Biomedical subjects

Judy N Quong

Publications and source records attributed to Judy N Quong.

3 recordsLinked to original sources

PubMed2005

A signature-based method to distinguish time-of-flight secondary-ion mass spectra from biological samples.

Time-Of-Flight Mass Spectrometry (TOF-SIMS) was used to determine elemental and biomolecular ions from isolated protein samples. We identified a set of 23 mass-to-charge ratio (m/z) peaks that represent signatures for distinguishing biological samples. The 23 peaks were identified by Singular Value Decomposition (SVD) and Canonical Analysis (CA) to find the underlying structure in the complex mass-spectra data sets. From this modified data, SVD was used to identify sets of m/z peaks, and we used these patterns from the TOF-SIMS data to predict the biological source from which individual mass spectra were generated. The signatures were validated using an additional data set different from the initial training set used to identify the signatures. We present a simple method to identify multiple variables required for sample classification based on mass spectra that avoids overfit. This is important in a variety of studies using mass spectrometry, including the ability to identify proteins in complex mixtures and for the identification of new biomarkers.

Biological Products↗

PubMed2005

A three-dimensional model of intercellular calcium signaling in epithelial cells.

We have developed a fully three-dimensional (3D) model of calcium signaling in epithelial cells based on a set of reaction diffusion equations that are solved on a large-scale finite-element code in three dimensions. We have explicitly included the cellular compartments including the cell nucleus, cytoplasm, and gap junctions. The model allows for buffering of free Ca2+, calcium-induced calcium release, and the explicit inclusion of mobile buffers. To make quantitative comparisons to experimental results, we used fluorescence microscopy images of cells to generate an accurate mesh describing cell morphology. We found that Ca2+ wave propagation through the tissue is a function of both initial conditions used to start the wave and various geometrical parameters that affect propagation such as gap junction density and distribution, and the presence of nuclei. The exogenous dyes used in experimental imaging also affect wave propagation.

Animals↗

PubMed2004

Linear fuzzy gene network models obtained from microarray data by exhaustive search.

BACKGROUND: Recent technological advances in high-throughput data collection allow for experimental study of increasingly complex systems on the scale of the whole cellular genome and proteome. Gene network models are needed to interpret the resulting large and complex data sets. Rationally designed perturbations (e.g., gene knock-outs) can be used to iteratively refine hypothetical models, suggesting an approach for high-throughput biological system analysis. We introduce an approach to gene network modeling based on a scalable linear variant of fuzzy logic: a framework with greater resolution than Boolean logic models, but which, while still semi-quantitative, does not require the precise parameter measurement needed for chemical kinetics-based modeling. RESULTS: We demonstrated our approach with exhaustive search for fuzzy gene interaction models that best fit transcription measurements by microarray of twelve selected genes regulating the yeast cell cycle. Applying an efficient, universally applicable data normalization and fuzzification scheme, the search converged to a small number of models that individually predict experimental data within an error tolerance. Because only gene transcription levels are used to develop the models, they include both direct and indirect regulation of genes. CONCLUSION: Biological relationships in the best-fitting fuzzy gene network models successfully recover direct and indirect interactions predicted from previous knowledge to result in transcriptional correlation. Fuzzy models fit on one yeast cell cycle data set robustly predict another experimental data set for the same system. Linear fuzzy gene networks and exhaustive rule search are the first steps towards a framework for an integrated modeling and experiment approach to high-throughput "reverse engineering" of complex biological systems.

Artificial Intelligence↗