Abstract: A method for estimating error in expression data. In one embodiment, the method includes single molecule sequencing a plurality of expression tags from an organism; removing expression tags that ambiguously relate to multiple genes; assigning each remaining expression tag to a respective gene; selecting a random subset of the expression tags; and counting the number of expression tags associated with each gene. The process of selecting a random subset of the expression tags; and counting the number of expression tags associated with each gene is repeated a predetermined number of times, both for expression tags sequenced before and after exposure of the organism to a perturbation. The method also includes the step of calculating a measure of error in response to the counts of the number of expression tags before and after the perturbation.

Abstract: Systems and methods for identifying populations of events in a multi-dimensional data set are described. The populations may, for example, be sets or clusters of data representing different white blood cell components in sample processed by a flow cytometer. The methods use a library consisting of one or more one finite mixture models, each model representing multi-dimensional Gaussian probability distributions with a density function for each population of events expected in the data set. The methods further use an expert knowledge set including one or more data transformations and one or more logical statements. The transformations and logical statements encode a priori expectations as to the populations of events in the data set. The methods further use program code by which a computer may operate on the data, a finite mixture model selected from the library, and the expert knowledge set to thereby identify populations of events in the data set.

Abstract: Systems and methods for identifying populations of events in a multi-dimensional data set, e.g., seven dimensional flow cytometry data of a blood sample. The populations may, for example, be sets or clusters of data representing different white blood cell components in the sample. The methods use a library consisting of one or more one finite mixture models, each model component comprising parameters representing multi-dimensional Gaussian probability density functions, one density for each population of events expected in the data set. The methods further use an expert knowledge set comprising one or more data transformations for operation on the multi-dimensional data set and one or more logical statements. The transformations and logical statements encode a priori expectations as to the relationships between different event populations in the data set.

Abstract: Novel zacrp3x2 polypeptides, polynucleotides encoding the polypeptides, and related compositions and methods are disclosed. Also disclosed are antibodies to the zacrp3x2 protein or fragments thereof.

Abstract: The present invention relates to polynucleotide and polypeptide molecules, and variants thereof, for Zzp1, a novel Zona Pellucida protein. The polypeptides, and polynucleotides encoding them, are fertility modulating and may be used for delivery and therapeutics. The present invention also includes antibodies to the Zzp1 polypeptides.

Abstract: Mammalian glycoprotein hormone-1 (Zlut1) polypeptides, polynucleotides encoding the polypeptides, antibodies that specifically bind to the polypeptides, expression vectors comprised of the polynucleotides, and host cells transformed with the expression vectors.