Biomedical subjects

Sarika Mehra

Publications and source records attributed to Sarika Mehra.

4 recordsLinked to original sources

PubMed2006

TimeView: for comparative gene expression analysis.

UNLABELLED: TimeView is a MATLAB program that compares multiple temporal datasets from microarray experiments under two or more conditions, for example, temporal variation of cellular response upon exposure to different drugs. The current paucity of programs designed to efficiently compare and visualise gene expression profiles in such datasets led us to design TimeView, which also enhances data visualisation by plotting the expression profiles of a large number of genes on a single screen. AVAILABILITY: TimeView is available free of charge to all users at http://hugroup.cems.umn.edu/Research/Genomics/Timeview/timeview.htm. To use TimeView, users will require access to the commercial software MATLAB (version 6.5). A help document is available on the TimeView website.

Algorithms↗

PubMed2005

A framework to analyze multiple time series data: a case study with Streptomyces coelicolor.

Transcriptional regulation in differentiating microorganisms is highly dynamic involving multiple and interwinding circuits consisted of many regulatory genes. Elucidation of these networks may provide the key to harness the full capacity of many organisms that produce natural products. A powerful tool evolved in the past decade is global transcriptional study of mutants in which one or more key regulatory genes of interest have been deleted. To study regulatory mutants of Streptomyces coelicolor, we developed a framework of systematic analysis of gene expression dynamics. Instead of pair-wise comparison of samples in different combinations, genomic DNA was used as a common reference for all samples in microarray assays, thus, enabling direct comparison of gene transcription dynamics across different isogenic mutants. As growth and various differentiation events may unfold at different rates in different mutants, the global transcription profiles of each mutant were first aligned computationally to those of the wild type, with respect to the corresponding growth and differentiation stages, prior to identification of kinetically differentially expressed genes. The genome scale transcriptome data from wild type and a DeltaabsA1 mutant of Streptomyces coelicolor were analyzed within this framework, and the regulatory elements affected by the gene knockout were identified. This methodology should find general applications in the analysis of other mutants in our repertoire and in other biological systems.

Anthraquinones↗

PubMed2005

A kinetic model of quantitative real-time polymerase chain reaction.

Real-time polymerase chain reaction (PCR) is one of the most sensitive and accurate methods for quantifying transcript levels especially for those expressed at low abundance. The selective amplification of target DNA over multiple cycles allows its initial concentration to be determined. The amplification rate is a complex interplay of the operating conditions, initial reactant concentrations, and reaction rate constants. Experimentally, the compounded effect of all factors is quantified in terms of an effective efficiency, which is estimated by curve fitting to the amplification data. We present a comprehensive model of PCR to study the effect of various reactant concentrations on the amplification efficiency. The model is used to calculate the kinetic progression of the target DNA concentration with cycle number under conditions when different species are stoichiometrically or kinetically limiting. The reaction efficiency remains constant for the initial cycles. As the primer concentration becomes limiting, the efficiency is marked by a gradual decrease. This is in contrast to a steep decline under nucleotide limiting conditions. Under some conditions, commonly used experimentally, increasing primer concentration has the adverse effect of reducing the final amplified template concentration. This phenomenon seen at times experimentally is explained by the simulation results under rate limiting enzyme concentrations. Primer dimer formation is shown to significantly affect the reaction rates, effective efficiency, and the estimated initial concentrations. This model, by describing the interplay of the many operating variables, will be a useful tool in designing PCR conditions and evaluating its results.

Computer Simulation↗

PubMed2004

A Boolean algorithm for reconstructing the structure of regulatory networks.

Advances in transcriptional analysis offer great opportunities to delineate the structure and hierarchy of regulatory networks in biochemical systems. We present an approach based on Boolean analysis to reconstruct a set of parsimonious networks from gene disruption and over expression data. Our algorithms, Causal Predictor (CP) and Relaxed Causal Predictor (RCP) distinguish the direct and indirect causality relations from the non-causal interactions, thus significantly reducing the number of miss-predicted edges. The algorithms also yield substantially fewer plausible networks. This greatly reduces the number of experiments required to deduce a unique network from the plausible network structures. Computational simulations are presented to substantiate these results. The algorithms are also applied to reconstruct the entire network of galactose utilization pathway in Saccharomyces cerevisiae. These algorithms will greatly facilitate the elucidation of regulatory networks using large scale gene expression profile data.

Algorithms↗