We have created novel engineered genetic counter designs and methods of use thereof that utilize DNA recombinases to provide modular systems, termed single invertase memory modules (SIMMs), for encoding memory in cells and cellular systems. Our designs are easily extended to compute to high numbers, by utilizing the >100 known recombinases to create subsequent modules. Flexibility in our engineered genetic counter designs is provided by daisy-chaining individual modular components, i.e., SIMMs together. These modular components of the engineered genetic counters can be combined in other network topologies to create circuits that perform, amongst other things, logic and memory. Our novel engineered genetic counter designs allow for the maintenance of memory and provide the ability to count between discrete states by expressing the recombinases between their cognate recognition sites.

Methods for analyzing signal data generated by sequencing of a polynucleotide strand using a pH-based method of detecting nucleotide incorporation(s). In an embodiment, the method comprises formulating a function that models the output signal of a representative empty well of a reactor array. A time transformation is applied to the empty well function to obtain a time-warped empty well function. The time-warped empty well function is fitted to an output signal from the loaded well representative of a flow that results in a non-incorporation event in the loaded well. The fitted time-warped empty well function can then be used to analyze output signals from the loaded well for other flows.

An analytical framework and modeling process for assessing salinity contamination of soil ecosystems in geographical areas related to oil and gas production sites combines detection and monitoring of unplanned saltwater releases from such production activities with soil impact prediction. The analytical framework and modeling process enables an assessment of risks associated with saltwater disposal from drilling operations to the surrounding environment and the impact on soils, aquifers, rangeland, cropland, and adjoining areas by monitoring water movement and other soil conditions, and generating predictive output data for landowners, farmers, oil and gas production site operators, governmental regulators, and other end users for contamination mitigation and agricultural activities.

A glucose tolerance analyzer comprising: an accepting section configured to accept inputs of information regarding a type of food or drink ingested by a subject, information regarding an intake amount of the food or drink, and information regarding an amount of glucose in the subject after the ingestion of the food or drink; an output section configured to output an analysis result of glucose tolerance; and a controller configured to: calculate a reference value for analyzing glucose tolerance of the subject based on the accepted information regarding the type of the food or drink ingested by the subject and the information regarding the intake amount of the food or drink, and based on a predetermined index regarding blood glucose increase due to food or drink; analyze the glucose tolerance of the subject based on the accepted information regarding the amount of glucose and based on the calculated reference value; and control the output section to output an obtained analysis result as an analysis result of glucose tolerance.

Systems and methods for analyzing genetic sequence data involve: (a) obtaining, by a computer system, genetic sequencing data pertaining to a subject; (b) splitting the genetic sequencing data into a plurality of segments; (c) processing the genetic sequencing data such that intra-segment reads, read pairs with both mates mapped to the same data set, are saved to a respective plurality of individual binary alignment map (BAM) files corresponding to that respective segment; (d) processing the genetic sequencing data such that inter-segment reads, read pairs with both mates mapped to different segments, are saved into at least a second BAM file; and (e) processing at least the first plurality of BAM files along parallel processing paths. The plurality of segments may correspond to any given number of genomic subregions and may be selected based upon the number of processing cores used in the parallel processing.

An apparatus for processing a set of data values, a data value representing a physiological measure of a body fluid at a time instant, comprising: an estimated probability function calculator for calculating an estimated probability function associated with the set of data values; a transform calculator for calculating a non-linear transform rule using a predetermined target probability function being different from the estimated probability function, so that the probability function of a set of transform data values is closer to the target probability function than the estimated probability function; and a transformer for applying the transform rule to the set of data values or to at least one further data value not included in the set of data values and sampled at the different time instant from the time instants for the set of data values to obtain at least one transformed value representing the physiological measure.