iPat: intelligent prediction and association tool for genomic research

doi:10.1093/bioinformatics/bty015

Title: iPat: intelligent prediction and association tool for genomic research

Full Record
Other Related Research

Abstract

Not provided.

Authors:

^[1]; Zhang, Zhiwu ^[1]; Hancock, John

Department of Crop and Soil Sciences, Washington State University, Pullman, WA, USA

Publication Date:: 2018-01-11

Research Org.:: Univ. of Idaho, Moscow, ID (United States)

Sponsoring Org.:: USDOE Office of Science (SC)

OSTI Identifier:: 1540587

DOE Contract Number:: SC0016366

Resource Type:: Journal Article

Journal Name:: Bioinformatics

Additional Journal Information:: Journal Volume: 34; Journal Issue: 11; Journal ID: ISSN 1367-4803

Publisher:: Oxford University Press

Country of Publication:: United States

Language:: English

Subject:: Biochemistry & Molecular Biology; Biotechnology & Applied Microbiology; Computer Science; Mathematical & Computational Biology; Mathematics

Citation Formats


                    Chen, Chunpeng James, Zhang, Zhiwu, and Hancock, John. iPat: intelligent prediction and association tool for genomic research.  United States: N. p., 2018. 
        Web.  doi:10.1093/bioinformatics/bty015.

Copy to clipboard


                    Chen, Chunpeng James, Zhang, Zhiwu, & Hancock, John. iPat: intelligent prediction and association tool for genomic research.  United States.  doi:10.1093/bioinformatics/bty015.

Copy to clipboard


                    Chen, Chunpeng James, Zhang, Zhiwu, and Hancock, John. Thu .  
        "iPat: intelligent prediction and association tool for genomic research".  United States.  doi:10.1093/bioinformatics/bty015.

Copy to clipboard


                    
@article{osti_1540587,

  title        = {iPat: intelligent prediction and association tool for genomic research},

  author       = {Chen, Chunpeng James and Zhang, Zhiwu and Hancock, John},

  abstractNote = {Not provided.},

  doi          = {10.1093/bioinformatics/bty015},

  journal      = {Bioinformatics},

  issn         = {1367-4803},

  number       = 11,

  volume       = 34,

  place        = {United States},

  year         = {2018},

  month        = {1}

}

Copy to clipboard

Journal Article:

DOI: 10.1093/bioinformatics/bty015

Other availability

Find in Google Scholar

Search WorldCat to find libraries that may hold this journal

Save / Share:

Export Metadata

Save to My Library

Similar records in OSTI.GOV collections:

DEVELOPMENT OF A VIRTUAL INTELLIGENCE TECHNIQUE FOR THE UPSTREAM OIL INDUSTRY

Technical Report Iraj A. Salehi ; Shahab D. Mohaghegh ; Samuel Ameri

The objective of the research and development work reported in this document was to develop a Virtual Intelligence Technique for optimization of the Preferred Upstream Management Practices (PUMP) for the upstream oil industry. The work included the development of a software tool for identification and optimization of the most influential parameters in upstream common practices as well as geological, geophysical and reservoir engineering studies. The work was performed in cooperation with three independent producing companies--Newfield Exploration, Chesapeake Energy, and Triad Energy--operating in the Golden Trend, Oklahoma. In order to protect data confidentiality, these companies are referred to as Company One,more »« less
DOI: 10.2172/835587

Full Text Available
Polynuclear Aromatic Hydrocarbons with Curved Surfaces: Buckyballs

Technical Report Sygula, Andrzej

The discovery of a new allotropic form of elemental carbon – the fullerenes – and subsequently other novel forms of elemental carbon with pyramidalized surfaces, most notably single-walled and multi-walled carbon nanotubes, introduced a novel structural motif to the polycyclic aromatic hydrocarbons (PAHs) with nonplanar surfaces. Our research program supported by BES DOE grant DE-FG02-04ER15514 has dealt with the synthesis, structural studies, and chemistry of the novel curved-surface PAHs with carbon frameworks structurally related to fullerenes. They are referred to as “buckybowls”. We prepared several new buckybowls and, even more importantly, developed the efficient, gram-scale synthetic methodologies for the preparationmore »« less
DOI: 10.2172/1335963

Full Text Available
Intelligent Solar Energy Devices Cybersecurity System

Technical Report Milovanov, Alexander

An advanced tool to improve the cybersecurity of electronic devices associated with the generation of solar energy such as inverters, DC-DC optimizers, and smart meters is needed. This tool should ensure access-control, authorization, authentication, confidentiality, integrity, availability, and non-repudiation for the future smart grid as well. To address this need, Physical Optics Corporation (POC) has completed a Phase I Small Business Innovative Research (SBIR) project: the Intelligent Solar Energy Devices Cybersecurity (ISEDEC) software tool. ISEDEC is based on an integration of (1) POC’s semi-supervised decision-making mechanism that provides self-learning capabilities, (2) cognitive data analytics for anomaly detection/prediction based on anmore »« less
Intelligent Buildings of the Future: Cyberaware, Deep Learning Powered, and Human Interacting

Journal Article Manic, Milos ; Amarasinghe, Kasun ; Rodriguez-Andina, Juan ; ... - IEEE Industrial Electronics Magazine

This study discuss, intelligent buildings are quickly becoming cohesive and integral entities of cyber-physical ecosystems. Modern buildings adapt to internal and external elements and thrive on ever increasing data sources such as ubiquitous smart devices and sensors while mimicking various approaches previously known in software, hardware, and bio inspired systems. This article provides an overview of intelligent buildings of the future from a range of perspectives. First, a brief overview of prospects of U.S. and world energy consumption, concepts of smart buildings as integral entities of smart grids is presented. This is followed by a discussion of the role ofmore »« less
Cited by 9
DOI: 10.1109/MIE.2016.2615575

Full Text Available
Using deep RNA sequencing for the structural annotation of the laccaria bicolor mycorrhizal transcriptome.

Journal Article Larsen, P. E. ; Trivedi, G. ; Sreedasyam, A. ; ... - PLoS ONE

Accurate structural annotation is important for prediction of function and required for in vitro approaches to characterize or validate the gene expression products. Despite significant efforts in the field, determination of the gene structure from genomic data alone is a challenging and inaccurate process. The ease of acquisition of transcriptomic sequence provides a direct route to identify expressed sequences and determine the correct gene structure. We developed methods to utilize RNA-seq data to correct errors in the structural annotation and extend the boundaries of current gene models using assembly approaches. The methods were validated with a transcriptomic data set derivedmore »« less
DOI: 10.1371/journal.pone.0009780

Similar Records