Abstract: A method for sequencing biopolymers. The method includes selecting with a sequence generator module an input nucleotide sequence having plural k-mers; simulating with a deep learning simulator, actual electrical current signals corresponding to the input nucleotide sequence; identifying reads that correspond to the actual electrical current signals; and displaying the reads. The deep learning simulator includes a context-dependent deep learning model that takes into consideration a position of a k-mer of the plural k-mers on the input nucleotide sequence when calculating a corresponding actual electrical current.

Abstract: A method for structure simulation for super-resolution fluorescence microscopy, the method including receiving a first image having a first resolution, which is indicative of a distribution of fluorophores; applying a Markov model to the fluorophores to indicate an emission state of the fluorophores; generating a plurality of second images, having the first resolution, based on the first image and the Markov model; adding DC background to the plurality of second images to generate a plurality of third images, having the first resolution; downsampling the plurality of third images to obtain a plurality of fourth images, which have a second resolution, lower than the first resolution; and generating a time-series, low-resolution images by adding noise to the plurality of fourth images. The time-series, low-resolution images have the second resolution.

Abstract: A method for global mapping between a first sequence Xp and a second sequence Xg.

Abstract: A method for image reconstruction from plural copies, the method including receiving a series of measured projections pi of a target object h and associated background; iteratively reconstructing images hi(k) of the target object and images gi(k) of the background of the target object for each member i of the series of the measured projections pi over plural iterations k; and generating a final image of the target object h, based on the reconstructed images hi, when a set condition is met. The index i describes how many elements are in the series of projections pi, and iteration k indicates how many times the reconstruction of the image target is performed.

Abstract: A method for structure simulation for super-resolution fluorescence microscopy, the method including receiving a first image having a first resolution, which is indicative of a distribution of fluorophores; applying a Markov model to the fluorophores to indicate an emission state of the fluorophores; generating a plurality of second images, having the first resolution, based on the first image and the Markov model; adding DC background to the plurality of second images to generate a plurality of third images, having the first resolution; downsampling the plurality of third images to obtain a plurality of fourth images, which have a second resolution, lower than the first resolution; and generating a time-series, low-resolution images by adding noise to the plurality of fourth images. The time-series, low-resolution images have the second resolution.

Abstract: A method for structure simulation for super-resolution fluorescence microscopy, the method including receiving a first image having a first resolution, which is indicative of a distribution of fluorophores; applying a Markov model to the fluorophores to indicate an emission state of the fluorophores; generating a plurality of second images, having the first resolution, based on the first image and the Markov model; adding DC background to the plurality of second images to generate a plurality of third images, having the first resolution; downsampling the plurality of third images to obtain a plurality of fourth images, which have a second resolution, lower than the first resolution; and generating a time-series, low-resolution images by adding noise to the plurality of fourth images. The time-series, low-resolution images have the second resolution.

Abstract: Provided is an apparatus and method for aligning fiducial markers. The apparatus may align positions of the fiducial markers on the two or more micrographs forming a two or more point sets corresponding to the two or more micrographs; create a first set of matched fiducial markers and unmatched fiducial markers; transform unmatched fiducial markers into transformed point sets and match the unmatched fiducial markers resulting in a second set of matched fiducial markers. The matching of the second set of matched fiducial markers results in improved alignment of a large number of fiducial markers. The aligned positions of fiducial markers may be constrained by an upper bound of transformation deviation of aligning positions of fiducial markers on two or more micrographs.

Abstract: A method for similarity searching directly on nanopore raw current signals, the method including receiving a reference genome sequence; receiving a query genome sequence; transforming the reference genome sequence, with a nanopore sequencing device, into a raw current signal X; transforming the query genome sequence, based on a pore model, into a query current signal Y; and mapping the query current signal Y to the raw current signal X based on a subsequence extension of dynamic time warping distance Dist, which calculates a distance between the raw current signal X and a padded signal query Y?. The padded signal query Y? is the query current signal Y to which an element y0 has been added, the raw current signal X and the query current signal Y are electrical currents, and the raw current signal X corresponds to a genome of an organism.

Abstract: A method for sequencing biopolymers. The method includes selecting with a sequence generator module an input nucleotide sequence having plural k-mers; simulating with a deep learning simulator, actual electrical current signals corresponding to the input nucleotide sequence; identifying reads that correspond to the actual electrical current signals; and displaying the reads. The deep learning simulator includes a context-dependent deep learning model that takes into consideration a position of a k-mer of the plural k-mers on the input nucleotide sequence when calculating a corresponding actual electrical current.

Abstract: A method for sequencing biopolymers. The method includes selecting with a sequence generator module an input nucleotide sequence having plural k-mers; simulating with a deep learning simulator, actual electrical current signals corresponding to the input nucleotide sequence; identifying reads that correspond to the actual electrical current signals; and displaying the reads. The deep learning simulator includes a context-dependent deep learning model that takes into consideration a position of a k-mer of the plural k-mers on the input nucleotide sequence when calculating a corresponding actual electrical current.

Abstract: A method for image reconstruction from plural copies, the method including receiving a series of measured projections pi of a target object h and associated background; iteratively reconstructing images hi(k) of the target object and images gi(k) of the background of the target object for each member i of the series of the measured projections pi over plural iterations k; and generating a final image of the target object h, based on the reconstructed images hi, when a set condition is met. The index i describes how many elements are in the series of projections pi, and iteration k indicates how many times the reconstruction of the image target is performed.

Abstract: A method for sequencing biopolymers. The method includes selecting with a sequence generator module an input nucleotide sequence having plural k-mers; simulating with a deep learning simulator, actual electrical current signals corresponding to the input nucleotide sequence; identifying reads that correspond to the actual electrical current signals; and displaying the reads. The deep learning simulator includes a context-dependent deep learning model that takes into consideration a position of a k-mer of the plural k-mers on the input nucleotide sequence when calculating a corresponding actual electrical current.

Abstract: A method for structure simulation for super-resolution fluorescence microscopy, the method including receiving a first image having a first resolution, which is indicative of a distribution of fluorophores; applying a Markov model to the fluorophores to indicate an emission state of the fluorophores; generating a plurality of second images, having the first resolution, based on the first image and the Markov model; adding DC background to the plurality of second images to generate a plurality of third images, having the first resolution; downsampling the plurality of third images to obtain a plurality of fourth images, which have a second resolution, lower than the first resolution; and generating a time-series, low-resolution images by adding noise to the plurality of fourth images. The time-series, low-resolution images have the second resolution.

Abstract: Provided is an apparatus and method for aligning fiducial markers. The apparatus may align positions of the fiducial markers on the two or more micrographs forming a two or more point sets corresponding to the two or more micrographs; create a first set of matched fiducial markers and unmatched fiducial markers; transform unmatched fiducial markers into transformed point sets and match the unmatched fiducial markers resulting in a second set of matched fiducial markers. The matching of the second set of matched fiducial markers results in improved alignment of a large number of fiducial markers. The aligned positions of fiducial markers may be constrained by an upper bound of transformation deviation of aligning positions of fiducial markers on two or more micrographs.

Abstract: A method for global mapping between a first sequence Xp and a second sequence Xg.