Abstract: A microtiter plate system includes an integral heater. In an embodiment, the integral heater includes a heater plate. In another embodiment, the integral heater includes resistive heater wires positioned beneath and/or between the wells of a microtiter plate. In an embodiment, the microtiter plate system includes optically clear well bottoms that permit sensing and measurement of samples through the optically clear well bottoms. In an implementation, an optically clear heater is positioned beneath the optically clear well bottoms. In an alternative implementation, resistive heater wires are positioned between the wells. In an embodiment, the microtiter plate system includes a microtiter plate lid with an integral heater, which can be implemented using a heater plate, resistive wires, and the like.

Abstract: The present invention determines properties of combinatorial library products from features of library building blocks. At least one feature is determined for each building block of a combinatorial library having a plurality of products. A training subset of products is selected from the products, and at least one property is determined for each product of the training subset. A building block set is identified for each product of the training subset, and an input features vector is formed from the features of the identified building blocks for each product of the training subset. A supervised machine learning approach is used to infer a mapping function that transforms the input features vector for each product of the training subset to the corresponding at least one property for each product of the training subset. After the mapping function is inferred, it is used for determining properties of other products of the library from their corresponding input features vectors.

Abstract: The present invention provides a method for ranking the affinity of each of a multiplicity of different molecules for a target molecule which is capable of unfolding due to a thermal change.

Abstract: The present invention provides a method for ranking the affinity of each of a multiplicity of different molecules for a target molecule which is capable of unfolding due to a thermal change.

Abstract: A microtiter plate system includes an integral heater. In an embodiment, the integral heater includes a heater plate. In another embodiment, the integral heater includes resistive heater wires positioned beneath and/or between the wells of a microtiter plate. In an embodiment, the microtiter plate system includes optically clear well bottoms that permit sensing and measurement of samples through the optically clear well bottoms. In an implementation, an optically clear heater is positioned beneath the optically clear well bottoms. In an alternative implementation, resistive heater wires are positioned between the wells. In an embodiment, the microtiter plate system includes a microtiter plate lid with an integral heater, which can be implemented using a heater plate, resistive wires, and the like.

Abstract: The present invention provides a method for functionally classifying a protein that is capable of unfolding due to a thermal change. The method comprises screening one or more of a multiplicity of different molecules for their ability to shift the thermal unfolding curve of the protein, wherein a shift in the thermal unfolding curve indicates that the molecule binds to the protein or affects the stability in a measurable way; generating an activity spectrum for the protein wherein the activity spectrum reflects a set of molecules, from the multiplicity of molecules, that shift the thermal unfolding curve, of the protein and therefore are ligands that bind to the protein, comparing the activity spectrum for the protein to one or more functional reference spectrum lists; and classifying the protein according to the set of molecules in the multiplicity of different molecules that shift the thermal unfolding curve of the protein.

Abstract: A method, system, and computer product is presented for mapping a set of patterns into an m-dimensional space so as to preserve relationships that may exist between these patterns. A subset of the input patterns is chosen and mapped into the m-dimensional space using an iterative nonlinear mapping process based on subset refinements. A set of n attributes are determined for each pattern, and one or more neural networks or other supervised machine learning techniques are then trained in accordance with the mapping produced by the iterative process. Additional input patterns not in the subset are mapped into the m-dimensional space by determining their n input attributes and using the neural networks in a feed-forward (prediction) mode.

Abstract: A microtiter plate system includes an integral heater. In an embodiment, the integral heater includes a heater plate. In another embodiment, the integral heater includes resistive heater wires positioned beneath and/or between the wells of a microtiter plate. In an embodiment, the microtiter plate system includes optically clear well bottoms that permit sensing and measurement of samples through the optically clear well bottoms. In an implementation, an optically clear heater is positioned beneath the optically clear well bottoms. In an alternative implementation, resistive heater wires are positioned between the wells. In an embodiment, the microtiter plate system includes a microtiter plate lid with an integral heater, which can be implemented using a heater plate, resistive wires, and the like.

Abstract: A method and computer product is presented for mapping n-dimensional input patterns into an m-dimensional space so as to preserve relationships that may exist in the n-dimensional space. A subset of the input patterns is chosen and mapped into the m-dimensional space using an iterative nonlinear mapping process. A set of locally defined neural networks is created, then trained in accordance with the mapping produced by the iterative process. Additional input patterns not in the subset are mapped into the m-dimensional space by using one of the local neural networks. In an alternative embodiment, the local neural networks are only used after training and use of a global neural network. The global neural network is trained in accordance with the mapping produced by the iterative process. Input patterns are initially projected into the m-dimensional space using the global neural network. Local neural networks are then used to refine the results of the global network.

Abstract: A microtiter plate system includes an integral heater. In an embodiment, the integral heater includes a heater plate. In another embodiment, the integral heater includes resistive heater wires positioned beneath and/or between the wells of a microtiter plate. In an embodiment, the microtiter plate system includes optically clear well bottoms that permit sensing and measurement of samples through the optically clear well bottoms. In an implementation, an optically clear heater is positioned beneath the optically clear well bottoms. In an alternative implementation, resistive heater wires are positioned between the wells. In an embodiment, the microtiter plate system includes a microtiter plate lid with an integral heater, which can be implemented using a heater plate, resistive wires, and the like.

Abstract: The present invention determines properties of combinatorial library products from features of library building blocks. At least one feature is determined for each building block of a combinatorial library having a plurality of products. A training subset of products is selected from the products, and at least one property is determined for each product of the training subset. A building block set is identified for each product of the training subset, and an input features vector is formed from the features of the identified building blocks for each product of the training subset. A supervised machine learning approach is used to infer a mapping function that transforms the input features vector for each product of the training subset to the corresponding at least one property for each product of the training subset. After the mapping function is inferred, it is used for determining properties of other products of the library from their corresponding input features vectors.

Abstract: The present invention provides a method for functionally classifying a protein that is capable of unfolding due to a thermal change. The method comprises screening one or more of a multiplicity of different molecules for their ability to shift the thermal unfolding curve of the protein, wherein a shift in the thermal unfolding curve indicates that the molecule binds to the protein or affects the stability in a measurable way; generating an activity spectrum for the protein wherein the activity spectrum reflects a set of molecules, from the multiplicity of molecules, that shift the thermal unfolding curve, of the protein and therefore are ligands that bind to the protein, comparing the activity spectrum for the protein to one or more functional reference spectrum lists; and classifying the protein according to the set of molecules in the multiplicity of different molecules that shift the thermal unfolding curve of the protein.