Abstract: According to an example, a method of analyzing an output of a sequencer is provided comprising identifying genetic targets, obtaining target signature snippets responsive thereto, each target signature snippet derived from a genetic sequence of the genetic targets, receiving portions of a test sequence output by a sequencer sequencing a sample in real time, determining, in real time or near-real time with the sequencer sequencing the sample, whether a target signature snippet of the target signature snippets is in at least one portion of the test sequence, determining, for each genetic target, a probability the genetic target is in the sample based on the determination of whether the target signature snippet is present in the at least one portion of the test sequence, and outputting an analysis of the sample indicating the respective probability that each genetic target is present in the sample.

Abstract: According to at least one example, a method of filtering signature snippets is provided comprising identifying a group of genetic targets, obtaining a plurality of sets of one or more target signature snippets responsive to identifying the group of genetic targets, each set of one or more target signature snippets corresponding to a respective genetic target of the group of genetic targets and being derived from a genetic sequence of the respective genetic target, filtering the plurality of sets of one or more target signature snippets to identify a set of one or more universal target signature snippets, and outputting the set of one or more universal target signature snippets.

Abstract: Techniques for generating custom libraries for nucleic acid synthesis are disclosed. The techniques include: obtaining one or more nucleic acid sequences for which to generate a subsequence catalog; performing pattern recognition on the one or more nucleic acid sequences, to identify subsequences that are repeated in the one or more nucleic acid sequences; and generating the subsequence catalog, including the subsequences that are repeated in the one or more nucleic acid sequences.

Abstract: A method of identifying regions of malicious organic sequences includes identifying a plurality of benign snippets derived from a first sequence obtained from at least one benign organism; extracting a plurality of candidate signature snippets from a second sequence obtained from a malicious organism; determining, for each of the plurality of candidate signature snippets, whether the candidate signature snippet matches at least one of the plurality of benign snippets; and responsive to the candidate signature snippet not matching the at least one of the plurality of benign snippets, identifying the candidate signature snippet as a malicious signature snippet.

Abstract: Disclosed techniques include generating a first set of sequence snippets from a set of nucleic acid sequences having a first trait; generating a second set of second sequence snippets from a set of nucleic acid sequences having a second trait; identifying a third set of sequence snippets categorized as being of a particular type; and filtering the first set of sequence snippets and the second set of sequence snippets to remove at least one sequence snippet in the third set of sequence snippets.

Abstract: A body garment including sensors distributed throughout the garment, each sensor senses body state information from a local surface area of a body; and sensor nodes in proximity to the plurality of sensors, each sensor node including a processor to receive sensing body state information from at least one of the plurality of sensors. Each processor is configured to receive body state information locally from sensors, to utilize the information to determine a local surface shape of the surface of a portion of the body part; and to exchange local surface shape information with neighboring sensor nodes. At least one processor of utilizes the local surface shape information received from the sensor nodes to generate one overall model of a surface shape of the entire surface of the body part covered by the garment.

Abstract: A method of identifying regions of malicious organic sequences includes identifying a plurality of benign snippets derived from a first sequence obtained from at least one benign organism; extracting a plurality of candidate signature snippets from a second sequence obtained from a malicious organism; determining, for each of the plurality of candidate signature snippets, whether the candidate signature snippet matches at least one of the plurality of benign snippets; and responsive to the candidate signature snippet not matching the at least one of the plurality of benign snippets, identifying the candidate signature snippet as a malicious signature snippet.

Abstract: A body garment including sensors distributed throughout the garment, each sensor senses body state information from a local surface area of a body; and sensor nodes in proximity to the plurality of sensors, each sensor node including a processor to receive sensing body state information from at least one of the plurality of sensors. Each processor is configured to receive body state information locally from sensors, to utilize the information to determine a local surface shape of the surface of a portion of the body part; and to exchange local surface shape information with neighboring sensor nodes. At least one processor of utilizes the local surface shape information received from the sensor nodes to generate one overall model of a surface shape of the entire surface of the body part covered by the garment.

Abstract: A body garment including sensors distributed throughout the garment, each sensor senses body state information from a local surface area of a body; and sensor nodes in proximity to the plurality of sensors, each sensor node including a processor to receive sensing body state information from at least one of the plurality of sensors. Each processor is configured to receive body state information locally from sensors, to utilize the information to determine a local surface shape of the surface of a portion of the body part; and to exchange local surface shape information with neighboring sensor nodes. At least one processor of utilizes the local surface shape information received from the sensor nodes to generate one overall model of a surface shape of the entire surface of the body part covered by the garment.

Abstract: The present invention is directed to a system and method for emulating smart grid devices in a smart grid for demand-response program analysis and optimization. Smart grid devices may be emulated in a virtual environment on a server, and can also be emulated individually on smart grid devices themselves. Demand-response programs can be simulated in a virtual environment with virtual emulated smart grid devices, or they can be simulated in a hybrid real-virtual environment with both real smart grid devices and virtual emulated smart grid devices. Demand-response programs can be simulated serially or in parallel. Additionally, such hybrid demand-response program simulations can be enhanced and optimized by including data obtained from the real smart grid devices into the simulation feed-back loop.

Abstract: A body garment including sensors distributed throughout the garment, each sensor senses body state information from a local surface area of a body; and sensor nodes in proximity to the plurality of sensors, each sensor node including a processor to receive sensing body state information from at least one of the plurality of sensors. Each processor is configured to receive body state information locally from sensors, to utilize the information to determine a local surface shape of the surface of a portion of the body part; and to exchange local surface shape information with neighboring sensor nodes. At least one processor of utilizes the local surface shape information received from the sensor nodes to generate one overall model of a surface shape of the entire surface of the body part covered by the garment.

Abstract: Described herein are methods of evaluating the expression levels of DNA parts encoding proteins in test circuits. In particular, the methods disclosed herein are useful to evaluate the expression of an output protein regulated by a regulatory protein-genetic element pair.

Abstract: The present invention is directed to a system and method for implementing demand-response operations with interoperating rules engines in a smart grid, and for implementing demand-response operations with interoperating rules engines distributed throughout the system in a smart grid.

Abstract: The present invention is directed to a system and method for emulating smart grid devices in a smart grid for demand-response program analysis and optimization. Smart grid devices may be emulated in a virtual environment on a server, and can also be emulated individually on smart grid devices themselves. Demand-response programs can be simulated in a virtual environment with virtual emulated smart grid devices, or they can be simulated in a hybrid real-virtual environment with both real smart grid devices and virtual emulated smart grid devices. Demand-response programs can be simulated serially or in parallel. Additionally, such hybrid demand-response program simulations can be enhanced and optimized by including data obtained from the real smart grid devices into the simulation feed-back loop.

Abstract: Described herein are methods of evaluating the expression levels of DNA parts encoding proteins in test circuits. In particular, the methods disclosed herein are useful to evaluate the expression of an output protein regulated by a regulatory protein-genetic element pair.

Abstract: The present invention is directed to a system and method for quantifying, measuring and verifying the results of demand side energy management programs in a smart grid by the selection of a smart grid device from the universe of smart grid devices participating in the demand side energy management program by a selecting energy collection server and collecting data from the selected smart grid device in order to reduce the load on the network. An agent resident on the selected smart grid device transmits data to the selecting energy collection server which utilizes the data to verify the demand side energy management program.