Nam Vo

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Papers by Nam Vo

mDAG: A web tool for analyzing, visualizing, and interpreting response patterns in gene expression data with multiple treatments

Advances in Bioscience and Biotechnology, 2013

Background: We previously introduced a method based on post hoc pairwise comparisons to analyze g... more Background: We previously introduced a method based on post hoc pairwise comparisons to analyze gene expression responses. This method utilized directed graphs to represent gene response to all treatment pairs. It has been found useful in identifying structure-activity relationships among drugs and differentiating genes sharing similar functional pathways. Directed graphs are descriptive, visually expressive and can benefit subsequent functional analysis. Results: mDAG is a web-based software package based on this established method for the analysis, visualization, and interpretation of patterns of responses in gene expression data involving multiple treatments. Genes with the same directed graph patterns hypothetically share similar biological function, which may be further analyzed using external tools. To facilitate subsequent functional analysis, several well-known tools have been incorporated into mDAG to help users explore hypotheses about gene function and regulation. This tool is useful for any studies that analyze comparatively response patterns in gene expression data with multiple treatments (chemicals, cell types, etc.). Availability: The (server/personal/demo) software is freely available at http://cetus.cs. memphis.edu/mdag.

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Probabilistic human action prediction and wait-sensitive planning for responsive human-robot collaboration

2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2013

How genome complexity can explain the hardness of aligning reads to genomes

2014 IEEE 4th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS), 2014

Escherichia coli Transcript Cleavage Factors GreA and GreB Stimulate Promoter Escape and Gene Expression In vivo and In vitro

Proceedings of The National Academy of Sciences, 1995

The process of RNA chain initiation by RNA polymerases plays a central role in the regulation of ... more The process of RNA chain initiation by RNA polymerases plays a central role in the regulation of transcription. In this complex phase of transcription, short oligomers are synthesized and released from the enzymepromoter complex in a reaction termed abortive initiation. The polymerase undergoes many cycles of abortive initiation prior to completion of the initiation process, which is signaled by the translocation of the enzyme away from the promoter, release of σ factor, and formation of an elongation complex in which the RNA is stably bound. We have studied the parameters that affect escape from the promoter by Escherichia coli RNA polymerase for the phage T7 A1 promoter, the phage T5 N25 promoter, and the chimeric promoter T5 N25antiDSR. The latter site contains a synthetic initial transcribed region that reduces its ability to synthesize RNA both in vivo and in vitro. Clearance from T5 N25antiDSR can be stimulated up to 10-fold in vitro by addition of the E. coli transcript cleavage factor GreA or GreB, but these factors have little effect on transcription from the normal T7 A1 or T5 N25 promoters. Using an E. coli strain lacking GreA and GreB, we were also able to show stimulation of transcription by the Gre factors from the T5 N25antiDSR promoter in vivo. The stimulation of RNA chain initiation by Gre factors, together with their known biochemical properties in the transcription elongation reaction, suggests some specific models for steps in the transcription initiation reaction.

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An integrated approach for SNP calling based on population of genomes

BMC Bioinformatics, 2014

The identification of genetic variants such as single nucleotide polymorphisms (SNPs) is a critic... more The identification of genetic variants such as single nucleotide polymorphisms (SNPs) is a critical step in many applications based on NGS technologies . Although many SNP calling programs have been developed, it is still challenging to accurately call SNPs, especially when coverage level is low . Moreover, the determination of SNPs, which is performed through many separate steps, requires a careful selection of a diverse set of tools . This can lead to several disadvantages, for example, one cannot incorporate information from the read alignment step into the SNP calling step or vice versa to help improve accuracy of called SNPs.

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Identification of RNA ligands that bind hepatitis C virus polymerase selectively and inhibit its RNA synthesis from the natural viral RNA templates

Virology, 2003

To identify the potential RNA inhibitors of HCV polymerase, we have isolated high-affinity RNA li... more To identify the potential RNA inhibitors of HCV polymerase, we have isolated high-affinity RNA ligands specific to hepatitis C virus (HCV) NS5B protein from a combinatorial RNA library using the Systematic Evolution of Ligands by EXponential enrichment (SELEX) procedure. Thirty-seven selected ligands were classified into eight groups on the basis of their sequence homologies. Most (60%) of the ligands carry the conserved YGUAGR hexamer (Y = pyrimidine, R = purine) at the 5′ end of the 40-nt randomized region, and 74% of the ligands end in (A/C)U at the 3′end. However, strong binding to NS5B required the whole RNA ligand including the flanking conserved nucleotides at both ends. The binding of the selected ligands to NS5B is highly specific and strong, as reflected in their low dissociation rate constants (kd ∼ 10−4 s−1). Analysis of secondary structure by computer program and RNase footprints of the two different aptamers from two most conserved groups revealed RNA structures containing three stem loops with internal bulges. NS5B bound these RNA at a region between the two stem loops from the 5′ -end. Some of these RNA aptamers could serve as a template for the HCV polymerase, but some interfered with the activity of the viral enzyme. These RNA ligands will be useful for further characterization of NS5B-binding properties and, with further modifications, may have potential therapeutic value.

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Exploiting the bootstrap method to analyze patterns of gene expression

BMC Bioinformatics, 2014

High resolution face sequences from a PTZ network camera

Face and Gesture 2011, 2011

We propose here to acquire high resolution sequences of a person's face using a pan-tilt-zoom (PT... more We propose here to acquire high resolution sequences of a person's face using a pan-tilt-zoom (PTZ) network camera. This capability should prove helpful in forensic analysis of video sequences as frames containing faces are tagged, and within a frame, windows containing faces can be retrieved. The system starts in pedestrian detector mode, where the lens angle is set widest, and detects people using a pedestrian detector module. The camera then changes to the region of interest (ROI) focusing mode where the parameters are automatically tuned to put the upper body of the detected person, where the face should appear, in the field of view (FOV). Then, in the face detection mode, the face is detected using a face detector module, and the system switches to an active tracking mode consisting a control loop to actively follow the detected face with two different modules: a tracker to track the face in the image, and a camera control module to adjust the camera parameters. During this loop, our tracker learns online the face appearance in multiple views under all condition changes. It runs robustly at 15 fps and is able to reacquire the face of interest after total occlusion or leaving FOV. We compare our tracker with various state-of-the-art tracking methods in terms of precision and running time performance. Extensive experiments in challenging indoor and outdoor conditions are also demonstrated to validate the complete system.

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Exploiting dependencies of pairwise comparison outcomes to predict patterns of gene response

BMC Bioinformatics, 2014

Background: The analysis of gene expression has played an important role in medical and bioinform... more Background: The analysis of gene expression has played an important role in medical and bioinformatics research. Although it is known that a large number of samples is needed to determine the patterns of gene expression accurately, practical designs of gene expression studies occasionally have insufficient numbers of samples, making it difficult to ascertain true response patterns of variantly expressed genes. Results: We describe an approach to cope with the challenge of predicting true orders of gene response to treatments. We show that true patterns of gene response must be orderable sets. In experiments with few samples, we modify the conventional pairwise comparison tests and increase the significance level a intelligently to deduce orderable patterns, which are most likely true orders of gene response. Additionally, motivated by the fact that a gene can be involved in multiple biological functions, our method further resamples experimental replicates and predicts multiple response patterns for each gene. Using a gene expression data set of Sprague-Dawley rats treated with chemopreventive chemical compounds and DAVID to annotate and validate gene sets, we showed that compared to the conventional method of fixing a, this method increased enrichment significantly. A comparison with hierarchical clustering showed that gene clusters labelled by response patterns produced by our method were much more enriched. One of the clusters contained 3 transcription factors, which hierarchical clustering failed to place into one cluster, that have been found to participate in multiple biological networks. One of the transcription factors is known to play an important role in pathways affected by the studied chemical compounds. Conclusions: This method can be useful in designing cost-effective experiments with small sample sizes. Patterns of highly-variantly expressed genes can be predicted by varying a intelligently. Furthermore, clusters are labeled meaningfully with patterns that describe precisely how genes in such clusters respond to treatments.

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Predicting possible directed-graph patterns of gene expressions in studies involving multiple treatments

Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine - BCB '12, 2012

ABSTRACT Analysis of gene expression data from studies to assess patterns of gene expression to m... more ABSTRACT Analysis of gene expression data from studies to assess patterns of gene expression to multiple treatments is usually challenging due to the inadequacy of sample size. We introduce an approach of representing gene expression response to multiple treatments using directed graphs and establish a relationship between sample size and a graph property known as contractibility. We exploit this relationship to predict patterns of gene response using synthetic replicates generated from real samples to produce most probable patterns for each pattern observed based on experimental replicates. Prediction based on gene expression simulation was validated with 4 different distribution models of gene expression, including Gaussian, Gaussian mixture, Weibull, and log normal. Across all distributions, we showed that predicting comparison outcomes was quite accurate, with accuracy generally above 0.85. Further, we showed how to apply this method to analyze gene responses to multiple treatments with few samples.

Context tracker: Exploring supporters and distracters in unconstrained environments

CVPR 2011, 2011

Visual tracking in unconstrained environments is very challenging due to the existence of several... more Visual tracking in unconstrained environments is very challenging due to the existence of several sources of varieties such as changes in appearance, varying lighting conditions, cluttered background, and frame-cuts. A major factor causing tracking failure is the emergence of regions having similar appearance as the target. It is even more challenging when the target leaves the field of view (FoV) leading the tracker to follow another similar object, and not reacquire the right target when it reappears. This paper presents a method to address this problem by exploiting the context on-the-fly in two terms: Distracters and Supporters. Both of them are automatically explored using a sequential randomized forest, an online template-based appearance model, and local features. Distracters are regions which have similar appearance as the target and consistently cooccur with high confidence score. The tracker must keep tracking these distracters to avoid drifting. Supporters, on the other hand, are local key-points around the target with consistent co-occurrence and motion correlation in a short time span. They play an important role in verifying the genuine target. Extensive experiments on challenging real-world video sequences show the tracking improvement when using this context information. Comparisons with several state-of-the-art approaches are also provided.

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Pattern analysis

Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine - BCB '12, 2012

ABSTRACT Analysis of microarray data with several treatments is an important problem in gene expr... more ABSTRACT Analysis of microarray data with several treatments is an important problem in gene expression studies. We previously introduced a method that employs directed graphs to represent gene response to pairs of treatments. In our method, genes sharing the same directed-graph patterns hypothetically share similar or related biological functions. This method has been applied and found useful in identifying and differentiating genes sharing similar functional pathways. We introduce a web-based tool for analyzing gene response patterns in low-replication, many-treatment microarray data. This software predicts possible directed-graph patterns of gene response to multiple treatments in studies with small number of replicates. This is done by using synthetic replicates in a proper way to produce the most probable patterns for each pattern that is observed based on few experimental replicates. Users can examine the effect and consequence of having different number of synthetic replicates on resulting gene response patterns. To facilitate subsequent functional analyses of gene clusters with the same patterns, the tool incorporates established external tools, such as DAVID and GeneMANIA, which hypothesize gene functions based on user-input gene lists. Although this software has only been applied to microarray data, conceptually, it can be adapted to other high-throughput technologies. The main reason is biological variation in gene response is independent of technologies. Consequently, this tool is useful for any studies that analyze comparatively response patterns in gene expression data with multiple treatments (chemicals, cell types, etc.). The software is freely available at http://cetus.cs.memphis.edu/pa.

Robust Visual Tracking Using Randomized Forest and Online Appearance Model

Lecture Notes in Computer Science, 2011

NT Nguyen, C.-G. Kim, and A. Janiak (Eds.): ACIIDS 2011, LNAI 6592, pp. 212221, 2011. © Springer... more

Exploiting Dependencies of Patterns in Gene Expression Analysis Using Pairwise Comparisons

Lecture Notes in Computer Science, 2013

Context tracker: Exploring supporters and distracters in unconstrained environments

Computer Vision and Pattern Recognition, 2011

Visual tracking in unconstrained environments is very challenging due to the existence of several... more Visual tracking in unconstrained environments is very challenging due to the existence of several sources of varieties such as changes in appearance, varying lighting conditions, cluttered background, and frame-cuts. A major factor causing tracking failure is the emergence of regions having similar appearance as the target. It is even more challenging when the target leaves the field of view (FoV) leading the tracker to follow another similar object, and not reacquire the right target when it reappears. This paper presents a method to address this problem by exploiting the context on-the-fly in two terms: Distracters and Supporters. Both of them are automatically explored using a sequential randomized forest, an online template-based appearance model, and local features. Distracters are regions which have similar appearance as the target and consistently co-occur with high confidence score. The tracker must keep tracking these distracters to avoid drifting. Supporters, on the other hand, are local key-points around the target with consistent co-occurrence and motion correlation in a short time span. They play an important role in verifying the genuine target. Extensive experiments on challenging real-world video sequences show the tracking improvement when using this context information. Comparisons with several state-of-the-art approaches are also provided.

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RandAL: a randomized approach to aligning DNA sequences to reference genomes

BMC Genomics, 2014

Background: The alignment of short reads generated by next-generation sequencers to genomes is an... more Background: The alignment of short reads generated by next-generation sequencers to genomes is an important problem in many biomedical and bioinformatics applications. Although many proposed methods work very well on narrow ranges of read lengths, they tend to suffer in performance and alignment quality for reads outside of these ranges. Results: We introduce RandAL, a novel method that aligns DNA sequences to reference genomes. Our approach utilizes two FM indices to facilitate efficient bidirectional searching, a pruning heuristic to speed up the computing of edit distances, and most importantly, a randomized strategy that enables effective estimation of key parameters. Extensive comparisons showed that RandAL outperformed popular aligners in most instances and was unique in its consistent and accurate performance over a wide range of read lengths and error rates. The software package is publicly available at https://github.com/namsyvo/RandAL. Conclusions: RandAL promises to align effectively and accurately short reads that come from a variety of technologies with different read lengths and rates of sequencing error.

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A randomized algorithm for aligning DNA sequences to reference genomes

2013 IEEE 3rd International Conference on Computational Advances in Bio and medical Sciences (ICCABS), 2013

ABSTRACT Accurately modeling protein loops is critical to predicting three-dimensional structures... more ABSTRACT Accurately modeling protein loops is critical to predicting three-dimensional structures and understanding functions of many proteins. Local interactions between neighboring residue configurations contribute significantly to forming loop conformations. In this paper, we improve our statistical potential energy function (J. Phys. Chem. B 114(5): 1859-1869, 2010) for loop backbone torsion angle conformations by taking influences from the second nearest neighbor effect (SNNE) into consideration. This is based on our study showing that the second nearest neighbors along a protein sequence still have non-negligible influences on the torsion angles conformation of a loop residue while such correlations from further neighbors are much weakened. A biologically meaningful reference state is also introduced. Accuracy and sensitivity enhancements of the new loop torsion potential energy are observed on a decoy set with 4- to 12-residue loop targets.

High resolution face sequences from a PTZ network camera

IEEE International Conference on Automatic Face and Gesture Recognition, 2011

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Using partially ordered sets to represent and predict true patterns of gene response to treatments

BMC Bioinformatics, 2013

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Identification of RNA ligands that bind hepatitis C virus polymerase selectively and inhibit its RNA synthesis from the natural viral RNA templates

Virology, 2003

To identify the potential RNA inhibitors of HCV polymerase, we have isolated high-affinity RNA li... more To identify the potential RNA inhibitors of HCV polymerase, we have isolated high-affinity RNA ligands specific to hepatitis C virus (HCV) NS5B protein from a combinatorial RNA library using the Systematic Evolution of Ligands by EXponential enrichment (SELEX) procedure. Thirty-seven selected ligands were classified into eight groups on the basis of their sequence homologies. Most (60%) of the ligands carry the conserved YGUAGR hexamer (Y ϭ pyrimidine, R ϭ purine) at the 5Ј end of the 40-nt randomized region, and 74% of the ligands end in (A/C)U at the 3Јend. However, strong binding to NS5B required the whole RNA ligand including the flanking conserved nucleotides at both ends. The binding of the selected ligands to NS5B is highly specific and strong, as reflected in their low dissociation rate constants (k d ϳ 10 Ϫ4 s Ϫ1 ). Analysis of secondary structure by computer program and RNase footprints of the two different aptamers from two most conserved groups revealed RNA structures containing three stem loops with internal bulges. NS5B bound these RNA at a region between the two stem loops from the 5Ј -end. Some of these RNA aptamers could serve as a template for the HCV polymerase, but some interfered with the activity of the viral enzyme. These RNA ligands will be useful for further characterization of NS5B-binding properties and, with further modifications, may have potential therapeutic value.

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