The present disclosure relates to methods of data encryption and data storage using molecular systems. The present disclosure also relates to molecular systems and methods for solving a polynomial time problem. Benefits of the methods and systems disclosed herein can include providing for the secure storage and retrieval of large amounts of encrypted data in a stable molecular system having random-access capability. Benefits of the methods and systems disclosed herein can include providing molecular computing systems that can solve complex polynomial time problems.

The disclosure relates to methods and systems for identifying chromosomal structural variants in a subject using chromosomal conformational capture data, relating the chromosomal structural variants to diseases or disorders, and methods of treating same.

The disclosure relates to methods and systems for identifying chromosomal structural variants in a subject using chromosomal conformational capture data, relating the chromosomal structural variants to diseases or disorders, and methods of treating same.

A method for training molecular binding models includes: using a to-be-trained molecular binding model to determine, based on protein feature information and molecular feature information, binding activity feature information, embedding feature information and eutectic feature information between sample protein molecules and sample alternative molecules; determining a training loss of the to-be-trained molecular binding model based on the binding activity feature information, the embedding feature information and the eutectic feature information; and outputting the molecular binding model as a trained molecular binding model when the training loss meets a training target; the trained molecular binding model being configured to determine binding activity feature information between a target protein molecule and a target alternative molecule to predict the binding activity of a compound after virtual binding of the target protein molecule and the target alternative molecule.

Some aspects of the present invention include a system for computationally prediction of oscillation patterns of charges in a DNA sequence. Such a system includes one or more means for computationally predicting proton wires with longitudinal (coaxial) hydrogen bonds in the DNA sequence; and at least one means for predicting electron wires in the DNA sequence. These wires connect the aromatic rings of DNA basepairs. The above system includes at least one means for predicting tautomeric oscillations in said DNA.

A method according to some aspects of the present invention for computationally predicting oscillation pattern of charges in a DNA sequence includes: computationally predicting proton wires containing longitudinal (coaxial) hydrogen bonds, the wires spanning at least two DNA basepairs; predicting electron wires in the DNA which includes stretches of purines; and predicting tautomeric oscillations in the DNA.

The present invention relates to a method for code standardizing DNA (a) C, T, A, and G are designated as 00, 01, 10, and 11, respectively, and (b) when each base is a base pair of G and C and A and T, in the 5′ to 3′ direction, designated as 1100 for G and C, 0011 for C and G, and 1001 for A and T and 0110 for T and A. As a result, the DNA code standardization method of the present invention provides an easy method for identifying specific patterns, secondary structures, and nucleotide sequence variations within the nucleotide sequence, and facilitates the prediction of diseases by using disease-specific sequence mutations such as SNPs. It provides an easy method for identifying a specific pattern present in a nucleotide sequence such as a DNA fragment or an aptamer.

The present invention relates to a method for code standardizing DNA (a) C, T, A, and G are designated as 00, 01, 10, and 11, respectively, and (b) when each base is a base pair of G and C and A and T, in the 5′ to 3′ direction, designated as 1100 for G and C, 0011 for C and G, and 1001 for A and T and 0110 for T and A. As a result, the DNA code standardization method of the present invention provides an easy method for identifying specific patterns, secondary structures, and nucleotide sequence variations within the nucleotide sequence, and facilitates the prediction of diseases by using disease-specific sequence mutations such as SNPs. It provides an easy method for identifying a specific pattern present in a nucleotide sequence such as a DNA fragment or an aptamer.

Disclosed herein are optimized guide RNAs (gRNAs) and methods of designing and using said optimized gRNAs that have increased target binding specificity and reduced off-target binding.

Disclosed herein are optimized guide RNAs (gRNAs) and methods of designing and using said optimized gRNAs that have increased target binding specificity and reduced off-target binding.

Methods for designing scaffolded RNA nanostructures of desired shape are described. In some forms, the methods design nucleic acid “staple” sequences that hybridize to a user-defined RNA scaffold and fold it into the desired shape based on A-form helical nucleic acid geometry. In some forms, the methods implement asymmetry in nucleotide positions across two helices of an edge to account for A-form nucleic acid geometry. In preferred forms, crossover asymmetry is implemented in the staples. In other forms, crossover asymmetry is implemented in the RNA scaffold. In other forms, the methods do not introduce crossover asymmetry. Scaffolded RNA nanostructures produced according to the methods including messenger RNAs, replicating RNAs, functional RNAs and other RNA species within the scaffold, staples, or both scaffold and staples are provided. Modified nanostructures including chemically modified nucleotides are also described.