Abstract: The present invention relates generally to groups of genes that can be used to diagnose and differentiate between types of specific diseases such as breast cancer. The groups of genes can be further used to develop diagnostic kits for the specific diseases. The diagnostic kits can also differentiate between sub-categories of a disease to help identify the appropriate treatment regimen for a patient.

Abstract: The process of System Reconstruction is used to integrate sequence data, clinical data, experimental data, and literature into functional models of disease pathways. System Reconstruction models serve as informational skeletons for integrating various types of high-throughput data. The present invention provides the first metabolic reconstruction study of a eukaryotic organism based solely on expressed sequence tag (EST) data. System Reconstruction also provides a method for the identification of novel therapeutic targets and biomarkers using network analysis. The initial seed networks are built from the lists of novel targets for diseases with the high-throughput experimental data being superimposed on the seed networks to identify specific targets.

Abstract: The process of System Reconstruction is used to integrate sequence data, clinical data, experimental data, and literature into functional models of disease pathways. System Reconstruction models serve as informational skeletons for integrating various types of high-throughput data. The present invention provides the first metabolic reconstruction study of a eukaryotic organism based solely on expressed sequence tag (EST) data. System Reconstruction also provides a method for the identification of novel therapeutic targets and biomarkers using network analysis. The initial seed networks are built from the lists of novel targets for diseases with the high-throughput experimental data being superimposed on the seed networks to identify specific targets.

Abstract: A system is provided for the prediction of human drug metabolism and toxicity of novel compounds. The system enables the visualization of pre-clinical and clinical high-throughput data in the context of a complete biological organism. Substructure and similarity structure searches can be performed using the underlying databases of xenobiotics, active ligands, and endobiotics. The system also has an analytical component for the parsing, integration, and network analysis of genomics, proteomics, and metabolomics high-throughput data. From this information, the system further generates networks around proteins, genes and compounds to assess toxicity and drug-drug interactions.

Abstract: The process of System Reconstruction is used to integrate sequence data, clinical data, experimental data, and literature into functional models of disease pathways. System Reconstruction models serve as informational “skeletons” for integrating various types of “high throughput” data. The present invention provides the first metabolic reconstruction study of a eukaryotic organism based solely on expressed sequence tag (EST) data.

Abstract: The process of System Reconstruction is used to integrate sequence data, clinical data, experimental data, and literature into functional models of disease pathways. System Reconstruction models serve as informational skeletons for integrating various types of high-throughput data. The present invention provides the first metabolic reconstruction study of a eukaryotic organism based solely on expressed sequence tag (EST) data. System Reconstruction also provides a method for the identification of novel therapeutic targets and biomarkers using network analysis. The initial seed networks are built from the lists of novel targets for diseases with the high-throughput experimental data being superimposed on the seed networks to identify specific targets.

Abstract: The process of System Reconstruction is used to integrate sequence data, clinical data, experimental data, and literature into functional models of disease pathways. System Reconstruction models serve as informational “skeletons” for integrating various types of “high throughput” data.

Abstract: A system is provided for the prediction of human drug metabolism and toxicity of novel compounds. The system enables the visualization of pre-clinical and clinical high-throughput data in the context of a complete biological organism. Substructure and similarity structure searches can be performed using the underlying databases of xenobiotics, active ligands, and endobiotics. The system also has an analytical component for the parsing, integration, and network analysis of genomics, proteomics, and metabolomics high-throughput data. From this information, the system further generates networks around proteins, genes and compounds to assess toxicity and drug-drug interactions.

Abstract: The present invention relates generally to groups of genes that can be used to diagnose and differentiate between types of specific diseases such as breast cancer. The groups of genes can be further used to develop diagnostic kits for the specific diseases. The diagnostic kits can also differentiate between sub-categories of a disease to help identify the appropriate treatment regimen for a patient.

Abstract: A system is provided for the prediction of human drug metabolism and toxicity of novel compounds. The system enables the visualization of pre-clinical and clinical high-throughput data in the context of a complete biological organism. Substructure and similarity structure searches can be performed using the underlying databases of xenobiotics, active ligands, and endobiotics. The system also has an analytical component for the parsing, integration, and network analysis of genomics, proteomics, and metabolomics high-throughput data. From this information, the system further generates networks around proteins, genes and compounds to assess toxicity and drug-drug interactions.

Abstract: The process of System Reconstruction is used to integrate sequence data, clinical data, experimental data, and literature into functional models of disease pathways. System Reconstruction models serve as informational skeletons for integrating various types of high-throughput data. The present invention provides the first metabolic reconstruction study of a eukaryotic organism based solely on expressed sequence tag (EST) data. System Reconstruction also provides a method for the identification of novel therapeutic targets and biomarkers using network analysis. The initial seed networks are built from the lists of novel targets for diseases with the high-throughput experimental data being superimposed on the seed networks to identify specific targets.