Abstract: The present invention provides methods for rapidly and efficiently searching biologically-related data space. More specifically, the present invention provides methods for identifying bio-molecules with desired properties, or which are most suitable for acquiring such properties, from complex bio-molecule libraries or sets of such libraries. The present invention also provides methods for modeling sequence-activity relationships, including but not limited to stepwise addition or subtraction techniques, Bayesian regression, ensemble regression and other methods. The present invention further provides digital systems and software for performing the methods provided herein.

Abstract: The present invention provides methods for identifying bio-molecules with desired properties, or which are most suitable for acquiring such properties, from complex bio-molecule libraries or sets of such libraries. More specifically, some embodiments of the present invention provide methods for building sequence-activity models comprising multiplicative terms and using the models to guide directed evolution. In some embodiments, the sequence-activity models include one or more interaction terms, each of which including an interaction coefficient representing the contribution to activity of two or more defined residues. In some embodiments, the models describe relation between protein or nucleic acid sequences and protein activities. In some embodiments, the present invention also provides methods for preparing sequence-activity models, including but not limited to stepwise addition or subtraction techniques, Bayesian regression, ensemble regression and other methods.

Abstract: The present invention provides methods for identifying bio-molecules with desired properties, or which are most suitable for acquiring such properties, from complex bio-molecule libraries or sets of such libraries. More specifically, some embodiments of the present invention provide methods for building sequence-activity models comprising multiplicative terms and using the models to guide directed evolution. In some embodiments, the sequence-activity models include one or more interaction terms, each of which including an interaction coefficient representing the contribution to activity of two or more defined residues. In some embodiments, the models describe relation between protein or nucleic acid sequences and protein activities. In some embodiments, the present invention also provides methods for preparing sequence-activity models, including but not limited to stepwise addition or subtraction techniques, Bayesian regression, ensemble regression and other methods.

Abstract: The present invention provides methods for rapidly and efficiently searching biologically-related data space. More specifically, the present invention provides methods for identifying bio-molecules with desired properties, or which are most suitable for acquiring such properties, from complex bio-molecule libraries or sets of such libraries. The present invention also provides methods for modeling sequence-activity relationships, including but not limited to stepwise addition or subtraction techniques, Bayesian regression, ensemble regression and other methods. The present invention further provides digital systems and software for performing the methods provided herein.

Abstract: The present invention provides methods for identifying bio-molecules with desired properties, or which are most suitable for acquiring such properties, from complex bio-molecule libraries or sets of such libraries. More specifically, some embodiments of the present invention provide methods for building sequence-activity models comprising multiplicative terms and using the models to guide directed evolution. In some embodiments, the sequence-activity models include one or more interaction terms, each of which including an interaction coefficient representing the contribution to activity of two or more defined residues. In some embodiments, the models describe relation between protein or nucleic acid sequences and protein activities. In some embodiments, the present invention also provides methods for preparing sequence-activity models, including but not limited to stepwise addition or subtraction techniques, Bayesian regression, ensemble regression and other methods.

Abstract: The present invention provides methods for rapidly and efficiently searching biologically-related data space. More specifically, the present invention provides methods for identifying bio-molecules with desired properties, or which are most suitable for acquiring such properties, from complex bio-molecule libraries or sets of such libraries. The present invention also provides methods for modeling sequence-activity relationships, including but not limited to stepwise addition or subtraction techniques, Bayesian regression, ensemble regression and other methods. The present invention further provides digital systems and software for performing the methods provided herein.