Methods and compositions are provided to identify oligonucleotides that bind targets of interest. The targets include tissues, cells, circulating biomarkers such as microvesicles, including those derived from various diseases. The oligonucleotides can be used in diagnostic and therapeutic applications.

Methods and compositions are provided to identify oligonucleotides that bind targets of interest. The targets include tissues, cells, circulating biomarkers such as microvesicles, including those derived from various diseases. The oligonucleotides can be used in diagnostic and therapeutic applications.

Methods and compositions are provided to identify oligonucleotides that bind targets of interest. The targets include tissues, cells, circulating biomarkers such as microvesicles, including those derived from various diseases. The oligonucleotides can be used in diagnostic and therapeutic applications.

Methods and compositions are provided to identify oligonucleotides that bind targets of interest. The targets include tissues, cells, circulating biomarkers such as microvesicles, including those derived from various diseases. The oligonucleotides can be used in diagnostic and therapeutic applications.

This application relates to molecular biology, and more specifically to a method which uses the molecular recognition between a target molecule ligand and an aptamer, magnetic separation and MS qualitative and quantitative analysis to enable the association between the detection of multi molecules and information of multiple functional groups, and effectively determine the correlation between molecules and functional groups of the body or tissue. This application can easily purify the target molecules by magnetic separation and can effectively obtain the target molecule group based on the high specificity and affinity of the aptamer. In addition, based on the MS detection, this application can effectively perform the qualification and quantification of the multi molecules, achieving the secondary molecular detection and improving the detection accuracy. The simultaneous qualification and quantification of multi molecules can not only accurately reflect the relationship among molecules, but also reveal the interrelationship among body functions, playing a significant role in the proteomics and genomics research and clinical molecular detection.

The invention relates to a method of identifying or producing an aptamer, the method comprising the steps of: a) Providing a candidate mixture of nucleic acids; b) Contacting the candidate mixture with a target sample; c) Partitioning nucleic acids that bind to the target sample from those that do not bind; d) Amplifying the binding nucleic acids to produce a population of nucleic acids that bind the target sample; e) Single strand displacement of the amplified nucleic acids, f) optionally repeating the steps a) to e), thereby identifying or producing an aptamer, wherein the target sample provides one or more peptides and/or proteins in a denatured form.

The invention relates to a method of identifying or producing an aptamer, the method comprising the steps of: a) Providing a candidate mixture of nucleic acids; b) Contacting the candidate mixture with a target sample; c) Partitioning nucleic acids that bind to the target sample from those that do not bind; d) Amplifying the binding nucleic acids to produce a population of nucleic acids that bind the target sample; e) Single strand displacement of the amplified nucleic acids, f) optionally repeating the steps a) to e), thereby identifying or producing an aptamer, wherein the target sample provides one or more peptides and/or proteins in a denatured form.

The present disclosure relates to a closed loop aptamer development system that identifies one or more aptamers observed experimentally and implements machine-learning models to identify other aptamers not observed experimentally. Particularly, aspects of the present disclosure are directed to receiving a query concerning one or more targets, acquiring a library of aptamers that potential satisfy the query, identifying a first set of aptamers from the library of aptamers that substantially or completely satisfy the query, obtaining sequence data for the first set of aptamers, generating, by a prediction model, a third set of aptamers derived from the sequence data for the first set of aptamers, validating the third set of aptamers that substantially or completely satisfy the query, and upon validating the third set of aptamers and in response to the query, providing the third set of aptamers as a result to the query.

The present disclosure relates to a closed loop aptamer development system that identifies one or more aptamers observed experimentally and implements machine-learning models to identify other aptamers not observed experimentally. Particularly, aspects of the present disclosure are directed to receiving a query concerning one or more targets, acquiring a library of aptamers that potential satisfy the query, identifying a first set of aptamers from the library of aptamers that substantially or completely satisfy the query, obtaining sequence data for the first set of aptamers, generating, by a prediction model, a third set of aptamers derived from the sequence data for the first set of aptamers, validating the third set of aptamers that substantially or completely satisfy the query, and upon validating the third set of aptamers and in response to the query, providing the third set of aptamers as a result to the query.

This disclosure describes methods and compositions for protein and peptide sequencing.