GNF provides public access to results from some of its most significant tools and discovery projects. We also use our own custom-built databases and applications to publish unique large-scale datasets on gene function and genetic polymorphism such that their value to the scientific community is maximized. This page provides an overview of tools currently available on our web site, along with a brief summary.

SymAtlas. This online tool is a public installation of our gene-centric database of integrated gene and genome annotation.  SymAtlas presents annotation collated from the public domain alongside gene expression data generated at GNF from humans and various rodents.  In particular, the “GeneAtlas” data set displays the expression pattern for > 20,000 transcripts across an anatomically diverse panel of tissues [1].  This application has been widely used as a candidate gene prioritization tool for gene expression and genetics studies.

SNPview. Browse or search the large-scale SNP collections GNF researchers generated for most of the commonly used in-bred laboratory strains. These SNP collections are a key tool towards the goal of in-silico mapping phenotypic and complex disease traits [2].

Druggable Genome BLAT. We provide a convenient interface to search against our expanded dataset of slightly more than 3000 unique human protein-encoding "druggable" genes [3].

P. falciparum e-Annotation Database. Ontology-based Pattern Identification (OPI) is a novel data-mining algorithm that systematically identifies gene/protein expression patterns that best represent existing knowledge of gene function [4]. We applied OPI to a gene expression data set (publicly available) on the life cycle of the malarial parasite P. falciparum and systematically annotated genes for several hundred functional categories. The database provides a systems-wide biological view of the parasite.

Redundant siRNA Activity (RSA) Analysis Tool.  RSA is a statistical analysis methodology designed to minimize the impact of off-target activities upon large-scale RNA interference screens in mammalian cells.  Application of this analysis significantly enhances reconfirmation rate [5].

We make extensive use of Open Source software packages in our in-house built informatics systems, and we have also contributed back to the community substantially.

1. Su AI, Wiltshire T, Batalov S, Lapp H, Ching KA, Block D, Zhang J, Soden R, Hayakawa M, Kreiman G, et al. A gene atlas of the mouse and human protein-encoding transcriptomes. Proc Natl Acad Sci U S A 2004;101(16):6062-7.
2. Pletcher MT, McClurg P, Batalov S, Su AI, Barnes SW, Lagler E, Korstanje R, Wang X, Nusskern D, Bogue MA, et al. Use of a dense single nucleotide polymorphism map for in silico mapping in the mouse. PLoS Biol 2004;2(12):e393.    
3. Orth AP, Batalov S, Perrone M, Chanda SK. The promise of genomics to identify novel therapeutic targets. Expert Opin Ther Targets 2004;8(6):587-96.     
4. Zhou Y, Young JA, Santrosyan A, Chen K, Yan SF, Winzeler EA. In silico gene function prediction using ontology-based pattern identification. Bioinformatics 2005;21(7):1237-45. 
5. Konig R, Chiang CY, Tu BP, Yan SF, DeJesus PD, Romero A, Bergauer T, Orth A, Krueger U, Zhou Y, et al. A probability-based approach for the analysis of large-scale RNAi screens. Nat Methods 2007;4(10):847-9.