A Toxicological Knowledge Base Prototype. Start date: March 1, 2007. Expires: Aug. 30, 2007. Amount: $100,000. Principal investigator: Nikolai Daraselia. Institution: Ariadne Genomics. NIH institute: NCRR.
Proposal to extend Ariadne’s MedScan text-mining technology into the metabolic, toxicological, and clinical areas. The grant funds development of a prototype database that will integrate molecular, cellular, and clinical aspects of drug action mechanisms, metabolism, and toxicity. The database will be populated with information extracted from the scientific literature using an extended version of MedScan.
Novel Machine Learning Methods for Analysis of MALDI-TOF Mass Spectrometry Data. Start date: March 1, 2007. Expires: Feb. 28, 2009. Amount: $77,600. Principal investigator: Habtom Ressom. Institution: Georgetown University. NIH institute: NCI.
Supports development of new mass spectral data preprocessing and biomarker selection methods. One goal is to develop algorithms for improved MALDI-TOF mass spectral data preprocessing including outlier screening, binning, smoothing, baseline correction, normalization, peak detection, and peak calibration. A second goal is to develop a novel algorithm that improves upon currently used biomarker selection methods by combining two machine learning methods: particle swarm optimization and support vector machines.
Computational Analysis of Retinal Regulatory Interactions: structure and dynamics. Start date: April 1, 2007. Expires: March 31, 2011. Amount: $286,781. Principal investigator: Jiang Qian. Institution: Johns Hopkins University. NIH institute: NEI.
Supports development of a computational approach to predict protein-DNA and protein-protein interactions related to retinal regulation by integrating current knowledge and a variety of data sets from high-throughput experiments. Aims include the identification of retina-related cis-regulatory elements and their regulatory targets, determination of interacting transcription factors that co-regulate retina-related genes, characterization of the dynamics of the retinal regulatory networks, and experimental verification of bioinformatics predictions.
Genetical Genomics Analysis Software. Start date: April 15, 2007. Expires: March 14, 2008. Amount: $89,008. Principal investigator: David Allen Henderson. Institution: Insightful. NIH institute: NIGMS.
Proposal to develop a suite of software tools for detecting polymorphic regions of the genome that confer transcript expression differences, identifying polymorphic regions of the genome that impart expression differences in genes located elsewhere in the genome, and detecting interactions between loci that may correspond to epistatic effects on transcription. The software, called S+EQTL (S-Plus for expression quantitative trait loci mapping), will be based on Insightful’s S-Plus software and will incorporate the functionality of an existing genetics software suite.
UltraScan Software Maintenance and Development. Start date: April 15, 2007. Expires: March 31, 2011. Amount: $312,418. Principal investigator: Borries Demeler. Institution: University of Texas Health Science Center. NIH institute: NCRR.
Supports continued development of UltraScan, a software package for analyzing hydrodynamic data from analytical ultracentrifugation and light scattering experiments. Current studies involving UltraScan focus on the role of macromolecular properties involved in disease and cancer, such as aggregation, and focus on the basic understanding of structure and function of biological polymers like proteins, RNA, and DNA.
An Open and Scalable Stochastic Simulation Library for Biology. Start date: May 1, 2007. Expires: April 30, 2010. Amount: $618,529. Principal investigator: Mark Anthony Stalzer. Institution: California Institute of Technology. NIH institute: NIBIB.
Supports development of a standard library for stochastic simulation that is compatible with a variety of programming languages “and able to capitalize on various hardware acceleration options,” according to the grant abstract. The proposed library will include simulation algorithms; support for C, C++, Java, Python, Perl, Matlab, and Mathematica under Windows, MacOS, Linux, and FreeBSD. The library will be suitable for a variety of hardware configurations, including typical desktop single-processor systems, multicore and multiprocessor systems, and field programmable gate array-based hardware acceleration boards. The library will also include an SBML (Systems Biology Markup Language) interface layer.