Abstract: The present invention provides methods and systems for automated morphological analysis of cells also known as phenotypic screening. The inventive methods are particularly useful in the rapid analysis of cells required in a biological screen or in the screening for agents with a particular mechanism of action. Agents which cause a particular phenotype in the cells can be identified using the inventive quantitative morphometric analysis of cells. The data gathered using the inventive method can also be quantified and analyzed later for various trends and classifications (e.g., Kolmogorov-Smirnov statistics, titration-invariant similarity scores). Characteristics of cells which can be determined using this method include number of nuclei, size of cell, size of nuclei, number of the centrosomes, shape of cells, size of centrosomes, perimeter of nucleus, shape of nucleus, staining for a particular protein, staining for an organelle, pattern of staining, and degree of staining.

Abstract: The present invention provides methods and systems for automated morphological analysis of cells. The inventive methods are particularly useful in the rapid analysis of cells required in a biological screen. Agents which cause a particular phenotype in the cells can be identified using the inventive quantitative morphometric analysis of cells. The data gathered using the inventive method can also be quantified and analyzed later for various trends and classifications. Characteristics of cells which can be determined using this method include number of nuclei, size of cell, size of nuclei, number of the centrosomes, shape of cells, size of centrosomes, perimeter of nucleus, shape of nucleus, pattern of staining, and degree of staining.

Abstract: Sound source separation, without permutation, using convolutional mixing independent component analysis based on a priori knowledge of the target sound source is disclosed. The target sound source can be a human speaker. The reconstruction filters used in the sound source separation take into account the a priori knowledge of the target sound source, such as an estimate the spectra of the target sound source. The filters may be generally constructed based on a speech recognition system. Matching the words of the dictionary of the speech recognition system to a reconstructed signal indicates whether proper separation has occurred. More specifically, the filters may be constructed based on a vector quantization codebook of vectors representing typical sound source patterns. Matching the vectors of the codebook to a reconstructed signal indicates whether proper separation has occurred. The vectors may be linear prediction vectors, among others.

Abstract: A pattern lattice data space as a framework for analyzing data, in which both schema-based and statistical analysis are accommodated, is defined. Ways to manage the size of the lattice structures in the pattern lattice data space are described. Utilities to classify or cluster, search (find similar data), or relate data using lattice fragments in the pattern lattice data space are also described. Superpattern cone or lattice generation function, which may be used by the classification and clustering functions, is also described. In addition, a subpattern cone or lattice generation process, which may be used by the search (find similar data) and data relating functions, is also described. Finally, a function to label, in readily understandable “pidgin”, categories which classify information, is also described.