Genetics and Genomics Commons^™

Sammd: Staphylococcus Aureus Microarray Meta-Database, Vijayaraj Nagarajan, Mohamed O. Elasri

Faculty Publications

Background

Staphylococcus aureus is an important human pathogen, causing a wide variety of diseases ranging from superficial skin infections to severe life threatening infections. S. aureus is one of the leading causes of nosocomial infections. Its ability to resist multiple antibiotics poses a growing public health problem. In order to understand the mechanism of pathogenesis of S. aureus, several global expression profiles have been developed. These transcriptional profiles included regulatory mutants of S. aureus and growth of wild type under different growth conditions. The abundance of these profiles has generated a large amount of data without a uniform annotation …

A Comparative Study Of Different Machine Learning Methods On Microarray Gene Expression Data, Mehdi Pirooznia, Jack Y. Yang, Mary Qu Yang, Youping Deng

Faculty Publications

Background

Several classification and feature selection methods have been studied for the identification of differentially expressed genes in microarray data. Classification methods such as SVM, RBF Neural Nets, MLP Neural Nets, Bayesian, Decision Tree and Random Forrest methods have been used in recent studies. The accuracy of these methods has been calculated with validation methods such as v-fold validation. However there is lack of comparison between these methods to find a better framework for classification, clustering and analysis of microarray gene expression results.

Results

In this study, we compared the efficiency of the classification methods including; SVM, RBF Neural Nets, …

A Hybrid Machine Learning-Based Method For Classifying The Cushing's Syndrome With Comorbid Adrenocortical Lesions, Jack Y. Yang, Mary Qu Yang, Zuojie Lao, Yan Ma, Jianling Li, Youping Deng, Xudong Huang

Faculty Publications

Background

The prognosis for many cancers could be improved dramatically if they could be detected while still at the microscopic disease stage. It follows from a comprehensive statistical analysis that a number of antigens such as hTERT, PCNA and Ki-67 can be considered as cancer markers, while another set of antigens such as P27KIP1 and FHIT are possible markers for normal tissue. Because more than one marker must be considered to obtain a classification of cancer or no cancer, and if cancer, to classify it as malignant, borderline, or benign, we must develop an intelligent decision system that can fullfill …

Improving Prediction Accuracy Of Tumor Classification By Reusing Genes Discarded During Gene Selection, Jack Y. Yang, Guo-Zheng Li, Hao-Hua Meng, Mary Qu Yang, Youping Deng

Faculty Publications

Background

Since the high dimensionality of gene expression microarray data sets degrades the generalization performance of classifiers, feature selection, which selects relevant features and discards irrelevant and redundant features, has been widely used in the bioinformatics field. Multi-task learning is a novel technique to improve prediction accuracy of tumor classification by using information contained in such discarded redundant features, but which features should be discarded or used as input or output remains an open issue.

Results

We demonstrate a framework for automatically selecting features to be input, output, and discarded by using a genetic algorithm, and propose two algorithms: GA-MTL …

Promoting Synergistic Research And Education In Genomics And Bioinformatics, Jack Y. Yang, Mary Qu Yang, Hamid R. Arabnia, Youping Deng

Faculty Publications

Bioinformatics and Genomics are closely related disciplines that hold great promises for the advancement of research and development in complex biomedical systems, as well as public health, drug design, comparative genomics, personalized medicine and so on. Research and development in these two important areas are impacting the science and technology.

High throughput sequencing and molecular imaging technologies marked the beginning of a new era for modern translational medicine and personalized healthcare. The impact of having the human sequence and personalized digital images in hand has also created tremendous demands of developing powerful supercomputing, statistical learning and artificial intelligence approaches to …

Iloop - A Web Application For Two-Channel Microarray Interwoven Loop Design, Mehdi Pirooznia, Ping Gong, Jack Y. Yang, Mary Qu Yang, Edward J. Perkins, Youping Deng

Faculty Publications

Microarray technology is widely applied to address complex scientific questions. However, there remain fundamental issues on how to design experiments to ensure that the resulting data enables robust statistical analysis. Interwoven loop design has several advantages over other designs. However it suffers in the complexity of design. We have implemented an online web application which allows users to find optimal loop designs for two-color microarray experiments. Given a number of conditions (such as treatments or time points) and replicates, the application will find the best possible design of the experiment and output experimental parameters. It is freely available from http://mcbc.usm.edu/iloop …

Batch Blast Extractor: An Automated Blastx Parser Application, Mehdi Pirooznia, Edward J. Perkins, Youping Deng

Faculty Publications

Motivation

BLAST programs are very efficient in finding similarities for sequences. However for large datasets such as ESTs, manual extraction of the information from the batch BLAST output is needed. This can be time consuming, insufficient, and inaccurate. Therefore implementation of a parser application would be extremely useful in extracting information from BLAST outputs.

Results

We have developed a java application, Batch Blast Extractor, with a user friendly graphical interface to extract information from BLAST output. The application generates a tab delimited text file that can be easily imported into any statistical package such as Excel or SPSS for further …

Genomics, Molecular Imaging, Bioinformatics, And Bio-Nano-Info Integration Are Synergistic Components Of Translational Medicine And Personalized Healthcare Research, Jack Y. Yang, Mary Qu Yang, Hamid R. Arabnia, Youping Deng

Faculty Publications

Supported by National Science Foundation (NSF), International Society of Intelligent Biological Medicine (ISIBM), International Journal of Computational Biology and Drug Design and International Journal of Functional Informatics and Personalized Medicine, IEEE 7th Bioinformatics and Bioengineering attracted more than 600 papers and 500 researchers and medical doctors. It was the only synergistic inter/multidisciplinary IEEE conference with 24 Keynote Lectures, 7 Tutorials, 5 Cutting-Edge Research Workshops and 32 Scientific Sessions including 11 Special Research Interest Sessions that were designed dynamically at Harvard in response to the current research trends and advances. The committee was very grateful for the IEEE Plenary Keynote Lectures …

Analyzing Adjuvant Radiotherapy Suggests A Non Monotonic Radio-Sensitivity Over Tumor Volumes, Jack Y. Yang, Andrzej Niemierko, Mary Qu Yang, Youping Deng

Faculty Publications

Background: Adjuvant Radiotherapy (RT) after surgical removal of tumors proved beneficial in long-term tumor control and treatment planning. For many years, it has been well concluded that radio-sensitivities of tumors upon radiotherapy decrease according to the sizes of tumors and RT models based on Poisson statistics have been used extensively to validate clinical data. Results: We found that Poisson statistics on RT is actually derived from bacterial cells despite of many validations from clinical data. However cancerous cells do have abnormal cellular communications and use chemical messengers to signal both surrounding normal and cancerous cells to develop new blood vessels …

Transcriptomic Analysis Of Rdx And Tnt Interactive Sublethal Effects In The Earthworm Eisenia Fetida, Ping Gong, Xin Guan, Laura S. Anouye, Youping Deng, Mehdi Pirooznia, Edward J. Perkins

Faculty Publications

Background

Explosive compounds such as TNT and RDX are recalcitrant contaminants often found co-existing in the environment. In order to understand the joint effects of TNT and RDX on earthworms, an important ecological and bioindicator species at the molecular level, we sampled worms (Eisenia fetida) exposed singly or jointly to TNT (50 mg/kg soil) and RDX (30 mg/kg soil) for 28 days and profiled gene expression in an interwoven loop designed microarray experiment using a 4k-cDNA array. Lethality, growth and reproductive endpoints were measured.

Results

Sublethal doses of TNT and RDX had no significant effects on the survival …

Investigation Of Transmembrane Proteins Using A Computational Approach, Jack Y. Yang, Mary Qu Yang, Keith A. Dunker, Youping Deng, Xudong Huang

Faculty Publications

Background

An important subfamily of membrane proteins are the transmembrane α-helical proteins, in which the membrane-spanning regions are made up of α-helices. Given the obvious biological and medical significance of these proteins, it is of tremendous practical importance to identify the location of transmembrane segments. The difficulty of inferring the secondary or tertiary structure of transmembrane proteins using experimental techniques has led to a surge of interest in applying techniques from machine learning and bioinformatics to infer secondary structure from primary structure in these proteins. We are therefore interested in determining which physicochemical properties are most useful for discriminating transmembrane …

Supervised Learning Method For The Prediction Of Subcellular Localization Of Proteins Using Amino Acid And Amino Acid Pair Composition, Tanwir Habib, Chaoyang Zhang, Jack Y. Yang, Mary Qu Yang, Youping Deng

Faculty Publications

Background

Occurrence of protein in the cell is an important step in understanding its function. It is highly desirable to predict a protein's subcellular locations automatically from its sequence. Most studied methods for prediction of subcellular localization of proteins are signal peptides, the location by sequence homology, and the correlation between the total amino acid compositions of proteins. Taking amino-acid composition and amino acid pair composition into consideration helps improving the prediction accuracy.

Results

We constructed a dataset of protein sequences from SWISS-PROT database and segmented them into 12 classes based on their subcellular locations. SVM modules were trained to …

Transcriptome Profiling Of Saccharomyces Cerevisiae Mutants Lacking C2h2 Zinc Finger Proteins, Jinghe Mao, Tanwir Habib, Ming Shenwu, Baobin Kang, Wilbur Allen, Lashonda Robertson, Jack Y. Yang, Youping Deng

Faculty Publications

Background

The budding yeast Saccharomyces cerevisiae is a eukaryotic organism with extensive genetic redundancy. Large-scale gene deletion analysis has shown that over 80% of the ~6200 predicted genes are nonessential and that the functions of 30% of all ORFs remain unclassified, implying that yeast cells can tolerate deletion of a substantial number of individual genes. For example, a class of zinc finger proteins containing C2H2 zinc fingers in tandem arrays of two or three is predicted to be transcription factors; however, seven of the thirty-one predicted genes of this class are nonessential, and their functions are poorly understood. In this …