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Funding Update: Jun 25, 2010


NSF Bioinformatics Grants Awarded May 15 — June 24, 2010

Sample Classification and Biomarker Discovery by Comprehensive Metabolomic Analysis
Start date: July 1, 2010
Expires: Dec. 31, 2010
Awarded amount to date: $145,536
Principal investigator: Stephen Reichenbach
Sponsor: GC Imaging

This Phase I Small Business Innovation Research project aims to develop a system for classifying biological samples. Specifically, the system will perform pattern analysis of biochemical separations generated by two-dimensional gas chromatography with high-resolution mass spectrometry. "A critical challenge for elective utilization of GCxGC-HRMS for biochemical classification and biomarker discovery is the difficulty of analyzing and interpreting the massive, complex data for metabolomic and proteomic features," the grant abstract states. The investigators plan to develop "an innovative framework for comprehensive feature matching and analysis across many samples" that will include methods for multidimensional peak detection, peak pattern matching across large sample sets, data alignment, GCxGC-HRMS feature computations, and classification with large feature sets.

New Technologies for Genome-Scale Comparative NcRNA Identification
Start date: July 1, 2010
Expires: June 30, 2011
Awarded amount to date: $117,956
Principal investigator: Yanni Sun
Sponsor: Michigan State University

This grant supports a project to develop new technologies for genome-scale comparative noncoding RNA identification. Current analysis tools "rely on conventional comparative sequence analysis, which cannot effectively account for structural conservation in homologous ncRNAs and thus jeopardize the sensitivity and accuracy of structured ncRNA search," according to the grant abstract. In response, the project aims to develop improved ncRNA detection algorithms "that combine the efficiency of conventional sequence comparison tools and the structural features of ncRNAs." The investigators plan to develop algorithms that can efficiently classify a large number of putative ncRNAs into corresponding ncRNA families, algorithms for genome-wide ncRNA homology search, and "a novel ncRNA structure modeling and comparison method."

Collaborative Research: Cross Species Analysis of Biological Systems Using Expression Data
Start date: July 1, 2010
Expires: June 30, 2011
This grant was awarded to two investigative teams:
• $234,235 to Ziv Bar-Joseph of Carnegie-Mellon University
• $77,582 to Gerard Nau of University of Pittsburgh

This project plans to develop algorithms and software tools for analyzing gene expression experiments that study the same biological system in multiple species. The grantees will develop an open-source software package for cross-species expression analysis and will also offer a class on the analysis and use of cross-species genomics data.

Computational Tools for Fundamental Characterization and Inference of Genetic Interaction Networks
Start date: June 15, 2010
Expires: May 31, 2011
Awarded amount to date: $96,531
Principal investigator: Chad Myers
Sponsor: University of Minnesota-Twin Cities

This award supports the development of computational approaches for understanding large-scale genetic interaction networks. Specifically, the investigators aim to develop algorithms for comprehensive mining of genetic interaction network structure, predictive models of genetic interactions from diverse genomic data within and across species, and software tools for integrative analysis and visualization of genetic interaction networks to facilitate discovery.

Agroecological Annotation of Gene Function and Computational Analysis of Gene Networks
Start date: June 15, 2010
Expires: May 31, 2011
Awarded amount to date: $1,199,040
Principal investigator: Cynthia Weinig
Sponsor: University of Wyoming

This project will use Brassica rapa and Arabidopsis thaliana as models for developing computational approaches that will "enable both reconstruction of gene networks that regulate density responses and prediction of different traits (such as flowering time, height, and fruit set) from complex genotypes," according to the grant abstract.

A Toolbox for Large-Scale Analysis of Structural Molecular Data
Start date: June 15, 2010
Expires: May 31, 2011
Awarded amount to date: $250,599
Principal investigator: Lydia Kavraki
Sponsor: William Marsh Rice University

This project aims to design and implement an "extensible and computationally efficient toolbox" that integrates sequence information and molecular metadata with structural analysis of proteins. The toolbox is based on a substructure matching method that finds correspondences of a three-dimensional set of atoms to a set of protein structures. "The toolbox will be built in a way that it will automatically draw metadata information from relevant online databases in order to be continuously up to date," according to the grant abstract.

Computational Modeling and Analysis of Gene Expression Patterns from Microscopy Image Data
Start date: June 1, 2010
Expires: May 31, 2011
Awarded amount to date: $155,068
Principal investigator: Uwe Ohler
Sponsor: Duke University

The investigators in this project will develop an integrated framework for analyzing and interpreting biological image data. "With recent advances in microscopy technology, as well as means to visualize biological molecules, the growing amount of available data has turned images into a new data type for computational biology with new and exciting challenges and possibilities," the grant abstract states. "In particular, microscopy allows for measuring gene expression patterns at high resolution and in living organisms." The grantees will develop tools based on a "principled probabilistic framework" that uses top-down generative strategies to extract samples from images, model gene expression patterns from microscopy data, and integrate image expression data with other genomic data to understand gene regulation.

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Statistical Tools for Post-Genomic Personalized Medicine and Health Care
Start date: June 1, 2010
Expires: May 31, 2013
Awarded amount to date: $304,504
Principal investigator: Mathukumalli Vidyasagar
Sponsor: University of Texas at Dallas

This project will develop statistical tools for a range of systems biology and personalized medicine applications, including target and lead identification and patient selection for clinical trials. The investigators aim to address several statistical problems, including detecting similarity in sequences, and subsampling large-scale data sets while retaining their statistical properties. For the similarity-detection challenge, the team will extend Blast "to the case where the sequences being compared are sample paths of Markov chains." For their work in subsampling large-scale data sets, the investigators plan to use Vapnik-Chervonenkis theory, which they claim is the only sampling theory that is "'distribution-free' — that is, the size of the subsample needed to retain the statistical properties of the original data does not depend on the distribution of the original data."

Statistical Methods for High Dimensional Discrete Data
Start date: June 1, 2010
Expires: May 31, 2011
Awarded amount to date: $48,768
Principal investigator: Naomi Altman
Sponsor: Pennsylvania State University, University Park

This grant supports the development of new methods for analyzing highly multivariate data. Methods will be developed in four areas: analyses for differences in distribution for discrete data that can accommodate complex experimental designs; methods for supervised clustering of samples and variables; dimension-reduction methods; and the extension of concepts and methods in multiple testing. The methods will be tested on genomics and imaging data.

GOSTRUCT: Modeling the Structure of the Gene Ontology for Accurate Protein Function Prediction
Start date: June 1, 2010
Expires: May 31, 2014
This grant was awarded to two investigative teams:
• $288,384 to Karin Verspoor at the University of Colorado at Denver and Health Sciences Center
• $523,303 to Asa Ben-Hur at Colorado State University

This award supports the development of machine-learning methods for predicting protein function based on Gene Ontology terms. "Protein function prediction has several properties that make it difficult to apply state-of-the-art machine learning methods to this problem, such as the large number of potential functions (thousands of possible terms), the fact that proteins can have multiple functions, and the hierarchical relationship between terms in the Gene Ontology," according to the grant abstract. The investigators plan to explicitly model the problem of annotating proteins with GO terms as a hierarchical classification problem using the methodology of "kernel methods for structured outputs", which enables the modeling of complex prediction problems.

ChemMine Tools: an Open Source Framework for Chemical Genomics
Start date: May 15, 2010
Expires: April 30, 2011
Awarded amount to date: $219,275
Principal investigator: Thomas Girke
Sponsor: University of California-Riverside

In this project the investigators will develop ChemMineTools, an environment to analyze and model large sets of small molecules along with their bioactivity data. Objectives include developing accelerated compound search and clustering algorithms that scale to large databases with millions of entries. This aspect of the project will adopt the EI-Search and EI-Clustering algorithms "to advanced similarity measures that can currently not be used for processing large databases due their insufficient speed performance." The grantees will also develop an R package called ChemMine R Tools that will provide "advanced clustering, machine learning, and visualization functionalities along with interactive visualization tools."

Public Service System for Automated Protein Structure Predictions
Start date: Sept. 1, 2009
Expires: June 30, 2010
Awarded amount to date: $128,801
Principal investigator: Yang Zhang
Sponsor: University of Michigan Ann Arbor

This grant funds the development of a public service system for automated and reliable protein structure prediction based on the I-TASSER method. "As a complement to the full-length I-TASSER modeling, a locally installed meta-threading server (LOMETS) will be developed for the generation of multiple threading alignments and spatial restraints," according to the grant abstract.

Algorithmic Problems in Protein Structure Studies
Start date: Sept. 17, 2009
Expires: Aug. 31, 2012 (Estimated)
Awarded amount to date: $225,001
Principal investigator: Gopal Pandurangan
Sponsor: Brown University

This project aims to design efficient algorithms for "fundamental problems" that arise in studies of the three-dimensional structures of proteins. In particular, the project addresses two algorithmic problems: identifying correspondences between a pair of graphs where one is a significantly corrupted version of the other, and determining three-dimensional coordinates for the vertices of a graph, given approximate, noisy distance measurements for its edges. For the first algorithmic problem, the investigators plan to develop efficient search algorithms to uncover correspondences, with random graph models to "rigorously analyze the algorithms and study threshold phenomena characterizing robustness to noise." The second algorithmic problem "is Euclidean embedding for sparse geometric graphs, and the research involves development of algorithms to render such graphs amenable to low rank distance matrix reconstruction methods, generalizing the reconstruction methods to exploit the underlying geometric structure and account for the confounding noise structure," the abstract states.

The Scan

Study Links Evolution of Longevity, Social Organization in Mammals

With the help of comparative phylogenetics and transcriptomics, researchers in Nature Communications see ties between lifespan and social organization in mammals.

Tumor Microenvironment Immune Score Provides Immunotherapy Response, Prognostic Insights

Using multiple in situ analyses and RNA sequence data, researchers in eBioMedicine have developed a score associated with immunotherapy response or survival.

CRISPR-Based Method for Finding Cancer-Associated Exosomal MicroRNAs in Blood

A team from China presents in ACS Sensors a liposome-mediated membrane fusion strategy for detecting miRNAs carried in exosomes in the blood with a CRISPR-mediated reporter system.

Drug Response Variants May Be Distinct in Somatic, Germline Samples

Based on variants from across 21 drug response genes, researchers in The Pharmacogenomics Journal suspect that tumor-only DNA sequences may miss drug response clues found in the germline.