From microarray to biological networks: Analysis of gene expression profiles.

Powerful new methods, such as expression profiles using cDNA arrays, have been used to monitor changes in gene expression levels as a result of a variety of metabolic, xenobiotic, or pathogenic challenges. This potentially vast quantity of data enables, in principle, the dissection of the complex genetic networks that control the patterns and rhythms of gene expression in the cell. Here we present a general approach to developing dynamic models for analyzing time series of whole-genome expression.

Digital genetics: unravelling the genetic basis of evolution.

Digital genetics, or the genetics of digital organisms, is a new field of research that has become possible as a result of the remarkable power of evolution experiments that use computers. Self-replicating strands of computer code that inhabit specially prepared computers can mutate, evolve and adapt to their environment. Digital organisms make it easy to conduct repeatable, controlled experiments, which have a perfect genetic 'fossil record'.

Isothermal DNA amplification coupled with DNA nanosphere-based colorimetric detection.

We present a simple, rapid method for detecting short DNA sequences that combines a novel isothermal amplification method (EXPAR) with visual, colorimetric readout based on aggregation of DNA-functionalized gold nanospheres. The reaction is initiated by a trigger oligonucleotide, synthetic in nature for this proof-of-principle study, which is exponentially amplified at 55 degrees C and converted to a universal reporter oligonucleotide capable of bridging two sets of DNA-functionalized gold nanospheres. This reaction provides >10(6)-fold amplification/conversion in under 5 min.

Exhaustive Metropolis Monte Carlo sampling and analysis of polyalanine conformations adopted under the influence of hydrogen bonds.

We propose a novel Metropolis Monte Carlo procedure for protein modeling and analyze the influence of hydrogen bonding on the distribution of polyalanine conformations. We use an atomistic model of the polyalanine chain with rigid and planar polypeptide bonds, and elastic alpha carbon valence geometry. We adopt a simplified energy function in which only hard-sphere repulsion and hydrogen bonding interactions between the atoms are considered.

A random polymer model of the statistical significance of structure alignment.

A theory for assessing the statistical significance of structure alignment is developed using a random or Gaussian chain model. In this model, we consider the statistical distribution of the root mean square distance (rmsd) of the alignment between two random chains of equal length and common center of mass (referred to as Case 1). We demonstrate that the rmsd2 is distributed as a sum of independent Gamma variables.

Stochastic fluctuations in gene expression far from equilibrium: Omega expansion and linear noise approximation.

The Omega expansion of the master equation is used to investigate the intrinsic noise in an autoregulatory gene expression system. This Omega expansion provides a mesoscale description of the system and is used to analyze the effect of feedback regulation on intrinsic noise when the system state is far from equilibrium. Using the linear noise approximation, analytic results are obtained for a single gene system with linear feedback that is far from equilibrium.

KMD: an open-source port of the ArrayExpress microarray database.

Unlabelled: The Keck Microarray Database (KMD) is a port of the ArrayExpress database from Oracle to the MySQL environment. The requirements for a locally available, open-source microarray database solution based on ArrayExpress are analysed in this article. The differences between the Oracle and MySQL environments are identified and the method to port to MySQL is described, providing a unified relational database management system (RDBMS) platform for both MIAMExpress and ArrayExpress.

A new scoring function and associated statistical significance for structure alignment by CE.

A new scoring function for assessing the statistical significance of protein structure alignment has been developed. The new scores were tested empirically using the combinatorial extension (CE) algorithm. The significance of a given score was given a p-value by curve-fitting the distribution of the scores generated by a random comparison of proteins taken from the PDB_SELECT database and the structural classification of proteins (SCOP) database.

Molecular clock in neutral protein evolution.

Background: A frequent observation in molecular evolution is that amino-acid substitution rates show an index of dispersion (that is, ratio of variance to mean) substantially larger than one. This observation has been termed the overdispersed molecular clock. On the basis of in silico protein-evolution experiments, Bastolla and coworkers recently proposed an explanation for this observation: Proteins drift in neutral space, and can temporarily get trapped in regions of substantially reduced neutrality.

Cluster analysis of dynamic parameters of gene expression.

Cluster analysis has proven to be a valuable statistical method for analyzing whole genome expression data. Although clustering methods have great utility, they do represent a lower level statistical analysis that is not directly tied to a specific model. To extend such methods and to allow for more sophisticated lines of inference, we use cluster analysis in conjunction with a specific model of gene expression dynamics.

Model system for high-throughput screening of novel human immunodeficiency virus protease inhibitors in Escherichia coli.

Novel human immunodeficiency virus (HIV) protease inhibitors are urgently needed for combating the drug-resistance problem in the fight against AIDS. To facilitate lead discovery of HIV protease inhibitors, we have developed a safe, convenient, and cost-effective Escherichia coli-based assay system. This E.

START lipid/sterol-binding domains are amplified in plants and are predominantly associated with homeodomain transcription factors.

Background: In animals, steroid hormones regulate gene expression by binding to nuclear receptors. Plants lack genes for nuclear receptors, yet genetic evidence from Arabidopsis suggests developmental roles for lipids/sterols analogous to those in animals. In contrast to nuclear receptors, the lipid/sterol-binding StAR-related lipid transfer (START) protein domains are conserved, making them candidates for involvement in both animal and plant lipid/sterol signal transduction.

The Pichia pastoris formaldehyde dehydrogenase gene (FLD1) as a marker for selection of multicopy expression strains of P. pastoris.

The methylotrophic yeast Pichia pastoris is a popular host for the production of a variety of recombinant proteins. We describe the use of a novel selectable marker, the P. pastoris formaldehyde dehydrogenase gene (FLD1) for DNA-mediated transformations of this yeast.

Some asymptotic properties of duplication graphs.

Duplication graphs are graphs that grow by duplication of existing vertices, and are important models of biological networks, including protein-protein interaction networks and gene regulatory networks. Three models of graph growth are studied: pure duplication growth, and two two-parameter models in which duplication forms one element of the growth dynamics. A power-law degree distribution is found to emerge in all three models.

Resolution of multiple ssDNA structures in free solution electrophoresis.

By using high concentrations of buffer, electroosmotic flow within uncoated channels of a microfluidic chip was minimized, allowing the free solution electrophoretic separation of DNA. More importantly, because of the ability to efficiently dissipate heat within these channels, field strengths as high as 600 V/cm could be applied with minimal Joule heating (<2 degrees C). As a result of the higher field strengths, separations within an 8-cm-long channel were achieved within a few minutes.

From microarrays to networks: mining expression time series.

Over the past few years, powerful new methods have been devised that enable researchers to study the expression dynamics of many genes simultaneously (e.g. gene expression profiles using cDNA microarrays).

A duplication growth model of gene expression networks.

Motivation: There has been considerable interest in developing computational techniques for inferring genetic regulatory networks from whole-genome expression profiles. When expression time series data sets are available, dynamic models can, in principle, be used to infer correlative relationships between gene expression levels, which may be causal. However, because of the range of detectable expression levels and the current quality of the data, the predictive nature of such inferred, quantitative models is questionable.

Kinetic studies of human tyrosyl-DNA phosphodiesterase, an enzyme in the topoisomerase I DNA repair pathway.

Tyrosyl-DNA phosphodiesterase (TDP) cleaves the phosphodiester bond linking the active site tyrosine residue of topoisomerase I with the 3' terminus of DNA in topoisomerase I-DNA complexes which accumulate during treatment of cancer with camptothecin. In yeast, TDP mutation confers a 1000-fold hypersensitivity to camptothecin in the presence of an additional mutation of RAD9 gene [Pouliot, J.J.

A Bayesian network model for protein fold and remote homologue recognition.

Motivation: The Bayesian network approach is a framework which combines graphical representation and probability theory, which includes, as a special case, hidden Markov models. Hidden Markov models trained on amino acid sequence or secondary structure data alone have been shown to have potential for addressing the problem of protein fold and superfamily classification.

Results: This paper describes a novel implementation of a Bayesian network which simultaneously learns amino acid sequence, secondary structure and residue accessibility for proteins of known three-dimensional structure.