Abstract: The present disclosure provides methods for constructing disease classifiers for evaluating subjects for one or more distinct biological conditions or one or more disease subtypes. The present invention involves identifying candidate small RNA (sRNA) sequences from sequence data of a discovery sample set. The presence or abundance of the candidate sRNA sequences (each taken individually) across the discovery sample set is predictive of a biological condition of interest (e.g., over other distinct biological conditions or non-disease controls), and these candidate sRNA sequences are further filtered or selected in accordance with embodiments of the present disclosure. Machine learning techniques are then applied to build and train disease classifiers, including multi-disease classifiers. The trained classifiers can be used to classify new samples, for example, to evaluate patients for disease.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying and providing image search results including general image search results responsive to an image search query and social image search results responsive to the image search query wherein each of the social image search results is associated with content generated by a respective member of a social graph of a user wherein the member is at two or more distinct degrees of separation from the user and has a minimum number of social graph friends in common with the user.