Abstract: Embodiments herein described provide methods for determining phenotypic parameters of cell populations and expressing them in terms of tensors that can be compared with one another. Embodiments provide methods for determining phenotypic parameters of cell populations in response to an agent. Embodiments provide methods for comparing effects of an agent on phenotypic parameters to effects of reference standards whose in vivo effects are known. Embodiments provide methods for predicting the effect of an agent by the comparison with the known effects of reference standards. Embodiments provide methods for classifying agents by their effects on phenotypic parameters. Embodiments provide software and computer systems for calculating multiparametric tensors, compressing their complexity and comparing them after compression.

Abstract: A system for the identification of micro-organisms includes an irradiation unit adapted to sequentially provide coherent electromagnetic radiation of one or more wavelengths along a common optical path. A holder is adapted to retain a substrate having a surface adapted for growth of a micro-organism colony. A beamsplitter is adapted to direct the coherent electromagnetic radiation from the common optical path towards the retained substrate. An imager is arranged opposite the beamsplitter from the retained substrate and is adapted to obtain images of backward-scattered light patterns from the micro-organism colony irradiated by the respective wavelengths of the directed coherent electromagnetic radiation. Some examples provide radiation of multiple wavelengths and include an imager arranged optically downstream of the retained substrate to obtain images of forward-scattered light patterns from the micro-organism colony irradiated by the wavelengths of radiation.

Abstract: The invention generally relates to methods, reagents, and substrates for detecting target analytes.

Abstract: Embodiments herein described provide methods for determining phenotypic parameters of cell populations and expressing them in terms of tensors that can be compared with one another. Embodiments provide methods for determining phenotypic parameters of cell populations in response to an agent. Embodiments provide methods for comparing effects of an agent on phenotypic parameters to effects of reference standards whose in vivo effects are known. Embodiments provide methods for predicting the effect of an agent by the comparison with the known effects of reference standards. Embodiments provide methods for classifying agents by their effects on phenotypic parameters. Embodiments provide software and computer systems for calculating multiparametric tensors, compressing their complexity and comparing them after compression.

Abstract: Embodiments herein described provide methods for determining phenotypic parameters of cell populations and expressing them in terms of tensors that can be compared with one another. Embodiments provide methods for determining phenotypic parameters of cell populations in response to an agent. Embodiments provide methods for comparing effects of an agent on phenotypic parameters to effects of reference standards whose in vivo effects are known. Embodiments provide methods for predicting the effect of an agent by the comparison with the known effects of reference standards. Embodiments provide methods for classifying agents by their effects on phenotypic parameters. Embodiments provide software and computer systems for calculating multiparametric tensors, compressing their complexity and comparing them after compression.

Abstract: A computer method for correlating depictions of colonies of microorganisms includes receiving an image of a substrate associated with a first time and showing a colony of microorganisms. A second image of the same substrate and associated with a second time shows a candidate colony of microorganisms. A region of the second image that shows the candidate colony of microorganisms is located. The first region of the first image is compared to the second region of the second image. Based on the comparison of the images, the candidate colony of microorganism is determined to be the same colony as the first colony of microorganisms. Systems for moving substrates having colonies of microorganisms and maintaining orientation of the substrates before and after movement are also described.

Abstract: A system for the identification of micro-organisms includes an irradiation unit adapted to sequentially provide coherent electromagnetic radiation of one or more wavelengths along a common optical path. A holder is adapted to retain a substrate having a surface adapted for growth of a micro-organism colony. A beamsplitter is adapted to direct the coherent electromagnetic radiation from the common optical path towards the retained substrate. An imager is arranged opposite the beamsplitter from the retained substrate and is adapted to obtain images of backward-scattered light patterns from the micro-organism colony irradiated by the respective wavelengths of the directed coherent electromagnetic radiation. Some examples provide radiation of multiple wavelengths and include an imager arranged optically downstream of the retained substrate to obtain images of forward-scattered light patterns from the micro-organism colony irradiated by the wavelengths of radiation.

Abstract: Embodiments herein described provide methods for determining phenotypic parameters of cell populations and expressing them in terms of tensors that can be compared with one another. Embodiments provide methods for determining phenotypic parameters of cell populations in response to an agent. Embodiments provide methods for comparing effects of an agent on phenotypic parameters to effects of reference standards whose in vivo effects are known. Embodiments provide methods for predicting the effect of an agent by the comparison with the known effects of reference standards. Embodiments provide methods for classifying agents by their effects on phenotypic parameters. Embodiments provide software and computer systems for calculating multiparametric tensors, compressing their complexity and comparing them after compression.

Abstract: Embodiments herein described provide methods for determining phenotypic parameters of cell populations and expressing them in terms of tensors that can be compared with one another. Embodiments provide methods for determining phenotypic parameters of cell populations in response to an agent. Embodiments provide methods for comparing effects of an agent on phenotypic parameters to effects of reference standards whose in vivo effects are known. Embodiments provide methods for predicting the effect of an agent by the comparison with the known effects of reference standards. Embodiments provide methods for classifying agents by their effects on phenotypic parameters. Embodiments provide software and computer systems for calculating multiparametric tensors, compressing their complexity and comparing them after compression.

Abstract: A system and method for identifying organisms by analysis of scattergrams of colonies is disclosed. cattergrams are obtained by culturing samples and illuminating the resultant colonies by a laser. The forward scattered light is imaged and subject to a feature extraction process. The feature vector may include Zernike or Chebyshev moments and may also include Harelick texture features. Feature vectors may be used to train a classification process using either supervised or unsupervised machine learning techniques. The classification process may be used to associate a colony phenotype with the genotype of the sample.

Abstract: Systems and methods for obtaining fluorochrome abundance information by unmixing fluorescence emission data captured by a flow cytometer in accordance with embodiments of the invention are disclosed. In one embodiment, a data analysis system includes a processor, a memory, and an optical data analysis application, wherein the optical data analysis application configures the processor to obtain control optical data, generate a mixing model using the obtained control optical data and a system of linear combinations, obtain experimental optical data for particles stained with a set of fluorochromes, and estimate abundances of the fluorochromes in the set of fluorochromes using the obtained experimental optical data by solving a system of equations to unmix the optical data, where the number of equations is larger than the number of unknowns, based upon the generated mixing model using an unmixing process that accounts for increased noise variance with increased fluorochrome abundance.

Abstract: A system and method for identifying organisms by analysis of scattergrams of colonies is disclosed. cattergrams are obtained by culturing samples and illuminating the resultant colonies by a laser. The forward scattered light is imaged and subject to a feature extraction process. The feature vector may include Zernike or Chebyshev moments and may also include Harelick texture features. Feature vectors may be used to train a classification process using either supervised or unsupervised machine learning techniques. The classification process may be used to associate a colony phenotype with the genotype of the sample.

Abstract: A multi-spectral detection and analysis system detects and classifies a targeted sample. The system may include a light source that causes the targeted sample to luminesce. A light dispersion element disperses the luminescence to a photodetector in a photodetector array. Each photodetector in the array transmits a signal indicating a portion of the spectrum to a multi-channel collection system. The multi-channel collection system processes the signal into a digital signal and forms the digital signal into a spectral signature. A processor analyzes the spectral signature and compares the spectral signature to known spectral signatures to identify the targeted sample.

Abstract: A multi-spectral detection and analysis system detects and classifies a targeted sample. The system may include a light source that causes the targeted sample to luminesce. A light dispersion element disperses the luminescence to a photodetector in a photodetector array. Each photodetector in the array transmits a signal indicating a portion of the spectrum to a multi-channel collection system. The multi-channel collection system processes the signal into a digital signal and forms the digital signal into a spectral signature. A processor analyzes the spectral signature and compares the spectral signature to known spectral signatures to identify the targeted sample.