Life Sciences 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 …

Gene Order Phylogeny And The Evolution Of Methanogens, Haiwei Luo, Zhiyi Sun, William Arndt, Jian Shi, Robert Friedman, Jijun Tang

Faculty Publications

Methanogens are a phylogenetically diverse group belonging to Euryarchaeota. Previously, phylogenetic approaches using large datasets revealed that methanogens can be grouped into two classes, “Class I” and “Class II”. However, some deep relationships were not resolved. For instance, the monophyly of “Class I” methanogens, which consist of Methanopyrales, Methanobacteriales and Methanococcales, is disputable due to weak statistical support. In this study, we use MSOAR to identify common orthologous genes from eight methanogen species and a Thermococcale species (outgroup), and apply GRAPPA and FastME to compute distance-based gene order phylogeny. The gene order phylogeny supports two classes of methanogens, but it …

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 …