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Full-Text Articles in Physical Sciences and Mathematics
A Dynamic Run-Profile Energy-Aware Approach For Scheduling Computationally Intensive Bioinformatics Applications, Sachin Pawaskar, Hesham Ali
A Dynamic Run-Profile Energy-Aware Approach For Scheduling Computationally Intensive Bioinformatics Applications, Sachin Pawaskar, Hesham Ali
Computer Science Faculty Proceedings & Presentations
High Performance Computing (HPC) resources are housed in large datacenters, which consume exorbitant amounts of energy and are quickly demanding attention from businesses as they result in high operating costs. On the other hand HPC environments have been very useful to researchers in many emerging areas in life sciences such as Bioinformatics and Medical Informatics. In an earlier work, we introduced a dynamic model for energy aware scheduling (EAS) in a HPC environment; the model is domain agnostic and incorporates both the deadline parameter as well as energy parameters for computationally intensive applications. Our proposed EAS model incorporates 2-phases. In …
Development And Application Of Comparative Gene Co-Expression Network Methods In Brachypodium Distachyon, Henry David Priest
Development And Application Of Comparative Gene Co-Expression Network Methods In Brachypodium Distachyon, Henry David Priest
Arts & Sciences Electronic Theses and Dissertations
Gene discovery and characterization is a long and labor-intensive process. Gene co-expression network analysis is a long-standing powerful approach that can strongly enrich signals within gene expression datasets to predict genes critical for many cellular functions. Leveraging this approach with a large number of transcriptome datasets does not yield a concomitant increase in network granularity. Independently generated datasets that describe gene expression in various tissues, developmental stages, times of day, and environments can carry conflicting co-expression signals. The gene expression responses of the model C3 grass Brachypodium distachyon to abiotic stress is characterized by a co-expression-based analysis, identifying 22 modules …
Identification Of Small Endogenous Viral Elements Within Host Genomes, Edward C. Davis Jr.
Identification Of Small Endogenous Viral Elements Within Host Genomes, Edward C. Davis Jr.
Boise State University Theses and Dissertations
A parallel string matching software architecture has been developed (incorporating several algorithms) to identify small genetic sequences in large genomes. Endogenous viral elements (EVEs) are sequences originating in the genomes of viruses that have become integrated into the chromosomes of sperm or egg cells of infected hosts, and passed to subsequent generations. EVEs have been identified in all seven classes of viruses and in the species of all kingdoms of life. Viruses from groups V and VI are considered in this thesis, including HIV and Ebola, within host genomes ranging from bacteria to humans. This database of small endogenous viral …
Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang
Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang
COBRA Preprint Series
Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …
A Polyglot Approach To Bioinformatics Data Integration: A Phylogenetic Analysis Of Hiv-1, Steven Reisman, Thomas Hatzopoulous, Konstantin Läufer, George K. Thiruvathukal, Catherine Putonti
A Polyglot Approach To Bioinformatics Data Integration: A Phylogenetic Analysis Of Hiv-1, Steven Reisman, Thomas Hatzopoulous, Konstantin Läufer, George K. Thiruvathukal, Catherine Putonti
Computer Science: Faculty Publications and Other Works
As sequencing technologies continue to drop in price and increase in throughput, new challenges emerge for the management and accessibility of genomic sequence data. We have developed a pipeline for facilitating the storage, retrieval, and subsequent analysis of molecular data, integrating both sequence and metadata. Taking a polyglot approach involving multiple languages, libraries, and persistence mechanisms, sequence data can be aggregated from publicly available and local repositories. Data are exposed in the form of a RESTful web service, formatted for easy querying, and retrieved for downstream analyses. As a proof of concept, we have developed a resource for annotated HIV-1 …
Providing Hands-On Training With Bioinformatics Databases: A Collaboration Between Vcu Libraries & Wright Center For Clinical And Translational Research, Karen H. Gau, Julie A. Arendt, Amy Olex, Aaron R. Wolen
Providing Hands-On Training With Bioinformatics Databases: A Collaboration Between Vcu Libraries & Wright Center For Clinical And Translational Research, Karen H. Gau, Julie A. Arendt, Amy Olex, Aaron R. Wolen
VCU Libraries Faculty and Staff Presentations
Background
With the goal of increasing specialized services for researchers, Virginia Commonwealth University (VCU) Libraries sent its basic science librarians to an intensive training on bioinformatics databases, “A Librarian’s Guide to NCBI.” VCU’s Wright Center for Clinical and Translational Research (Wright CCTR) was expanding the educational component of its bioinformatics support around the same time. This year, the librarians partnered with the Wright CCTR to offer an introductory bioinformatics database workshop introducing researchers to genetic/genomic databases.
Methods
For one week in June, sessions were conducted introducing up to 30 faculty and staff to The Cancer Genome Atlas and NCBI’s Gene, …
Novel Dynamic Partial Reconfiguration Implementations Of The Support Vector Machine Classifier On Fpga, Hanaa Hussain, Khaled Benkrid, Hüseyi̇n Şeker
Novel Dynamic Partial Reconfiguration Implementations Of The Support Vector Machine Classifier On Fpga, Hanaa Hussain, Khaled Benkrid, Hüseyi̇n Şeker
Turkish Journal of Electrical Engineering and Computer Sciences
The support vector machine (SVM) is one of the highly powerful classifiers that have been shown to be capable of dealing with high-dimensional data. However, its complexity increases requirements of computational power. Recent technologies including the postgenome data of high-dimensional nature add further complexity to the construction of SVM classifiers. In order to overcome this problem, hardware implementations of the SVM classifier have been proposed to benefit from parallelism to accelerate the SVM. On the other hand, those implementations offer limited flexibility in terms of changing parameters and require the reconfiguration of the whole device. The latter interrupts the operation …