Bioinformatics Commons^™

Structure–Activity Relationship-Based Chemical Classification Of Highly Imbalanced Tox21 Datasets, Gabriel Idakwo, Sundar Thangapandian, Joseph Luttrell, Yan Li, Nan Wang, Zhaoxian Zhou, Huixiao Hong, Bei Yang, Chaoyang Zhang, Ping Gong

Faculty Publications

The specificity of toxicant-target biomolecule interactions lends to the very imbalanced nature of many toxicity datasets, causing poor performance in Structure–Activity Relationship (SAR)-based chemical classification. Undersampling and oversampling are representative techniques for handling such an imbalance challenge. However, removing inactive chemical compound instances from the majority class using an undersampling technique can result in information loss, whereas increasing active toxicant instances in the minority class by interpolation tends to introduce artificial minority instances that often cross into the majority class space, giving rise to class overlapping and a higher false prediction rate. In this study, in order to improve the …

Scl: A Lattice-Based Approach To Infer 3d Chromosome Structures From Single-Cell Hi-C Data, Hao Zhu, Zheng Wang

Student Publications

Motivation: In contrast to population-based Hi-C data, single-cell Hi-C data are zero-inflated and do not indicate the frequency of proximate DNA segments. There are a limited number of computational tools that can model the 3D structures of chromosomes based on single-cell Hi-C data.

Results: We developed single-cell lattice (SCL), a computational method to reconstruct 3D structures of chromosomes based on single-cell Hi-C data. We designed a loss function and a 2 D Gaussian function specifically for the characteristics of single-cell Hi-C data. A chromosome is represented as beads-on-a-string and stored in a 3 D cubic lattice. Metropolis–Hastings simulation …

In Silico Identification Of Genetic Mutations Conferring Resistance To Acetohydroxyacid Synthase Inhibitors: A Case Study Of Kochia Scoparia, Yan Li, Michael D. Netherland, Chaoyang Zhang, Huixiao Hong, Ping Gong

Faculty Publications

Mutations that confer herbicide resistance are a primary concern for herbicide-based chemical control of invasive plants and are often under-characterized structurally and functionally. As the outcome of selection pressure, resistance mutations usually result from repeated long-term applications of herbicides with the same mode of action and are discovered through extensive field trials. Here we used acetohydroxyacid synthase (AHAS) of Kochia scoparia (KsAHAS) as an example to demonstrate that, given the sequence of a target protein, the impact of genetic mutations on ligand binding could be evaluated and resistance mutations could be identified using a biophysics-based computational approach. Briefly, …

Predicting Protein Residue-Residue Contacts Using Random Forests And Deep Networks, Joseph Luttrell Iv, Tong Liu, Chaoyang Zhang, Zheng Wang

Faculty Publications

Background: The ability to predict which pairs of amino acid residues in a protein are in contact with each other offers many advantages for various areas of research that focus on proteins. For example, contact prediction can be used to reduce the computational complexity of predicting the structure of proteins and even to help identify functionally important regions of proteins. These predictions are becoming especially important given the relatively low number of experimentally determined protein structures compared to the amount of available protein sequence data.

Results: Here we have developed and benchmarked a set of machine learning methods …

Similarities And Differences Between Variants Called With Human Reference Genome Hg19 Or Hg38, Bohu Pan, Rebecca Kusko, Wenming Xiao, Yuantin Zheng, Zhichao Liu, Chunlin Xiao, Sugunadevi Sakkiah, Wenjing Guo, Ping Gong, Chaoyang Zhang, Weigong Ge, Leming Shi, Weida Tong, Huixiao Hong

Faculty Publications

Background: Reference genome selection is a prerequisite for successful analysis of next generation sequencing (NGS) data. Current practice employs one of the two most recent human reference genome versions: HG19 or HG38. To date, the impact of genome version on SNV identification has not been rigorously assessed.

Results: We conducted analysis comparing the SNVs identified based on HG19 vs HG38, leveraging whole genome sequencing (WGS) data from the genome-in-a-bottle (GIAB) project. First, SNVs were called using 26 different bioinformatics pipelines with either HG19 or HG38. Next, two tools were used to convert the called SNVs between HG19 and …

Deep Learning Architectures For Multi-Label Classification Of Intelligent Health Risk Prediction, Andrew Maxwell, Runzhi Li, Bei Yang, Heng Weng, Aihua Ou, Huixiao Hong, Zhaoxian Zhou, Ping Gong, Chaoyang Zhang

Faculty Publications

No abstract provided.

Proceedings Of The 2014 Midsouth Computational Biology And Bioinformatics Society (Mcbios) Conference, Jonathan D. Wren, Mikhail G. Dozmorov, Dennis Burian, Andy Perkins, Chaoyang Zhang, Peter Hoyt, Rakesh Kaundal

Faculty Publications

No abstract provided.

Smoq: A Tool For Predicting The Absolute Residue-Specific Quality Of A Single Protein Model With Support Vector Machine, Renzhi Cao, Zheng Wang, Yiheng Wang, Jianlin Cheng

Faculty Publications

Background: It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models.

Results: We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to …

Differential Reconstructed Gene Interaction Networks For Deriving Toxicity Threshold In Chemical Risk Assessment, Yi Yang, Andrew Maxwell, Xiaowei Zhang, Nan Wang, Edward J. Perkins, Chaoyang Zhang, Ping Gong

Faculty Publications

Background: Pathway alterations reflected as changes in gene expression regulation and gene interaction can result from cellular exposure to toxicants. Such information is often used to elucidate toxicological modes of action. From a risk assessment perspective, alterations in biological pathways are a rich resource for setting toxicant thresholds, which may be more sensitive and mechanism-informed than traditional toxicity endpoints. Here we developed a novel differential networks (DNs) approach to connect pathway perturbation with toxicity threshold setting.

Methods: Our DNs approach consists of 6 steps: time-series gene expression data collection, identification of altered genes, gene interaction network reconstruction, differential …

Transcriptomic Profiles Of Peripheral White Blood Cells In Type Ii Diabetes And Racial Differences In Expression Profiles, Jinghe Mao, Junmei Ai, Xinchun Zhou, Ming Shenwu, Manuel Ong Jr., Marketta Blue, Jasmine T. Washington, Xiaonan Wang, Youping Deng

Faculty Publications

Background: Along with obesity, physical inactivity, and family history of metabolic disorders, African American ethnicity is a risk factor for type 2 diabetes (T2D) in the United States. However, little is known about the differences in gene expression and transcriptomic profiles of blood in T2D between African Americans (AA) and Caucasians (CAU), and microarray analysis of peripheral white blood cells (WBCs) from these two ethnic groups will facilitate our understanding of the underlying molecular mechanism in T2D and identify genetic biomarkers responsible for the disparities.

Results: A whole human genome oligomicroarray of peripheral WBCs was performed on 144 …

Refnetbuilder: A Platform For Construction Of Integrated Reference Gene Regulatory Networks From Expressed Sequence Tags, Ying Li, Ping Gong, Edward J. Perkins, Chaoyang Zhang, Nan Wang

Faculty Publications

Background: Gene Regulatory Networks (GRNs) provide integrated views of gene interactions that control biological processes. Many public databases contain biological interactions extracted from experimentally validated literature reports, but most furnish only information for a few genetic model organisms. In order to provide a bioinformatic tool for researchers who work with non-model organisms, we developed RefNetBuilder, a new platform that allows construction of putative reference pathways or GRNs from expressed sequence tags (ESTs).

Results: RefNetBuilder was designed to have the flexibility to extract and archive pathway or GRN information from public databases such as the Kyoto Encyclopedia of Genes …

The Proteogenomic Mapping Tool, William S. Sanders, Nan Wang, Susan M. Bridges, Brandon M. Malone, Yoginder S. Dandass, Fiona M. Mccarthy, Bindu Nanduri, Mark L. Lawrence, Shane C. Burgess

Faculty Publications

Background: High-throughput mass spectrometry (MS) proteomics data is increasingly being used to complement traditional structural genome annotation methods. To keep pace with the high speed of experimental data generation and to aid in structural genome annotation, experimentally observed peptides need to be mapped back to their source genome location quickly and exactly. Previously, the tools to do this have been limited to custom scripts designed by individual research groups to analyze their own data, are generally not widely available, and do not scale well with large eukaryotic genomes.

Results: The Proteogenomic Mapping Tool includes a Java implementation of …

Quail Genomics: A Knowledgebase For Northern Bobwhite, Arun Rawat, Kurt A. Gust, Mohamed O. Elasri, Edward J. Perkins

Faculty Publications

Background

The Quail Genomics knowledgebase (http://www.quailgenomics.info) has been initiated to share and develop functional genomic data for Northern bobwhite (Colinus virginianus). This web-based platform has been designed to allow researchers to perform analysis and curate genomic information for this non-model species that has little supporting information in GenBank.

Description

A multi-tissue, normalized cDNA library generated for Northern bobwhite was sequenced using 454 Life Sciences next generation sequencing. The Quail Genomics knowledgebase represents the 478,142 raw ESTs generated from the sequencing effort in addition to assembled nucleotide and protein sequences including 21,980 unigenes annotated with meta-data. A …

Time Lagged Information Theoretic Approaches To The Reverse Engineering Of Gene Regulatory Networks, Vijender Chaitankar, Preetam Ghosh, Edward J. Perkins, Ping Gong, Youping Deng, Chaoyang Zhang

Faculty Publications

Background: A number of models and algorithms have been proposed in the past for gene regulatory network (GRN) inference; however, none of them address the effects of the size of time-series microarray expression data in terms of the number of time-points. In this paper, we study this problem by analyzing the behaviour of three algorithms based on information theory and dynamic Bayesian network (DBN) models. These algorithms were implemented on different sizes of data generated by synthetic networks. Experiments show that the inference accuracy of these algorithms reaches a saturation point after a specific data size brought about by …

Dynamics Of Protofibril Elongation And Association Involved In Aβ42 Peptide Aggregation In Alzheimer's Disease, Preetam Ghosh, Amit Kumar, Bhaswati Datta, Vijayaraghavan Rangachari

Faculty Publications

Background: The aggregates of a protein called, ‘Aβ’ found in brains of Alzheimer’s patients are strongly believed to be the cause for neuronal death and cognitive decline. Among the different forms of Aβ aggregates, smaller aggregates called ‘soluble oligomers’ are increasingly believed to be the primary neurotoxic species responsible for early synaptic dysfunction. Since it is well known that the Aβ aggregation is a nucleation dependant process, it is widely believed that the toxic oligomers are intermediates to fibril formation, or what we call the ‘on-pathway’ products. Modeling of Aβ aggregation has been of intense investigation during the last …

Incorporating Genomics And Bioinformatics Across The Life Sciences Curriculum, Jayna L. Ditty, Christopher A. Kvaal, Brad Goodner, Sharyn K. Freyermuth, Cheryl Bailey, Robert A. Britton, Stuart G. Gordon, Sabine Heinhorst, Kelyenne Reed, Zhaohui Xu, Erin R. Sanders-Lorenz, Seth Axen, Edwin Kim, Mitrick Johns, Kathleen Scott, Cheryl A. Kerfeld

Faculty Publications

No abstract provided.

Feature Selection And Classification Of Maqc-Ii Breast Cancer And Multiple Myeloma Microarray Gene Expression Data, Qingzhong Liu, Andrew H. Sung, Zhongxue Chen, Jianzhong Liu, Xudong Huang, Youping Deng

Faculty Publications

Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray data for the purpose of, e.g., predicting gene-disease association, feature selection is very important because it provides a way to handle the high dimensionality by exploiting information redundancy induced by associations among genetic markers. Judicious feature selection in microarray data analysis can result in significant reduction of cost while maintaining or improving the classification or prediction accuracy of learning machines that are employed to sort …

Novel Implementation Of Conditional Co-Regulation By Graph Theory To Derive Co-Expressed Genes From Microarray Data, Arun Rawat, Georg J. Seifert, Youping Deng

Faculty Publications

Background

Most existing transcriptional databases like Comprehensive Systems-Biology Database (CSB.DB) and Arabidopsis Microarray Database and Analysis Toolbox (GENEVESTIGATOR) help to seek a shared biological role (similar pathways and biosynthetic cycles) based on correlation. These utilize conventional methods like Pearson correlation and Spearman rank correlation to calculate correlation among genes. However, not all are genes expressed in all the conditions and this leads to their exclusion in these transcriptional databases that consist of experiments performed in varied conditions. This leads to incomplete studies of co-regulation among groups of genes that might be linked to the same or related biosynthetic pathway.

Results …

Cloning, Analysis And Functional Annotation Of Expressed Sequence Tags From The Earthworm Eisenia Fetida, Mehdi Pirooznia, Ping Gong, Xin Guan, Laura S. Inouye, Kuan Yang, Edward J. Perkins, Youping Deng

Faculty Publications

Background

Eisenia fetida, commonly known as red wiggler or compost worm, belongs to the Lumbricidae family of the Annelida phylum. Little is known about its genome sequence although it has been extensively used as a test organism in terrestrial ecotoxicology. In order to understand its gene expression response to environmental contaminants, we cloned 4032 cDNAs or expressed sequence tags (ESTs) from two E. fetida libraries enriched with genes responsive to ten ordnance related compounds using suppressive subtractive hybridization-PCR.

Results

A total of 3144 good quality ESTs (GenBank dbEST accession number EH669363–EH672369 and EL515444–EL515580) were obtained from the raw clone …

Comparison Of Probabilistic Boolean Network And Dynamic Bayesian Network Approaches For Inferring Gene Regulatory Networks, Peng Li, Chaoyang Zhang, Edward J. Perkins, Ping Gong, Youping Deng

Faculty Publications

Background: The regulation of gene expression is achieved through gene regulatory networks (GRNs) in which collections of genes interact with one another and other substances in a cell. In order to understand the underlying function of organisms, it is necessary to study the behavior of genes in a gene regulatory network context. Several computational approaches are available for modeling gene regulatory networks with different datasets. In order to optimize modeling of GRN, these approaches must be compared and evaluated in terms of accuracy and efficiency.

Results: In this paper, two important computational approaches for modeling gene regulatory networks, …

Structure And Function Predictions Of The Msa Protein In Staphylococcus Aureus, Vijayaraj Nagarajan, Mohamed O. Elasri

Faculty Publications

Background

Staphylococcus aureus is a human pathogen that causes a wide variety of life-threatening infections using a large number of virulence factors. One of the major global regulators used by S. aureus is the staphylococcal accessory regulator (sarA). We have identified and characterized a new gene (modulator of sarA: msa) that modulates the expression of sarA. Genetic and functional analysis shows that msa has a global effect on gene expression in S. aureus. However, the mechanism of Msa function is still unknown. Function predictions of Msa are complicated by the fact that it does …

Development Of Computations In Bioscience And Bioinformatics And Its Application: Review Of The Symposium Of Computations In Bioinformatics And Bioscience (Scbb06), Youping Deng, Jun Ni, Chaoyang Zhang

Faculty Publications

The first symposium of computations in bioinformatics and bioscience (SCBB06) was held in Hangzhou, China on June 21-22, 2006. Twenty-six peer-reviewed papers were selected for publication in this special issue of BMC Bioinformatics. These papers cover a broad range of topics including bioinformatics theories, algorithms, applications and tool development. The main technical topics contain gene expression analysis, sequence analysis, genome analysis, phylogenetic analysis, gene function prediction, molecular interaction and system biology, genetics and population study, immune strategy, protein structure prediction and proteomics.

Svm Classifier: A Comprehensive Java Interface For Support Vector Machine Classification Of Microarray Data, Mehdi Pirooznia, Youping Deng

Faculty Publications

Motivation

Graphical user interface (GUI) software promotes novelty by allowing users to extend the functionality. SVM Classifier is a cross-platform graphical application that handles very large datasets well. The purpose of this study is to create a GUI application that allows SVM users to perform SVM training, classification and prediction.

Results

The GUI provides user-friendly access to state-of-the-art SVM methods embodied in the LIBSVM implementation of Support Vector Machine. We implemented the java interface using standard swing libraries.

We used a sample data from a breast cancer study for testing classification accuracy. We achieved 100% accuracy in classification among the …

A Fourier Transformation Based Method To Mine Peptide Space For Antimicrobial Activity, Vijayaraj Nagarajan, Navodit Kaushik, Beddhu Murali, Chaoyang Zhang, Sanyogita Lakhera, Mohamed O. Elasri, Youping Deng

Faculty Publications

Background

Naturally occurring antimicrobial peptides are currently being explored as potential candidate peptide drugs. Since antimicrobial peptides are part of the innate immune system of every living organism, it is possible to discover new candidate peptides using the available genomic and proteomic data. High throughput computational techniques could also be used to virtually scan the entire peptide space for discovering out new candidate antimicrobial peptides.

Result

We have identified a unique indexing method based on biologically distinct characteristic features of known antimicrobial peptides. Analysis of the entries in the antimicrobial peptide databases, based on our indexing method, using Fourier transformation …

Parallelization Of Multicategory Support Vector Machines (Pmc- Svm) For Classifying Microarray Data, Chaoyang Zhang, Peng Li, Arun Rajendran, Youping Deng, Dequan Chen

Faculty Publications

Background: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the process of generating models in traditional multicategory support vector machines for large datasets is very computationally intensive, there is a need to improve the performance using high performance computing techniques.

Results: In this paper, Parallel Multicategory Support Vector Machines (PMC-SVM) have been developed based on the sequential minimum optimization-type decomposition method for support vector machines (SMO-SVM). It was implemented in parallel using MPI and C++ libraries and executed on both shared memory supercomputer and Linux cluster …

Identification Of New Members Of Hydrophobin Family Using Primary Structure Analysis, Kuan Yang, Youping Deng, Chaoyang Zhang, Mohamed O. Elasri

Faculty Publications

Background

Hydrophobins are fungal proteins that can turn into amphipathic membranes at hydrophilic/hydrophobic interfaces by self-assembly. The assemblages by Class I hydrophobins are extremely stable and possess the remarkable ability to change the polarity of the surface. One of its most important industrial applications is its usage as paint. Without detailed knowledge of the 3D structure and self-assembly principles of hydrophobins, it is difficult to make significant progress in furthering its research.

Results

In order to provide useful information to hydrophobin researchers, we analyzed primary structure of hydrophobins to gain more insight about these proteins. In this paper, we presented …

Incremental Genetic K-Means Algorithm And Its Application In Gene Expression Data Analysis, Yi Lu, Shiyong Lu, Farhad Fotouhi, Youping Deng, Susan J. Brown

Faculty Publications

Background

In recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms such as K-means, hierarchical clustering, SOM, etc, genes are partitioned into groups based on the similarity between their expression profiles. In this way, functionally related genes are identified. As the amount of laboratory data in molecular biology grows exponentially each year due to advanced technologies such as Microarray, new efficient and effective methods for clustering must be developed to process this growing amount of biological data.

Results

In this paper, we propose a new clustering algorithm, …