Biomedical subjects

Ramakrishna Ramaswamy

Publications and source records attributed to Ramakrishna Ramaswamy.

9 recordsLinked to original sources

PubMed2005

Spectral signatures of the diffusional anomaly in water.

Power spectra for various tagged particle quantities in bulk extended simple point charge model water [H. J. C. Berendsen, J. R. Grigera, and T. P. Straatsma, J. Phys. Chem. 91, 6269 (1987)] are shown to have a regime with 1f(alpha) dependence on frequency f with alpha lying between 1 and 1.5 if the dynamical changes in the particular observable are sensitive to the multiple time-scale behavior of the hydrogen-bond network. The variations in mobility associated with the diffusional anomaly are mirrored in the scaling exponent alpha associated with this multiple time-scale behavior, suggesting that monitoring of 1f(alpha) behavior is a simple and direct method for linking phenomena on three distinctive length and time scales: the local molecular environment, hydrogen-bond network reorganizations, and the diffusivity. Our results indicate that experimental studies of supercooled water to probe the density dependence of 1f(alpha) spectral features, or equivalent stretched exponential behavior in time-correlation functions, will be of interest.

Journal Article↗

PubMed2005

The phase-modulated logistic map.

We study the logistic mapping with the nonlinearity parameter varied through a delayed feedback mechanism. This history dependent modulation through a phaselike variable offers an enhanced possibility for stabilization of periodic dynamics. Study of the system as a function of nonlinearity and modulation parameters reveals new phenomena: In addition to period-doubling and tangent bifurcations, there can be bifurcations where the period increases by unity. These are extensions of crises that arise in nonlinear dynamical systems. Periodic orbits in this system can be systematized via the kneading theory, which in the present case extends the analysis of Metropolis, Stein, and Stein for unimodal maps.

Logistic Models↗

PubMed2005

A robust meta-classification strategy for cancer diagnosis from gene expression data.

One of the major challenges in cancer diagnosis from microarray data is to develop robust classification models which are independent of the analysis techniques used and can combine data from different laboratories. We propose a meta-classification scheme which uses a robust multivariate gene selection procedure and integrates the results of several machine learning tools trained on raw and pattern data. We validate our method by applying it to distinguish diffuse large B-cell lymphoma (DLBCL) from follicular lymphoma (FL) on two independent datasets: the HuGeneFL Affmetrixy dataset of Shipp et al. (www. genome.wi.mit.du/MPR /lymphoma) and the Hu95Av2 Affymetrix dataset (DallaFavera's laboratory, Columbia University). Our meta-classification technique achieves higher predictive accuracies than each of the individual classifiers trained on the same dataset and is robust against various data perturbations. We also find that combinations of p53 responsive genes (e.g., p53, PLK1 and CDK2) are highly predictive of the phenotype.

Algorithms↗

PubMed2004

Fractalization route to strange nonchaotic dynamics.

In the fractalization route for the formation of strange nonchaotic attractors (SNA's) in quasiperiodically driven nonlinear dynamical systems, a smooth torus gradually becomes a fractal as the forcing amplitude is increased, while the Lyapunov exponent remains nonpositive. Using techniques introduced by Kim et al. to identify unstable sets in SNA's, we study torus fractalization in a sequence of approximations wherein the quasiperiodic drive is replaced by periodic forcing of increasing period. This allows us to identify an unstable set embedded in the attractor. In the periodically forced system, we show that there is a cascade of attractor merging crises, and argue that the quasiperiodic analogue of such crises causes fractalization of tori to create SNA's.

Journal Article↗

PubMed2003

Strange nonchaotic attractors in driven excitable systems.

Through quasiperiodic forcing, an excitable system can be driven into a regime of spiking behavior that is both aperiodic and stable. This is a consequence of strange nonchaotic dynamics: the motion of the system is on a fractal attractor and the largest Lyapunov exponent is negative.

Computers↗

PubMed2003

Thermodynamics of critical strange nonchaotic attractors.

The thermodynamic formalism is applied to dynamical attractors which have fractal geometry and on which all Lyapunov exponents are exactly zero. Such critical strange nonchaotic attractors (SNAs) which arise, for example, in the Harper system exhibit a static phase transition in the free energy. The Tsallis nonextensive entropy which is known to characterize the thermodynamics of systems with leading Lyapunov exponent zero is found to be subadditive for the critical states. These properties are shared by other quasiperiodic systems with critical SNAs.

Journal Article↗

PubMed2002

Simplifying the mosaic description of DNA sequences.

By using the Jensen-Shannon divergence, genomic DNA can be divided into compositionally distinct domains through a standard recursive segmentation procedure. Each domain, while significantly different from its neighbors, may, however, share compositional similarity with one or more distant (non-neighboring) domains. We thus obtain a coarse-grained description of the given DNA string in terms of a smaller set of distinct domain labels. This yields a minimal domain description of a given DNA sequence, significantly reducing its organizational complexity. This procedure gives a new means of evaluating genomic complexity as one examines organisms ranging from bacteria to human. The mosaic organization of DNA sequences could have originated from the insertion of fragments of one genome (the parasite) inside another (the host), and we present numerical experiments that are suggestive of this scenario.

Journal Article↗

PubMed2002

Segmentation of genomic DNA through entropic divergence: power laws and scaling.

Genomic DNA is fragmented into segments using the Jensen-Shannon divergence. Use of this criterion results in the fragments being entropically homogeneous to within a predefined level of statistical significance. Application of this procedure is made to complete genomes of organisms from archaebacteria, eubacteria, and eukaryotes. The distribution of fragment lengths in bacterial and primitive eukaryotic DNAs shows two distinct regimes of power-law scaling. The characteristic length separating these two regimes appears to be an intrinsic property of the sequence rather than a finite-size artifact, and is independent of the significance level used in segmenting a given genome. Fragment length distributions obtained in the segmentation of the genomes of more highly evolved eukaryotes do not have such distinct regimes of power-law behavior.

Journal Article↗

PubMed2002

Ab initio gene identification: prokaryote genome annotation with GeneScan and GLIMMER.

We compare the annotation of three complete genomes using the ab initio methods of gene identification GeneScan and GLIMMER. The annotation given in GenBank, the standard against which these are compared, has been made using GeneMark. We find a number of novel genes which are predicted by both methods used here, as well as a number of genes that are predicted by GeneMark, but are not identified by either of the nonconsensus methods that we have used. The three organisms studied here are all prokaryotic species with fairly compact genomes. The Fourier measure forms the basis for an efficient non-consensus method for gene prediction, and the algorithm GeneScan exploits this measure. We have bench-marked this program as well as GLIMMER using 3 complete prokaryotic genomes. An effort has also been made to study the limitations of these techniques for complete genome analysis. GeneScan and GLIMMER are of comparable accuracy insofar as gene-identification is concerned, with sensitivities and specificities typically greater than 0.9. The number of false predictions (both positive and negative) is higher for GeneScan as compared to GLIMMER, but in a significant number of cases, similar results are provided by the two techniques. This suggests that there could be some as-yet unidentified additional genes in these three genomes, and also that some of the putative identifications made hitherto might require re-evaluation. All these cases are discussed in detail.

Algorithms↗