Quantum algorithm for de novo DNA sequence assembly based on quantum walks on graphs.

De novo DNA sequence assembly is based on finding paths in overlap graphs, which is a NP-hard problem. We developed a quantum algorithm for de novo assembly based on quantum walks in graphs. The overlap graph is partitioned repeatedly to smaller graphs that form a hierarchical structure.

Quantum gate algorithm for reference-guided DNA sequence alignment.

Reference-guided DNA sequencing and alignment is an important process in computational molecular biology. The amount of DNA data grows very fast, and many new genomes are waiting to be sequenced while millions of private genomes need to be re-sequenced. Each human genome has 3.

A quantum walks assisted algorithm for peptide and protein folding prediction.

Proteins are considered as the working force of cells. Their functionality is determined by their spatial form. In 1973 Anfinsen proposed that the spatial form is determined by the sequence of amino acids in the protein backbone.

Quantum transport in the FMO photosynthetic light-harvesting complex.

The very high light-harvesting efficiency of natural photosynthetic systems in conjunction with recent experiments, which showed quantum-coherent energy transfer in photosynthetic complexes, raised questions regarding the presence of non-trivial quantum effects in photosynthesis. Grover quantum search, quantum walks, and entanglement have been investigated as possible effects that lead to this efficiency. Here we explain the near-unit photosynthetic efficiency without invoking non-trivial quantum effects.

Simulation of the Dynamics of Bacterial Quorum Sensing.

Quorum sensing (QS) is a signaling mechanism that pathogenic bacteria use to communicate and synchronize the production of exofactors to attack their hosts. Understanding and controlling QS is an important step towards a possible solution to the growing problem of antibiotic resistance. QS is a cooperative effort of a bacterial population in which some of the bacteria do not participate.

Boolean network model of the Pseudomonas aeruginosa quorum sensing circuits.

To coordinate their behavior and virulence and to synchronize attacks against their hosts, bacteria communicate by continuously producing signaling molecules (called autoinducers) and continuously monitoring the concentration of these molecules. This communication is controlled by biological circuits called quorum sensing (QS) circuits. Recently QS circuits and have been recognized as an alternative target for controlling bacterial virulence and infections without the use of antibiotics.

Mechanics and resonance of the cyanobacterial circadian oscillator.

Recent experiments elucidated the structure and function of the cyanobacterial circadian oscillator, which is driven by sunlight intensity variation and therefore by Earth's rotation. It is known that cyanobacteria appeared about 3.5 billion years ago and that Earth's rotational speed is continuously decreasing because of tidal friction.

Quantum gate circuit model of signal integration in bacterial quorum sensing.

Bacteria evolved cell to cell communication processes to gain information about their environment and regulate gene expression. Quorum sensing is such a process in which signaling molecules, called autoinducers, are produced, secreted and detected. In several cases bacteria use more than one autoinducers and integrate the information conveyed by them.

Regulating the quorum sensing signalling circuit to control bacterial virulence: in silico analysis.

Pathogenic bacteria employ a communication mechanism, known as quorum sensing (QS), to obtain information about their cell density and to synchronise their behaviour. Most bacteria species use QS signalling circuits to optimise the secretion of virulence factors that damage their host. Recently, QS has been recognised as a target for antimicrobial drugs that can control bacterial infections.

Quantum mechanical model for information transfer from DNA to protein.

A model for the information transfer from DNA to protein using quantum information and computation techniques is presented. DNA is modeled as the sender and proteins are modeled as the receiver of this information. On the DNA side, a 64-dimensional Hilbert space is used to describe the information stored in DNA triplets (codons).

Reconstruction of DNA sequences using genetic algorithms and cellular automata: towards mutation prediction?

Change of DNA sequence that fuels evolution is, to a certain extent, a deterministic process because mutagenesis does not occur in an absolutely random manner. So far, it has not been possible to decipher the rules that govern DNA sequence evolution due to the extreme complexity of the entire process. In our attempt to approach this issue we focus solely on the mechanisms of mutagenesis and deliberately disregard the role of natural selection.

Microtubules as mechanical force sensors.

Microtubules are polymers of tubulin subunits (dimers) arranged on a hexagonal lattice. Each tubulin dimer comprises two monomers, the alpha-tubulin and beta-tubulin, and can be found in two states. In the first state a mobile negative charge is located into the alpha-tubulin monomer and in the second into the beta-tubulin monomer.

An algorithm for the study of DNA sequence evolution based on the genetic code.

Recent studies of the quantum-mechanical processes in the DNA molecule have seriously challenged the principle that mutations occur randomly. The proton tunneling mechanism causes tautomeric transitions in base pairs resulting in mutations during DNA replication. The meticulous study of the quantum-mechanical phenomena in DNA may reveal that the process of mutagenesis is not completely random.

A cellular automaton model for the study of DNA sequence evolution.

Cellular automata are introduced as a model for DNA structure, function and evolution. DNA is modeled as a one-dimensional cellular automaton with four states per cell. These states are the four DNA bases A, C, T and G.

Constitutive activation of jasmonate signaling in an Arabidopsis mutant correlates with enhanced resistance to Erysiphe cichoracearum, Pseudomonas syringae, and Myzus persicae.

In Arabidopsis spp., the jasmonate (JA) response pathway generally is required for defenses against necrotrophic pathogens and chewing insects, while the salicylic acid (SA) response pathway is generally required for specific, resistance (R) gene-mediated defenses against both biotrophic and necrotrophic pathogens. For example, SA-dependent defenses are required for resistance to the biotrophic fungal pathogen Erysiphe cichoracearum UCSC1 and the bacterial pathogen Pseudomonas syringae pv.

The Arabidopsis mutant cev1 links cell wall signaling to jasmonate and ethylene responses.

Biotic and abiotic stresses stimulate the synthesis of jasmonates and ethylene, which, in turn, induce the expression of genes involved in stress response and enhance defense responses. The cev1 mutant has constitutive expression of stress response genes and has enhanced resistance to fungal pathogens. Here, we show that cev1 plants have increased production of jasmonate and ethylene and that its phenotype is suppressed by mutations that interrupt jasmonate and ethylene signaling.

A model for the influence of the greenhouse effect on insect and microorganism geographical distribution and population dynamics.

A model for the influence of the greenhouse effect on insect and microorganism geographical distribution and population dynamics using cellular automata is presented. Based on this model, an algorithm has been developed and used to determine the geographical distribution and population dynamics of a hypothetical species in an scenario of global warming. The species' initial population distribution is assumed to be Gaussian.