Techniques for multi-dimensional signal analysis are described herein. The techniques may be used in one or more sequencing applications. For example, according to some aspects, there is provided a method comprising: determining information about a sample that emits emission light in response to excitation light based on at least one of pulse duration and interpulse duration and at least two of wavelength, intensity, and lifetime of the emission light, wherein the sample comprises a reagent configured to be coupled to a luminescent label, and wherein a shielding element is disposed between the reagent and the luminescent label.

Systems and methods to automatically de novo assemble a set of unordered read sequences into one or more, larger nucleotide sequences are presented. The method involves first creating two identical sets of the reads, dividing each read in both sets into smaller sorted mer sequences and then comparing the mers for each read in set 1 to the mers from each read in set 2 to exhaustively identify overlapping segments. Overlap information is used to construct a modified assembly string graph, traversal of which produces a sorted string graph layout file consisting of all the reads ordered left to right including their approximate starting offset position. The sorted string graph layout file is then processed by a novel multiple sequence alignment system that uses mer matches between all the overlapping reads at a given position to place matching individual bases from each read into columns from which an overall consensus sequence is determined.

Systems and methods to automatically de novo assemble a set of unordered read sequences into one or more, larger nucleotide sequences are presented. The method involves first creating two identical sets of the reads, dividing each read in both sets into smaller sorted mer sequences and then comparing the mers for each read in set 1 to the mers from each read in set 2 to exhaustively identify overlapping segments. Overlap information is used to construct a modified assembly string graph, traversal of which produces a sorted string graph layout file consisting of all the reads ordered left to right including their approximate starting offset position. The sorted string graph layout file is then processed by a novel multiple sequence alignment system that uses mer matches between all the overlapping reads at a given position to place matching individual bases from each read into columns from which an overall consensus sequence is determined.

The technology disclosed generates a reference array of variant data for locations that are shared between read results which are to be compared, and generates hashes over a selected pattern length of positions in the reference array to independently produce non-unique window hashes for base patterns in the read results. It then selects for comparison window hashes that occur less than a ceiling number of times and compares the selected window hashes to identify common window hashes between the read results. It then determines a similarity measure for the read results based on the common window hashes.

Systems and methods are provided for identifying characteristics of a subject using a biofield scan obtained from the subject. An embodiment can include a method for cross-correlating biofield scans to an enome database, and/or a genome database. A phenotype history and a biofield scan can be created from a user. A user's biofield scan can be created from measured amplitude and frequency. A database is created from a user's phenotype history, and biofield scan. The user's phenotype history and biofield scans are then correlated with known physical and biochemical characteristics. A biofield signature is created and compared to the user's phenotype history, and biofield scan.

Provided herein are compositions, devices, systems and methods for the generation and use of secured biomolecule-based information for storage. Further described herein are compositions, devices, systems and methods for bioencryption or biodecryption of information. Conversion of a digital sequence to a nucleic based sequence includes a step of selection of one or more bioencryption methods.

Provided herein are compositions, devices, systems and methods for the generation and use of secured biomolecule-based information for storage. Further described herein are compositions, devices, systems and methods for bioencryption or biodecryption of information. Conversion of a digital sequence to a nucleic based sequence includes a step of selection of one or more bioencryption methods.

The present invention provides a novel approach to matching personality traits, as determined through observational or self-assessment reporting in combination with specific loci and identifiable variations within an individual's nucleotide sequence in the form of SNPs. The present invention further utilizes an individual's cyber footprint, in combination with SNPs and traditional assessment and self-assessment techniques, to define a testing and reinforcement mechanism for strengthening the interdependence and accuracy of each type of reporting in order to bolster the reliability of each alone and in combination.

The present invention provides a novel approach to matching personality traits, as determined through observational or self-assessment reporting in combination with specific loci and identifiable variations within an individual's nucleotide sequence in the form of SNPs. The present invention further utilizes an individual's cyber footprint, in combination with SNPs and traditional assessment and self-assessment techniques, to define a testing and reinforcement mechanism for strengthening the interdependence and accuracy of each type of reporting in order to bolster the reliability of each alone and in combination.

The technology disclosed generates a reference array of variant data for locations that are shared between read results which are to be compared, and generates hashes over a selected pattern length of positions in the reference array to independently produce non-unique window hashes for base patterns in the read results. It then selects for comparison window hashes that occur less than a ceiling number of times and compares the selected window hashes to identify common window hashes between the read results. It then determines a similarity measure for the read results based on the common window hashes.