摘要:
The disclosed visual RRC-humanoid robot is a computer-based system that has been programmed to reach human-like levels of visualization Artificial Intelligence (AI). Behavioral-programming techniques are used to reach human-like levels of identification AI, recognition AI, visualization AI, and comprehension AI. The system is programmed to identify, recognize, visualize and comprehend the full array of sizes, distances, shapes, and colors of objects recorded in the FOV of the system. The following innovative features have been incorporated into the system: (i) incorporation of the RRC, (ii) incorporation of the Relational Correlation Sequencer (RCS): A proprietary RRC-module, (iii) a paradigm shift in the analytical-programming methodology employed in computer vision systems, (iv) incorporation of a central hub of intelligence, (v) design of a “self knowledge” capability and Internalization of all data, and (vi) design of an interface circuit compatible with human-like levels of visualization-AI.
摘要:
The present invention provides an approach for the determination of the activation states of a plurality of proteins in single cells. This approach permits the rapid detection of heterogeneity in a complex cell population based on activation states, expression markers and other criteria, and the identification of cellular subsets that exhibit correlated changes in activation within the cell population. Moreover, this approach allows the correlation of cellular activities or properties. In addition, the use of modulators of cellular activation allows for characterization of pathways and cell populations. Several exemplary diseases that can be analyzed using the invention include AML, MDS, and MPN.
摘要:
The present invention provides an approach for the determination of the activation states of a plurality of proteins in single cells. This approach permits the rapid detection of heterogeneity in a complex cell population based on activation states, expression markers and other criteria, and the identification of cellular subsets that exhibit correlated changes in activation within the cell population. Moreover, this approach allows the correlation of cellular activities or properties. In addition, the use of modulators of cellular activation allows for characterization of pathways and cell populations. Several exemplary diseases that can be analyzed using the invention include AML, MDS, and MPN.
摘要:
The present invention provides an approach for the determination of the activation states of a plurality of proteins in single cells. This approach permits the rapid detection of heterogeneity in a complex cell population based on activation states, expression markers and other criteria, and the identification of cellular subsets that exhibit correlated changes in activation within the cell population. Moreover, this approach allows the correlation of cellular activities or properties. In addition, the use of modulators of cellular activation allows for characterization of pathways and cell populations. Several exemplary diseases that can be analyzed using the invention include AML, MDS, and MPN.
摘要:
The present invention provides an approach for the determination of the activation states of a plurality of proteins in single cells. This approach permits the rapid detection of heterogeneity in a complex cell population based on activation states, expression markers and other criteria, and the identification of cellular subsets that exhibit correlated changes in activation within the cell population. Moreover, this approach allows the correlation of cellular activities or properties. In addition, the use of modulators of cellular activation allows for characterization of pathways and cell populations. Several exemplary diseases that can be analyzed using the invention include AML, MDS, and MPN.