Background: Surprisal analysis is a thermodynamic-like molecular level approach that identifies biological constraints that prevents the entropy from reaching its maximum. To examine the significance of altered gene expression levels in tumorigenesis we apply surprisal analysis to the WI-38 model through its precancerous states. The constraints identified by the analysis are transcription patterns underlying the process of transformation. Each pattern highlights the role of a group of genes that act coherently to define a transformed phenotype. Results: We identify a major transcription pattern that represents a contraction of signaling networks accompanied by induction of cellular proliferation and protein metabolism, which is essential for full transformation. In addition, a more minor, ``tumor signature'' transcription pattern completes the transformation process. The variation with time of the importance of each transcription pattern is determined. Midway through the transformation, at the stage when cells switch from slow to fast growth rate, the major transcription pattern undergoes a total inversion of its weight while the more minor pattern does not contribute before that stage. Conclusions: A similar network reorganization occurs in two very different cellular transformation models: WI-38 and the cervical cancer HF1 models. Our results suggest that despite differences in a list of transcripts expressed in different cancer models the rationale of the network reorganization remains essentially the same.

We experimentally demonstrate classical-optical logic operations in a solid-state memory, coherently driven by variants of stimulated Raman adiabatic passage (STIRAP). Cyclic transfer of atomic populations permits the implementation of a flip-flop or XOR gate, with up to eight optical input operations. Observation of stimulated emission as an additional output channel enables the setup of a STIRAP-driven full adder for three optical input bits (or two input bits and a memory bit).

Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3, ... ), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network.

The attosecond time-scale electronic dynamics induced by an ultrashort laser pulse is computed using a multi configuration time dependent approach in ABCU (C(10)H(19)N), a medium size polyatomic molecule with a rigid cage geometry. The coupling between the electronic states induced by the strong pulse is included in the many electron Hamiltonian used to compute the electron dynamics. We show that it is possible to implement control of the electron density stereodynamics in this medium size molecule by varying the characteristics of the laser pulse, for example by polarizing the electric field either along the N-C axis of the cage, or in the plane perpendicular to it. The excitation produces an oscillatory, non-stationary, electronic state that exhibits localization of the electron density in different parts of the molecule both during and after the pulse. The coherent oscillations of the non-stationary electronic state are also demonstrated through the alternation of the dipole moment of the molecule.

Isotopic effects associated with molecular absorption are discussed with reference to natural phenomena including early solar system processes, Titan and terrestrial atmospheric chemistry, and Martian atmospheric evolution. Quantification of the physicochemical aspects of the excitation and dissociation processes may lead to enhanced understanding of these environments. Here we examine a physical basis for an additional isotope effect during photolysis of molecular nitrogen due to the coupling of valence and Rydberg excited states. The origin of this isotope effect is shown to be the coupling of diabatic electronic states of different bonding nature that occurs after the excitation of these states. This coupling is characteristic of energy regimes where two or more excited states are nearly crossing or osculating. A signature of the resultant isotope effect is a window of rapid variation in the otherwise smooth distribution of oscillator strengths vs. frequency. The reference for the discussion is the numerical solution of the time dependent Schrodinger equation for both the electronic and nuclear modes with the light field included as part of the Hamiltonian. Pumping is to all extreme UV dipole-allowed, valence and Rydberg, excited states of N-2. The computed absorption spectra are convoluted with the solar spectrum to demonstrate the importance of including this isotope effect in planetary, interstellar molecular cloud, and nebular photochemical models. It is suggested that accidental resonance with strong discrete lines in the solar spectrum such as the CIII line at 97.703 nm can also have a marked effect.

Scaling down the size of computing circuits is about to reach the limitations imposed by the discrete atomic structure of matter. Reducing the power requirements and thereby dissipation of integrated circuits is also essential. New paradigms are needed to sustain the rate of progress that society has become used to. Single-atom transistors, SATs, cascaded in a circuit are proposed as a promising route that is compatible with existing technology. We demonstrate the use of quantum degrees of freedom to perform logic operations in a complementary-metal-oxide-semiconductor device. Each SAT performs multilevel logic by electrically addressing the electronic states of a dopant atom. A single electron transistor decodes the physical multivalued output into the conventional binary output. A robust scalable circuit of two concatenated full adders is reported, where by utilizing charge and quantum degrees of freedom, the functionality of the transistor is pushed far beyond that of a simple switch.

High throughput experiments, characteristic of studies in systems biology, produce large output data sets often at different time points or under a variety of related conditions or for different patients. In several recent papers the data is modeled by using a distribution of maximal information-theoretic entropy. We pose the question: `whose entropy' meaning how do we select the variables whose distribution should be compared to that of maximal entropy. The point is that different choices can lead to different answers. Due to the technological advances that allow for the system-wide measurement of hundreds to thousands of events from biological samples, addressing this question is now part of the analysis of systems biology datasets. The analysis of the extent of phosphorylation in reference to the transformation potency of Bcr-Abl fusion oncogene mutants is used as a biological example. The approach taken seeks to use entropy not simply as a statistical measure of dispersion but as a physical, thermodynamic, state function. This highlights the dilemma of what are the variables that describe the state of the signaling network. Is what matters Boolean, spin-like, variables that specify whether a particular phosphorylation site is or is not actually phosphorylated. Or does the actual extent of phosphorylation matter. Last but not least is the possibility that in a signaling network some few specific phosphorylation sites are the key to the signal transduction even though these sites are not at any time abundantly phosphorylated in an absolute sense.

Biological systems that are capable of performing computational operations(1-3) could be of use in bioengineering and nanomedicine(4,5), and DNA and other biomolecules have already been used as active components in biocomputational circuits(6-13). There have also been demonstrations of DNA/RNA-enzyme-based automatons(12), logic control of gene expression(14), and RNA systems for processing of intracellular information(15,16). However, for biocomputational circuits to be useful for applications it will be necessary to develop a library of computing elements, to demonstrate the modular coupling of these elements, and to demonstrate that this approach is scalable. Here, we report the construction of a DNA-based computational platform that uses a library of catalytic nucleic acids (DNAzymes)(10), and their substrates, for the input-guided dynamic assembly of a universal set of logic gates and a half-adder/half-subtractor system. We demonstrate multilayered gate cascades, fan-out gates and parallel logic gate operations. In response to input markers, the system can regulate the controlled expression of anti-sense molecules, or aptamers, that act as inhibitors for enzymes.

Cancer is a multistep process characterized by altered signal transduction, cell growth, and metabolism. To identify such processes in early carcinogenesis we use an information theoretic approach to characterize gene expression quanti. ed as mRNA levels in primary keratinocytes (K) and human papillomavirus 16 (HPV16)-transformed keratinocytes (HF1 cells) from early (E) and late (L) passages and from benzo(a) pyrene-treated (BP) L cells. Our starting point is that biological signaling processes are subjected to the same quantitative laws as inanimate, nonequilibrium chemical systems. Environmental and genomic constraints thereby limit the maximal thermodynamic entropy that the biological system can reach. The procedure uncovers the changes in gene expression patterns in different networks and de. nes the signi. cance of each altered network in the establishment of a particular phenotype. The development of transformed HF1 cells is shown to be represented by one major transcription pattern that is important at all times. Two minor transcription patterns are also identi. ed, one that contributes at early times and a distinguishably different pattern that contributes at later times. All three transcription patterns de. ned by our analysis were validated by gene expression values and biochemical means. The major transcription pattern includes reduced transcripts participating in the apoptotic network and enhanced transcripts participating in cell cycle, glycolysis, and oxidative phosphorylation. The two minor patterns identify genes that are mainly involved in lipid or carbohydrate metabolism.

A Set-Reset machine is the simplest logic circuit with a built-in memory. Its output is a (nonlinear) function of the input and of the state stored in the machine's memory. Here, we report a nanoscale Set-Reset machine operating at room temperature that is based on a 5-nm silicon nanoparticle attached to the inner pore of a stable circular protein. The nanoparticle-protein hybrid can also function as a balanced ternary multiplier. Conductive atomic force microscopy is used to implement the logic input and output operations, and the processing of the logic Set and Reset operations relies on the finite capacitance of the nanoparticle provided by the good electrical isolation given by the protein, thus enabling stability of the logic device states. We show that the machine can be cycled, such that in every successive cycle, the previous state in the memory is retained as the present state. The energy cost of one cycle of computation is minimized to the cost of charging this state.

Point mutations in the phosphorylation domain of the Bcr-Abl fusion oncogene give rise to drug resistance in chronic myelogenous leukemia patients. These mutations alter kinase-mediated signaling function and phenotypic outcome. An information theoretic analysis of the correlation of phosphoproteomic profiling and transformation potency of the oncogene in different mutants is presented. The theory seeks to predict the leukemic transformation potency from the observed signaling by constructing a distribution of maximal entropy of site-specific phosphorylation events. The theory is developed with special reference to systems biology where high throughput measurements are typical. We seek sets of phosphorylation events most contributory to predicting the phenotype by determining the constraints on the signaling system. The relevance of a constraint is measured by how much it reduces the value of the entropy from its global maximum, where all events are equally likely. Application to experimental phospho-proteomics data for kinase inhibitor-resistant mutants shows that there is one dominant constraint and that other constraints are not relevant to a similar extent. This single constraint accounts for much of the correlation of phosphorylation events with the oncogenic potency and thereby usefully predicts the trends in the phenotypic output. An additional constraint possibly accounts for biological fine structure.

We propose charge quantization in electrochemical oxidation-reduction (redox) systems as a route to performing logical operations efficiently and reversibly. The theory is based on the interfacial potential distribution for electrodes coated with electroactive self-assembled molecular films. We monitor the change in the oxidation number by studying the current as a function of the working and reference electrode potentials and of the temperature. Diamond-shaped regions can be defined that delineate the stability of a given redox species as a function of the applied and reference potentials. Using these electrochemical Coulomb diamonds, we then show the principles for the design of a complete set of binary gates and a finite-state set-reset machine. We demonstrate the analogies between these redox systems and nanoscale solid-state systems where the charging energy is finite. Redox systems allow simple logic operations at room temperature because typically the standard potential is higher than the thermal energy.

We provide an experimental proof of principle for a ternary multiplier realized in terms of the charge state of a single dopant atom embedded in a fin field effect transistor (Fin-FET). Robust reading of the logic output is made possible by using two channels to measure the current flowing through the device and the transconductance. A read out procedure that allows for voltage gain is proposed. Long numbers can be multiplied by addressing a sequence of Fin-FET transistors in a row.

Biomolecular logic devices can be applied for sensing and nanomedicine. We built three DNA tweezers that are activated by the inputs H+/OH-; Hg2+/cysteine; nucleic acid linker/complementary antilinker to yield a 16-states finite-state automaton. The outputs of the automata are the configuration of the respective tweezers (opened or closed) determined by observing fluorescence from a fluorophore/quencher pair at the end of the arms of the tweezers. The system exhibits a memory because each current state and output depend not only on the source configuration but also on past states and inputs.

Electrical spectroscopy of a heteroatomic molecule-like shallow-donor pair in silicon can switch the molecule between two ionic states of opposite polarities. We study this charge reorganization theoretically by solving the time-dependent Schroedinger equation on a grid using an effective mass model. The ability to control the charge reorganization by applying external electrical fields is then used to design a cyclable full-adder that operates as a nonlinear finite state machine. The logic operations, equivalent to 32 switches, are implemented by realistic pulse voltages that induce diabatic and adiabatic charge transfer between the wells of the two donors. A RF-SET is used for the read out by charge detection.

A silicon field-effect transistor is operated as a logic circuit by electrically addressing the ground and excited electronic states of an embedded single dopant atom. Experimental results-complemented by analytical and computational calculations-are presented. First, we show how a complete set of binary logic gates can be realized on the same hardware. Then, we show that these gates can be operated in parallel on the very some dopant up to the logic level of a full adder. To use the device not as a switch but as a full logic circuit, we make essential use of the excited electronic states of the dopant and of the ability to shift their energy by gating. The experimental ability to use two channels to measure the current flowing through the device and the conductance (dI/dV) allows for a robust reading of the output of the logic operations.

The time evolution of a non-stationary electronic wave packet created by a sudden ionization is computed using a multi-reference time-dependent approach at a frozen geometry of the nuclei. The methodology is illustrated for the water dimer cation. The electron density as well as the dipole moment are computed as a function of time and used as a probe for the charge migration following upon the sudden removal of a valence electron. It is shown that there is significant purely electronic dynamics on a few femtosecond time scale and that the characteristics of the charge motion depend of the degree of localization of the initial hole formed in the impulsive ionization process. (C) 2009 Elsevier B.V. All rights reserved.