce the postsynaptic effects of targeting neurons. However, this classic argument does not really fit the discovery that firing synchronization over extended brain areas often appears to be established in about 1 ms, which is a small fraction of any EEG frequency component period. This is in contrast with the fact that all computational models of dynamic systems formed by more or less weakly interacting oscillators of near frequencies take more than one period to reach synchronization. The discovery that the somatodendritic membranes of specialized populations of neurons exhibit intrinsic subthreshold oscillations (ISOs) in the EEG frequency range, together with experimental evidence that short inhibitory stimuli are capable of resetting ISO phases, radically changes the scheme described above and paves the way to a novel view. This paper aims to elucidate the nature of ISO generation mechanisms, to explain the reasons for their reliability in starting and stopping synchronized firing, and to indicate their potential in brain information processing. The need for a repertoire of extraneuronal regulation mechanisms, putatively mediated by astrocytes, is also inferred. Lastly, the importance of ISOs for the brain as a parallel recursive machine is briefly discussed.     

Modeling information flow in biological networks

Large-scale molecular interaction networks are being increasingly used to provide a system level view of cellular processes. Modeling communications between nodes in such huge networks as information flows is useful for dissecting dynamical dependences between individual network components. In the information flow model, individual nodes are assumed to communicate with each other by propagating the signals through intermediate nodes in the network. In this paper, we first provide an overview of the state of the art of research in the network analysis based on information flow models. In the second part, we describe our computational method underlying our recent work on discovering dysregulated pathways in glioma. Motivated by applications to inferring information flow from genotype to phenotype in a very large human interaction network, we generalized previous approaches to compute information flows for a large number of instances and also provided a formal proof for the method.     

Incidental processing of biological motion

The successful detection of biological motion can have important consequences for survival. Previous studies have demonstrated the ease and speed with which observers can extract a wide range of information from impoverished dynamic displays in which only an actor's joints are visible. Although it has often been suggested that such biological motion processing can be accomplished relatively automatically, few studies have directly tested this assumption by using behavioral methods. Here we used a flanker paradigm to assess how peripheral "to-be-ignored" walkers affect the processing of a central target walker. Our results suggest that task-irrelevant dynamic figures cannot be ignored and are processed to a level where they influence behavior. These findings provide the first direct evidence that complex dynamic patterns can be processed incidentally, a finding that may have important implications for cognitive, neurophysiological, and computational models of biological motion processing.     

Biphasic constitutive laws for biological interface evolution

 A model of tissue differentiation at the bone–implant interface is proposed. The basic hypothesis of the model is that the mechanical environment determines the tissue differentiation. The stimulus chosen is related to the bone–implant micromotions. Equations governing the evolution of the interfacial tissue are proposed and combined with a finite element code to determine the evolution of the fibrous tissue around prostheses. The model is applied to the case of an idealized hip prosthesis. Received: 28 May 2002 / Accepted: 10 November 2002     

Bayesian processing of vestibular information

Complex self-motion stimulations in the dark can be powerfully disorienting and can create illusory motion percepts. In the absence of visual cues, the brain has to use angular and linear acceleration information provided by the vestibular canals and the otoliths, respectively. However, these sensors are inaccurate and ambiguous. We propose that the brain processes these signals in a statistically optimal fashion, reproducing the rules of Bayesian inference. We also suggest that this processing is related to the statistics of natural head movements. This would create a perceptual bias in favour of low velocity and acceleration. We have constructed a Bayesian model of self-motion perception based on these assumptions. Using this model, we have simulated perceptual responses to centrifugation and off-vertical axis rotation and obtained close agreement with experimental findings. This demonstrates how Bayesian inference allows to make a quantitative link between sensor noise and ambiguities, statistics of head movement, and the perception of self-motion.     

Modelling efficiency in insect olfactory information processing

The olfactory system of insects is essential for the search of food and mates, and weak signals can be detected, amplified and discriminated in a fluctuating environment. The olfactory system also allows for learning and recall of odour memories. Based on anatomical, physiological, and behavioural data from the olfactory system of insects, we have developed a cross-scale dynamical neural network model to simulate the presentation, amplification and discrimination of host plant odours and sex pheromones. In particular, we model how the spatial and temporal patterns of the odour information emerging in the glomeruli of the antennal lobe (AL) rely on the glomerular morphology, the connectivity and the complex dynamics of the AL circuits. We study how weak signals can be amplified, how different odours can be discriminated, based on stochastic (resonance) dynamics and the connectivity of the network. We further investigate the spatial and temporal coding of sex pheromone components and plant volatile compounds, in relation to the glomerular structure, arborizing patterns of the projection neurons (PNs) and timing patterns of the neuronal spiking activity.     

Testing quantum dynamics in genetic information processing

Does quantum dynamics play a role in DNA replication? What type of tests would reveal that? Some statistical checks that distinguish classical and quantum dynamics in DNA replication are proposed.     

NMDA receptors in sensory information processing.

During the past year electrophysiological studies, particularly in the visual and somatosensory systems, have begun to uncover the specific roles played by NMDA receptors in the processing of sensory information. Many of the features of NMDA-receptor-mediated sensory responses reflect known properties of the receptor.     

Terminal chaos for information processing in neurodynamics

New nonlinear phenomenon — terminal chaos caused by failure of the Lipschitz condition at equilibrium points of dynamical systems is introduced. It is shown that terminal chaos has a well organized probabilistic structure which can be predicted and controlled. This gives an opportunity to exploit this phenomenon for information processing. It appears that chaotic states of neurons activity are associated with higher level of cognitive processes such as generalization and abstraction.     

Thermal noise and biological information

Thermal noise limits the efficiency of all information-handling systems. This principle, which is a routine consideration in electronics, is just as fundamental to the handling of highly specific information by living organisms. The rapid basal turnover rates of cells and intracellular proteins and the high energy consumption of regulatory organs, previously unaccounted for, can be explained to a large extent by the need to compensate for the steady loss of essential information due to thermal noise.