Described are techniques for determining population structure from identity-by-descent (IBD) of individuals. The techniques may be used to predict that an individual belongs to zero, one or more of a number of communities identified within an IBD network. Additional data may be used to annotate the communities with birth location, surname, and ethnicity information. In turn, these data may be used to provide to an individual a prediction of membership to zero, one or more communities, accompanied by a summary of the information annotated to those communities.

Described are techniques for determining population structure from identity-by-descent (IBD) of individuals. The techniques may be used to predict that an individual belongs to zero, one or more of a number of communities identified within an IBD network. Additional data may be used to annotate the communities with birth location, surname, and ethnicity information. In turn, these data may be used to provide to an individual a prediction of membership to zero, one or more communities, accompanied by a summary of the information annotated to those communities.

The present disclosure describes methods for determining the functional consequences of mutations. The methods include the use of machine learning to identify and quantify features of all atom molecular dynamics simulations to obtain the disruptive severity of genetic variants on molecular function.

The present disclosure describes methods for determining the functional consequences of mutations. The methods include the use of machine learning to identify and quantify features of all atom molecular dynamics simulations to obtain the disruptive severity of genetic variants on molecular function.

Embodiments for authenticating a source of website content utilizing computer-generated or anonymized digital deoxyribonucleic acid (DNA) sequences include: receiving a request for a security sequence from a user device during a browser session; sending a first-generation digital DNA sequence (F1) to the device, wherein the F1 is generated from first and second DNA sequences (P1) and (P2) associated with a website; receiving a request for a second security sequence; generating a second-generation DNA sequence (F2) based on the F1 and the P1, wherein the F2 includes at least one genetic marker of the F1 and/or the P1; sending the F2 to the user device; receiving a request for security confirmation from the device; determining whether the F2 is a child DNA sequence of the F1 and/or the P1 utilizing Marker Assisted Selection techniques; and sending a response to the device indicating whether website content originates from the website.

Embodiments for authenticating a source of website content utilizing computer-generated or anonymized digital deoxyribonucleic acid (DNA) sequences include: receiving a request for a security sequence from a user device during a browser session; sending a first-generation digital DNA sequence (F1) to the device, wherein the F1 is generated from first and second DNA sequences (P1) and (P2) associated with a website; receiving a request for a second security sequence; generating a second-generation DNA sequence (F2) based on the F1 and the P1, wherein the F2 includes at least one genetic marker of the F1 and/or the P1; sending the F2 to the user device; receiving a request for security confirmation from the device; determining whether the F2 is a child DNA sequence of the F1 and/or the P1 utilizing Marker Assisted Selection techniques; and sending a response to the device indicating whether website content originates from the website.

The present invention generally relates to methods of generating antibodies against a species of pathogen that involve identifying the pathogen that is most genetically representative of member of pathogen species and using the identified pathogen to generate an antibody.

The present invention generally relates to methods of generating antibodies against a species of pathogen that involve identifying the pathogen that is most genetically representative of member of pathogen species and using the identified pathogen to generate an antibody.

A computer-implemented method for using companion pet DNA information to train a machine-learning model to predict a familial relationship of a companion pet, the method comprising receiving companion pet DNA information, the companion pet DNA information including at least one DNA sequence, at least one matching companion pet, and at least one familial label corresponding to the familial relationship between the companion pet and the at least one matching companion pet, and upon the receiving, training the machine-learning model to predict at least one familial relationship from the at least one DNA sequence.

Cell free nucleic acids from a test sample obtained from an individual are analyzed to identify possible fusion events. Cell free nucleic acids are sequenced and processed to generate fragments. Fragments are decomposed into kmers and the kmers are either analyzed de novo or compared to targeted nucleic acid sequences that are known to be associated with fusion gene pairs of interest. Thus, kmers that may have originated from a fusion event can be identified. These kmers are consolidated to generate gene ranges from various genes that match sequences in the fragment. A candidate fusion event can be called given the spanning of one or more gene ranges across the fragment.