Embodiments of a system, method and apparatus incorporate two-stage identification of targets in hyperspectral image analysis. In various embodiments, unmixing is employed that integrates F-test and model averaging approaches. Further, a multi-tier target library process provides an improvement in the spectra that can be used to detect target materials and spectra that can be used for unmixing in identification. Additionally, the hierarchical identification of the present disclosure combines probabilities from model averaging to generate target identifications simultaneously at multiple levels of specificity.

Embodiments of a system, method and apparatus incorporate two-stage identification of targets in hyperspectral image analysis. In various embodiments, unmixing is employed that integrates F-test and model averaging approaches. Further, a multi-tier target library process provides an improvement in the spectra that can be used to detect target materials and spectra that can be used for unmixing in identification. Additionally, the hierarchical identification of the present disclosure combines probabilities from model averaging to generate target identifications simultaneously at multiple levels of specificity.

This invention relates generally to identifying peptide sequences involved in antibody binding to any protein for synthesis of vaccine treatments. This novel method allows for a more manageable vaccine peptide discovery and specific generation of unique immunogenic peptides from self-tumor associated proteins and/or foreign proteins from infectious organisms for specific and/or enhanced expression only in the presence of the antibody.

Novel peptide inhibitors of GSK-3, compositions containing same and uses thereof are disclosed. The novel peptide inhibitors are converted to inhibitors of GSK-3 upon interacting with the enzyme's catalytic site and hence act as disease-selective inhibitors for treating conditions associated with increased activity and/or expression of GSK-3. Each of the disclosed peptides is independently of no more than 15 amino acid residues, and has an amino acid sequence which comprises a ZX.sub.1X.sub.2X.sub.3Z(p) recognition motif of GSK-3, wherein Z(p) is a phosphorylated serine or threonine residue; Z is a phosphorylatable serine or threonine residue, and each of X.sub.1, X.sub.2 and X.sub.3 is independently any amino acid, as defined in the specification. Further disclosed are methods of identifying a putative substrate-competitive peptide inhibitor of GSK-3 which are effected by computational modeling and screening.

A method comprising obtaining a control catalyst set having a plurality of members each having a control characteristic, wherein the members of the control catalyst set comprise a transition metal and an organic ligand, selecting an intermediate formed during a catalytic cycle of each member of the control catalyst set, geometrically and energetically optimizing a structure of the intermediate, determining one or more characteristics of the geometrically and energetically optimized structure of the intermediate, determining a mathematical relationship between the control characteristic and the one or more characteristics of the geometrically and energetically optimized structure of the intermediate, utilizing the mathematical relationship to identify one or more members of a sample catalyst set having a control characteristic within a desired range, contacting the identified sample catalyst with a reactant under conditions suitable for the formation of product, and recovering the product.

The present invention provides systems, methods and software for improving robustness of transcriptomic data analysis, the method including receiving control cell transcriptomic data (C) and cell transcriptomic data (S) under study for a gene, calculating a fold change ratio (fc) for the gene, repeating these steps for a plurality of genes, grouping co-expressed genes into modules, estimating gene importance factors based on a network topology, mapped from a plurality of the modules and obtaining a insilico Pathway Activation Network Decomposition Analysis (iPANDA) value, wherein the iPANDA value has a Pearson coefficient greater than a Pearson coefficient associated with another platform for manipulating the same data.

Disclosed herein are methods of identifying infections, such as methods of identifying bacterial infections which utilize whole metagenome sequence analysis to sequence the entire wound microbiome of clinical samples. The disclosed methods use fast k-mer based sequence analysis, predictive modeling, and Bayesian network analysis, to analyze bacterial metagenomic sequence compositions in conjunction with clinical factors to stratify communities of bacteria into healing versus non-healing clusters. The methods of identifying infections can include performing molecular analysis of a patient wound sample, preparing the data obtained from the molecular analysis, diagnosing the wound sample and/or prognosing the wound sample. The disclosed methods can also be used to identify protein function as well as novel biomarkers.

Disclosed herein are methods of identifying infections, such as methods of identifying bacterial infections which utilize whole metagenome sequence analysis to sequence the entire wound microbiome of clinical samples. The disclosed methods use fast k-mer based sequence analysis, predictive modeling, and Bayesian network analysis, to analyze bacterial metagenomic sequence compositions in conjunction with clinical factors to stratify communities of bacteria into healing versus non-healing clusters. The methods of identifying infections can include performing molecular analysis of a patient wound sample, preparing the data obtained from the molecular analysis, diagnosing the wound sample and/or prognosing the wound sample. The disclosed methods can also be used to identify protein function as well as novel biomarkers.

Methods and systems for ordering assays which detect SNPs or gene expression are provided. The methods use PCR and RT-PCR procedures. Collections of stock assays are assembled using pre- and post-manufacturing quality control procedures and made available to consumers via the Internet. In addition, custom assays are prepared upon order from the consumer and these assays are also prepared using pre- and post-manufacturing quality control procedures. The assays are then delivered to the consumer.

Disclosed herein are methods of selecting an allogeneic T cell line for therapeutic administration to a patient having or suspected of having a pathogen or cancer. Also disclosed are methods of selecting a donor from whom to derive an allogeneic T cell line for therapeutic administration to a patient having or suspected of having a pathogen or cancer.