The present invention teaches multiple three-dimensional nanosensing geometries for simultaneously assaying both large and small bio-related molecules in one device. The invention delivers broader sensitivity and selectivity than devices that assay small or large molecules separately. The combination assays all classes of molecules, e.g., proteins, lipoproteins, nucleoproteins, lipids, phospholipids, carbohydrates, nucleic acids, simple sugars, hormones, volatile organic compounds, drugs, drug metabolites, etc. Broad collection enables i) rapid and accurate diagnosis, ii) likely courses of treatments, and iii) timely feedback that monitors and follows the progressions of treatment(s). In one example, a patient's pattern of blood lipids, proteins—including proteins with alternate cleavage patterns, peptides—including endocrine peptides, thyroxine (and/or other hormones), and drug metabolites, forms a profile specific to that patient at that time. The profile is inputted for analysis by comparing it to a library of pooled data. Applying artificial intelligence (AI) to this comparison allows accurate diagnosis and then can suggest historically validated treatments most suited to that patient.

The present invention teaches multiple three-dimensional nanosensing geometries for simultaneously assaying both large and small bio-related molecules in one device. The invention delivers broader sensitivity and selectivity than devices that assay small or large molecules separately. The combination assays all classes of molecules, e.g., proteins, lipoproteins, nucleoproteins, lipids, phospholipids, carbohydrates, nucleic acids, simple sugars, hormones, volatile organic compounds, drugs, drug metabolites, etc. Broad collection enables i) rapid and accurate diagnosis, ii) likely courses of treatments, and iii) timely feedback that monitors and follows the progressions of treatment(s). In one example, a patient's pattern of blood lipids, proteins—including proteins with alternate cleavage patterns, peptides—including endocrine peptides, thyroxine (and/or other hormones), and drug metabolites, forms a profile specific to that patient at that time. The profile is inputted for analysis by comparing it to a library of pooled data. Applying artificial intelligence (AI) to this comparison allows accurate diagnosis and then can suggest historically validated treatments most suited to that patient.

Methods of designing a polynucleotide sequence for expressing a polypeptide-of-interest in a cell are provided. Also provided are artificial transcript sequences generated according to the present teachings. Further provided are methods of estimating the adaptiveness of a transcript sequence encoding a polypeptide-of-interest to a gene expression machinery in a cell.

Methods of designing a polynucleotide sequence for expressing a polypeptide-of-interest in a cell are provided. Also provided are artificial transcript sequences generated according to the present teachings. Further provided are methods of estimating the adaptiveness of a transcript sequence encoding a polypeptide-of-interest to a gene expression machinery in a cell.

This disclosure provides systems and methods for sample processing and data analysis. Sample processing may include nucleic acid sample processing and subsequent sequencing. Some or all of a nucleic acid sample may be sequenced to provide sequence information, which may be stored or otherwise maintained in an electronic storage location. The sequence information may be analyzed with the aid of a computer processor, and the analyzed sequence information may be stored in an electronic storage location that may include a pool or collection of sequence information and analyzed sequence information generated from the nucleic acid sample. Methods and systems of the present disclosure can be used, for example, for the analysis of a nucleic acid sample, for producing one or more libraries, and for producing biomedical reports. Methods and systems of the disclosure can aid in the diagnosis, monitoring, treatment, and prevention of one or more diseases and conditions.

Molecular beacons and developmental methods related thereto. Methods include obtaining a nucleotide sequence for an aptamer that binds to a target analyte. The aptamer comprises a binding domain nucleotide sequence, a first domain nucleotide sequence, and a displacement domain nucleotide sequence complementary to the first domain nucleotide sequence. A molecular beacon is developed based on the nucleotide sequence of the aptamer by preserving the binding domain nucleotide sequence and truncating or extending one or both of the first domain nucleotide sequence or the displacement domain nucleotide sequence. The resultant molecular beacon is developed such that the molecular beacon comprises a Gibbs free energy value that is greater than the Gibbs free energy value of the aptamer.

Molecular beacons and developmental methods related thereto. Methods include obtaining a nucleotide sequence for an aptamer that binds to a target analyte. The aptamer comprises a binding domain nucleotide sequence, a first domain nucleotide sequence, and a displacement domain nucleotide sequence complementary to the first domain nucleotide sequence. A molecular beacon is developed based on the nucleotide sequence of the aptamer by preserving the binding domain nucleotide sequence and truncating or extending one or both of the first domain nucleotide sequence or the displacement domain nucleotide sequence. The resultant molecular beacon is developed such that the molecular beacon comprises a Gibbs free energy value that is greater than the Gibbs free energy value of the aptamer.

A data storage medium includes a substrate. The data storage medium also includes an antifreeze layer coated on at least one surface of the substrate. The data storage medium further includes multiple storage containers located on the substrate. The multiple storage containers store different combinations of plant-based molecules representing data.

A data storage medium includes a substrate. The data storage medium also includes an antifreeze layer coated on at least one surface of the substrate. The data storage medium further includes multiple storage containers located on the substrate. The multiple storage containers store different combinations of plant-based molecules representing data.

Disclosed are methods for identifying bio-molecules with desired properties (or which are most suitable for a round of directed evolution) from complex bio-molecule libraries or sets of such libraries. Some embodiments of the present disclosure provide methods for virtually screening proteins for beneficial properties. Some embodiments of the present disclosure provide methods for virtually screening enzymes for desired activity and/or selectivity for catalytic reactions involving particular substrates. Some embodiments combine screening and directed evolution to design and develop proteins and enzymes having desired properties. Systems and computer program products implementing the methods are also provided.