Beckman Coulter, Inc.

Xy, Inc.

Dakocytomation Colorado, Inc.

George C Malachowski

Paul Barclay Purcell

Edward Allan Stanton

Kenneth Michael Evans

Daniel Nelson Fox

Jeffrey W Degeal

Charles S Bay

Thomas L Thrasher

Matthias J G Ottenberg

Tidhar Sadeh

Theodore W Jochum

Carl E Ellison

Matthias J Ottenberg

In flow cytometry, particles () can be distinguished between populations () by combining n-dimensional parameter data, which may be derived from signal data from a particle, to mathematically achieve numerical results representative of an alteration (). An alteration may include a rotational alteration, a scaled alteration, or perhaps even a translational alteration. Alterations may enhance separation of data points which may provide real-time classification () of signal data corresponding to individual particles into one of at least two populations.

Enhancing flow cytometry discrimination with geometric transformation

Disclosed are computer-implemented methods of sorting particles from a particle stream in a flow cytometer. The methods include: calculating sort decision making parameters using the raw event data values from a flow cytometer and a sort logic; performing sort logic computations using the sort logic definition and the sort decision making parameters to generate sort decisions; converting the sort decisions into sort commands; and sending the one or more sort commands to the flow cytometer. Sort logic computations may include algorithmically using conditional branching logic, and may include sort logic equations having mathematical functions characterizing one or more regions of interest in multidimensional data space. Such mathematical functions may be determined based on one or more parameters provided by a user. Also disclosed are corresponding systems having a flow cytometer and a computer.

Flow cytometer sorter

Disclosed is a self-tuning flow cytometer that uses a mathematical model to perform sort decisions that is based upon the biological response of the particular types of cells that are being sorted. In one embodiment, statistical calculations of the likelihood of an event belonging to a certain population are used to make the sort decisions. Automated self-tuning processes are used to optimize the operating parameters of the flow cytometer to achieve a selected purity with higher yield at optimal sorting speeds. The fully automated processes minimize user input and allows the user to select a desired purity while maximizing yield.

Self-tuning, biologically modeled sorter

A flow cytometer capable of using electronics to analyze a large dynamic range while avoiding and/or correcting traditional limitations of acquisition electronics. The invention allows for measuring signal characteristics, which may include but are not limited to linear peak, integral, logarithmic peak, and pulse width. Other system parameters may also be generated by the invention to indicate timing or status information. Accurate and precise measurements may be performed by correcting for input errors if needed, and by transforming the input signal to produce a more easily measured form.

System for high dynamic range analysis in flow cytometry

A flow cytometry apparatus and methods to process information incident to particles or cells entrained in a sheath fluid stream allowing assessment, differentiation, assignment, and separation of such particles or cells even at high rates of speed. A first signal processor individually or in combination with at least one additional signal processor for applying compensation transformation on data from a signal. Compensation transformation can involve complex operations on data from at least one signal to compensate for one or numerous operating parameters. Compensated parameters can be returned to the first signal processor for provide information upon which to define and differentiate particles from one another.

Transiently dynamic flow cytometer analysis system

Growing community of inventors

Melbourne, Australia

George C Malachowski