Provided herein are methods for rational design of nicotine haptens. More particularly, provided herein are methods for designing, selecting, and synthesizing nicotine haptens and nicotine hapten conjugates. Also provided herein are novel nicotine haptens and methods for using nicotine haptens to treat nicotine addiction.

A method includes receiving one input feature and one output feature of importance of polymers used to stabilize a protein. A set of polymers from a library are identified based on the input feature and the output feature of importance that are applied to a machine learning model. Data for each polymer in the library includes features for each polymer and reagents for stabilizing the protein. Each polymer in the identified set is used to stabilize samples of the protein in well plates in a well plate array based on the reagents from the library data in the identified set. A score for each sample of the protein is assigned by comparing the measured output feature from the well plates corresponding to the identified set to the output feature of importance. The samples of the protein are identified having scores higher than a predefined threshold.

A method includes receiving one input feature and one output feature of importance of polymers used to stabilize a protein. A set of polymers from a library are identified based on the input feature and the output feature of importance that are applied to a machine learning model. Data for each polymer in the library includes features for each polymer and reagents for stabilizing the protein. Each polymer in the identified set is used to stabilize samples of the protein in well plates in a well plate array based on the reagents from the library data in the identified set. A score for each sample of the protein is assigned by comparing the measured output feature from the well plates corresponding to the identified set to the output feature of importance. The samples of the protein are identified having scores higher than a predefined threshold.

A method of making a polypeptide including at least one covalent bond between a pair of reactive side chains of corresponding amino acids, wherein the covalent bond is insensitive to reduction is provided including genetically modifying a genomically recoded organism to express a corresponding synthetase, tRNA or synthetase/tRNA pair for translating mRNA encoding the corresponding amino acids having the reactive side chains into the polypeptide and to express the polypeptide including the at least one pair of the reactive side chains wherein the reactive side chains are oriented near one another when the expressed polypeptide is in a folded configuration, wherein the reactive side chains react to form the covalent bond that is insensitive to reduction.

Disclosed herein are systems and methods for direct classification of biological datasets. The datasets may include raw mass spectrometry data. Some aspects include training a classifier for direct classification of raw data, and some aspects include applying the classifier.

Disclosed herein in are methods and systems for determining genetic variants (e.g., copy number variation) in a polynucleotide sample. A method for determining copy number variations includes tagging double-stranded polynucleotides with duplex tags, sequencing polynucleotides from the sample and estimating total number of polynucleotides mapping to selected genetic loci. The estimate of total number of polynucleotides can involve estimating the number of double-stranded polynucleotides in the original sample for which no sequence reads are generated. This number can be generated using the number of polynucleotides for which reads for both complementary strands are detected and reads for which only one of the two complementary strands is detected.

Computational methods for classifying and predicting protein side chain conformations utilizing a data driven scoring function are disclosed. According to some embodiments, the methods may include obtaining structure data representing a plurality of conformations of a compound. The methods may also include determining structural differences among the conformations. The methods may also include classifying, based on the structural differences, the conformations into one or more clusters. The methods may also include determining representative conformations of the dusters, wherein an average structural difference between a representative conformation of a duster and conformations in the duster is below a predetermined threshold. The method may further include determining the representative conformations as poses of the compound.

A system and a method for image alignment between at least two images to a three-dimensional model. The method including: determining a lower bound and an upper bound of an acceptable likelihood of mismatch between the at least two images; evaluating the likelihood of mismatch between the at least two images over a set of poses (r), shifts (t), or both poses (r) and shifts (t); and discarding those evaluations resulting beyond the lower bound and upper bound.

Systems and methods to characterize one or more microorganisms or DNA fragments thereof are disclosed. Exemplary methods and systems use comparison of DNA sequencing information to information in one or more databases to characterize the one or more microorganism or DNA fragments thereof. Exemplary systems and methods can be used in a clinical setting to provide rapid analysis of microorganisms that may be a cause of infection.

Systems and methods to characterize one or more microorganisms or DNA fragments thereof are disclosed. Exemplary methods and systems use comparison of DNA sequencing information to information in one or more databases to characterize the one or more microorganism or DNA fragments thereof. Exemplary systems and methods can be used in a clinical setting to provide rapid analysis of microorganisms that may be a cause of infection.