Genetics and Genomics Commons^™

The Tbx20 Homologs Midline And H15 Specify Ventral Fate In The Drosophila Melanogaster Leg, Pia C. Svendson, Ann Formaz-Preston, Sandra M. Leal, William J. Brook

Faculty Publications

Regional fates in the developing limbs of Drosophila melanogaster are controlled by selector gene transcription factors. Ventral fate in the fly leg is specified by the expression of the ligand Wingless. We present evidence that midline and H15, members of the Tbx20 class of T-box transcription factors, are key mediators of the Wingless signal in the formation of the ventral region of the fly leg. midline and H15 are restricted to identical ventral domains of expression through activation by Wingless and repression by the dorsal signal Decapentaplegic. midline and H15 function redundantly and cell autonomously in the formation of …

Bridging Functional Genomics And Toxicogenomics Through Dna Microarrays In A Fish Model, Shuzhao Li

Dissertations

In a case study of finding gene expression signatures for environmental stressors in Cyprinodon variegatus, this dissertation examines several important issues of applying DNA microarray technology to fish toxicogenomics. The most relevant disciplines, fish toxicogenomics and computational systems biology are reviewed in Chapter 1. Chapter 2 reviews major aspects of DNA microarray technology.

On DNA microarrays, even for probes that target the same transcript, large variations are seen in the probe signals. These variations are partly dependent and partly independent on probe sequences. Chapter 3 estimates the sequence independent variation by combining experimental and computational approaches. Chapter 4 and …

Reverse Engineering Of Gene Regulatory Networks For Discovery Of Novel Interactions In Pathways Using Gene Expression Data, Tanwir Habib

Dissertations

A variety of chemicals in the environment have the potential to adversely affect the biological systems. We examined the responses of Rat (Rattus norvegicus) to the RDX exposure and female fathead minnows (FHM, Pimephales promelas) to a model aromatase inhibitor, fadrozole, using a transcriptional network inference approach. Rats were exposed to RDX and fish were exposed to 0 or 30mg/L fadrozole for 8 days. We analyzed gene expression changes using 8000 probes microarrays for rat experiment and 15,000 probe microarrays for fish. We used these changes to infer a transcriptional network. The central nervous system is remarkably plastic in its …

Inferring Gene Regulatory Networks From Time Series Microarray Data, Peng Li

Dissertations

The innovations and improvements in high-throughput genomic technologies, such as DNA microarray, make it possible for biologists to simultaneously measure dependencies and regulations among genes on a genome-wide scale and provide us genetic information. An important objective of the functional genomics is to understand the controlling mechanism of the expression of these genes and encode the knowledge into gene regulatory network (GRN). To achieve this, computational and statistical algorithms are especially needed.

Inference of GRN is a very challenging task for computational biologists because the degree of freedom of the parameters is redundant. Various computational approaches have been proposed for …

A Distribution-Free Convolution Model For Background Correction Of Oligonucleotide Microarray Data, Zhongxue Chen, Monnie Mcgee, Qingzhong Liu, Megan Kong, Youping Deng, Richard H. Scheuermann

Faculty Publications

Introduction

Affymetrix GeneChip^® high-density oligonucleotide arrays are widely used in biological and medical research because of production reproducibility, which facilitates the comparison of results between experiment runs. In order to obtain high-level classification and cluster analysis that can be trusted, it is important to perform various pre-processing steps on the probe-level data to control for variability in sample processing and array hybridization. Many proposed preprocessing methods are parametric, in that they assume that the background noise generated by microarray data is a random sample from a statistical distribution, typically a normal distribution. The quality of the final results depends …

Comparing 2-Nt 3' Overhangs Against Blunt-Ended Sirnas: A Systems Biology Based Study, Preetam Ghosh, Robert Dullea, James E. Fischer, Tom G. Turi, Ronald W. Sarver, Chaoyang Zhang, Kalyan Basu, Sajal K. Das

Faculty Publications

In this study, we formulate a computational reaction model following a chemical kinetic theory approach to predict the binding rate constant for the siRNA-RISC complex formation reaction. The model allowed us to study the potency difference between 2-nt 3' overhangs against blunt-ended siRNA molecules in an RNA interference (RNAi) system. The rate constant predicted by this model was fed into a stochastic simulation of the RNAi system (using the Gillespie stochastic simulator) to study the overall potency effect. We observed that the stochasticity in the transcription/translation machinery has no observable effects in the RNAi pathway. Sustained gene silencing using siRNAs …

An Ensemble Learning Approach To Reverse-Engineering Transcriptional Regulatory Networks From Time-Series Gene Expression Data, Jianhua Ruan, Youping Deng, Edward J. Perkins, Weixiong Zhang

Faculty Publications

Background

One of the most challenging tasks in the post-genomic era is to reconstruct the transcriptional regulatory networks. The goal is to reveal, for each gene that responds to a certain biological event, which transcription factors affect its expression, and how a set of transcription factors coordinate to accomplish temporal and spatial specific regulations.

Results

Here we propose a supervised machine learning approach to address these questions. We focus our study on the gene transcriptional regulation of the cell cycle in the budding yeast, thanks to the large amount of data available and relatively well-understood biology, although the main ideas …

High-Throughput Next-Generation Sequencing Technologies Foster New Cutting-Edge Computing Techniques In Bioinformatics, Mary Qu Yang, Brian D. Athey, Hamid R. Arabnia, Andrew H. Sung, Qingzhong Liu, Jack Y. Yang, Jinghe Mao, Youping Deng

Faculty Publications

The advent of high-throughput next generation sequencing technologies have fostered enormous potential applications of supercomputing techniques in genome sequencing, epi-genetics, metagenomics, personalized medicine, discovery of non-coding RNAs and protein-binding sites. To this end, the 2008 International Conference on Bioinformatics and Computational Biology (Biocomp) - 2008 World Congress on Computer Science, Computer Engineering and Applied Computing (Worldcomp) was designed to promote synergistic inter/multidisciplinary research and education in response to the current research trends and advances. The conference attracted more than two thousand scientists, medical doctors, engineers, professors and students gathered at Las Vegas, Nevada, USA during July 14-17 and received great …