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Microarray-Relevant NIH Grants Feb. 13 -- April 9

Microarray-Relevant NIH Grants in Fiscal Year 2006, Feb. 13 — April 9
Organization Name,
City, State
PI Name Project Title
British Columbia Cancer Agency,
Vancouver, BC
Lam, Wan Whole genome array CGH of progressing oral dysplasia
Callida Genomics,
Sunnyvale, Calif.
Callow, Matthew Megabase scale polymorphism discovery by mis-match selection and random arrays
Colorado State University,
Fort Collins,
Fort Collins, Colo.
Grainger, David DNA microarray surface analysis to optimize detection
Alachua, Fla.
Larkin, Patrick Microarrays in fathead minnows and bass
H Lee Moffitt Cancer Center & Research Institute,
Tampa, Fla.
Edgerton, Mary Clinical & microarray data predict lung cancer outcomes
Harvard University School of Public Health,
Betensky, Rebecca Statistical methods for analysis of array CGH data
San Diego
Gunderson, Kevin High resolution DNA copy/LOH measurements on WGG arrays
Massachusetts General Hospital Chess, Andrew Single cell PCR microarray study of alternative splicing
Massachusetts General Hospital,
Yarmush, Martin Living cell arrays for real-time functional genomics
Medical University of South Carolina,
Charleston, SC
Argraves, Scott Microarray scanner and accessories for MUSC
Cancer center microarray bioinformatics facility
San Diego
Hodko, Dalibor Electric-field assisted isothermal on-chip amplification of DNA
Neuronexus Technologies,
Ann Arbor, Mich.
Hetke, Jamille Deep brain microelectrode array for functional neurosurgery
North Carolina State University, Raleigh,
Raleigh, NC
Oleksiak, Marjorie Microarray analyses of polluted natural populations
Oregon Health & Science University,
Portland, Ore.
Sahn, David High frequency ultrasound arrays: intracardiac imaging
Perlegen Sciences,
Mountain View, Calif.
Stokowski, Renee Signature SNPs to distinguish Yersinia pestis strains
Pulsar Clinical Technologies Awdeh, Zuheir Novel DNA microarray for HLA typing
Purdue University,
West Lafeyette, Ind.
Bashir, Rashid Nanowire sensor arrays for detection of nucleic acid molecules
Stanford University,
Stanford, Calif.
Sherlock, Gavin Expanded system for the Stanford microarray database
University of Arkansas,
Little Rock, Ark.
Dennis, Richard High-throughput real-time PCR system for the microarray core
University of California, San Diego,
La Jolla, Calif.
Vinetz, Joseph Microarray analysis of leptospiral genomes
University of Colorado, Boulder,
Boulder, Colo.
Rowlen, Kathy Development of diagnostic microarray for Influenza A
University of Georgia, Athens,
Athens, Ga.
Tarleton, Rick Microarray analysis of gene expresion in T. cruzi
University of Maryland,
Elmer, Gregory Microarray analysis of morphine's behavioral effects
University of Massachusetts, Amherst,
Amherst, Mass.
Kulp, David Improved design and analysis of diploid resequencing microarrays
University of North Carolina, Chapel Hill,
Chapel Hill, NC
Sullivan, Patrick Microarrays & proteomics in MZ twins discordant for CFS
Veterans Medical Research Foundation,
San Diego
Patel, Piyush Microarray analysis of neuronal ischemic preconditioning
Wistar Institute,
Showe, Louise Microarray analysis of responsiveness of CTCL IL-12
The Scan

Genetic Tests Lead to Potential Prognostic Variants in Dutch Children With Dilated Cardiomyopathy

Researchers in Circulation: Genomic and Precision Medicine found that the presence of pathogenic or likely pathogenic variants was linked to increased risk of death and poorer outcomes in children with pediatric dilated cardiomyopathy.

Fragile X Syndrome Mutations Found With Comprehensive Testing Method

Researchers in Clinical Chemistry found fragile X syndrome expansions and other FMR1 mutations with ties to the intellectual disability condition using a long-range PCR and long-read sequencing approach.

Team Presents Strategy for Speedy Species Detection in Metagenomic Sequence Data

A computational approach presented in PLOS Computational Biology produced fewer false-positive species identifications in simulated and authentic metagenomic sequences.

Genetic Risk Factors for Hypertension Can Help Identify Those at Risk for Cardiovascular Disease

Genetically predicted high blood pressure risk is also associated with increased cardiovascular disease risk, a new JAMA Cardiology study says.