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WASHINGTON UNIVERSITY IN ST LOUIS
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You are viewing titles for WASHINGTON UNIVERSITY IN ST LOUIS in the Bioinformatics available through the UMI Dissertations & Thesis Gradwoorks site
Comparing and contrasting cis-regulatory sequences to identify functional noncoding sequence variation
Techniques for hardware-accelerated parsing for network and bioinformatic applications
Designing filtration strategies for fast sequence annotation
Genome-wide discovery of cis-regulatory RNA motifs and transcriptional regulatory networks
Implications of sequence conservation on selection strength and functionality
Decoding the relationship between promoter sequence and gene expression
Computational systems biology methods to study Alzheimer's disease
Integrating experimental high-throughput transcript detection data into probabilistic gene finding
Accurate docking is achieved by decoupling systematic sampling from scoring
Structural RNA homology search and alignment using covariance models
Modeling and identification of differentially regulated genes using transcriptomics and proteomics data
Integrated genomics of susceptiblity to therapy-related leukemia
Novel algorithms for structural alignment of non-coding RNAs
Genetic analysis of the PI3k/AKT/mTOR signaling pathway
Parallelization of dynamic programming recurrences in computational biology
The Interaction of Cofilin with the Actin Filament
Computational Methods for Accelerated Discovery and Characterization of Genes in Emerging Model Organisms
The advancement of mass spectrometry-based hydroxyl radical protein footprinting: Application of novel analysis methods to model proteins and apolipoprotein E
Protein-DNA recognition models for the homeodomain and C2H2 zinc finger transcription factor families
Systematic identification of independent functional non-coding RNA genes in Oxytricha trifallax
Novel Sequence-Based Method for Identifying Transcription Factor Binding Sites in Prokaryotic Genomes
Bioinformatics for High-throughput Virus Detection and Discovery
Practical Approaches to Biological Network Discovery
A Ranksum Statistics Based Framework to Decipher Transcription Regulation