Abstract: Systems and techniques are disclosed for predicting the structural status of an object. An object model, such as a machine learning model, can be trained on sample sensor data indicating vibrations, movements, and/or other reactions of objects with known desired and undesired structural statuses to a stimulus agent, such as a puff of air. A scanning device can output a corresponding stimulus agent towards an object, capture sensor data indicating the reaction of the object to the stimulus agent, and provide the sensor data to the trained object model. Based on the sensor data indicating how the object reacted to the stimulus agent, the object model can predict whether the object has a desired structural status or an undesired structural status.

Abstract: Two or more aerial vehicles, such as drones, can each include one or more cameras for capturing surveying or other image data within a field of view. Some of the image data, as well as other data, can be stored and pre-processed on the vehicles, including via onboard edge computing devices. The image and/or other data can be analyzed by a remote system or service, which has additional computing resources, and used to determine the occurrence or existence of an anomaly, such as a seismic event or structure identified in the field of view. The anomaly determination may be based on a disparity, involving a distance between cameras, the cameras' focal length, and a perpendicular distance from a point between cameras to a surface or subsurface point.

Abstract: A system and method are disclosed for the collection and aggregation of genomic, medical, and other data of interest for individuals and populations that may be of interest for analysis, research, pharmaceutical development, medical treatment, and so forth. Contributors become members of a community upon creation of an account and providing of data or files. The data is received and processed, such as to analyze, structure, perform quality control, and curate the data. Value or shares in one or more community databases are computed and attributed to each contributing member. The data is controlled to avoid identification or personalization. Third parties interested in the database information may contribute value (e.g., pay) for access and use. Value flows back to the members and to a system administrative entity.

Abstract: A system and method are disclosed for the collection and aggregation of genomic, medical, and other data of interest for individuals and populations that may be of interest for analysis, research, pharmaceutical development, medical treatment, and so forth. Contributors become members of a community upon creation of an account and providing of data or files. The data is received and processed, such as to analyze, structure, perform quality control, and curate the data. Value or shares in one or more community databases are computed and attributed to each contributing member. The data is controlled to avoid identification or personalization. Third parties interested in the database information may contribute value (e.g., pay) for access and use. Value flows back to the members and to a system administrative entity.

Abstract: A system and method are disclosed for the collection and aggregation of genomic, medical, and other data of interest for individuals and populations that may be of interest for analysis, research, pharmaceutical development, medical treatment, and so forth. Contributors become members of a community upon creation of an account and providing of data or files. The data is received and processed, such as to analyze, structure, perform quality control, and curate the data. Value or shares in one or more community databases are computed and attributed to each contributing member. The data is controlled to avoid identification or personalization. Third parties interested in the database information may contribute value (e.g., pay) for access and use. Value flows back to the members and to a system administrative entity.

Abstract: A system and method are disclosed for the collection and aggregation of genomic, medical, and other data of interest for individuals and populations that may be of interest for analysis, research, pharmaceutical development, medical treatment, and so forth. Contributors become members of a community upon creation of an account and providing of data or files. The data is received and processed, such as to analyze, structure, perform quality control, and curate the data. Value or shares in one or more community databases are computed and attributed to each contributing member. The data is controlled to avoid identification or personalization. Third parties interested in the database information may contribute value (e.g., pay) for access and use. Value flows back to the members and to a system administrative entity.

Abstract: A system and method are disclosed for the collection and aggregation of genomic, medical, and other data of interest for individuals and populations that may be of interest for analysis, research, pharmaceutical development, medical treatment, and so forth. Contributors become members of a community upon creation of an account and providing of data or files. The data is received and processed, such as to analyze, structure, perform quality control, and curate the data. Value or shares in one or more community databases are computed and attributed to each contributing member. The data is controlled to avoid identification or personalization. Third parties interested in the database information may contribute value (e.g., pay) for access and use. Value flows back to the members and to a system administrative entity.

Abstract: A system and method are disclosed for the collection and aggregation of genomic, medical, and other data of interest for individuals and populations that may be of interest for analysis, research, pharmaceutical development, medical treatment, and so forth. Contributors become members of a community upon creation of an account and providing of data or files. The data is received and processed, such as to analyze, structure, perform quality control, and curate the data. Value or shares in one or more community databases are computed and attributed to each contributing member. The data is controlled to avoid identification or personalization. Third parties interested in the database information may contribute value (e.g., pay) for access and use. Value flows back to the members and to a system administrative entity.

Abstract: A system and method are disclosed for the collection and aggregation of genomic, medical, and other data of interest for individuals and populations that may be of interest for analysis, research, pharmaceutical development, medical treatment, and so forth. Contributors become members of a community upon creation of an account and providing of data or files. The data is received and processed, such as to analyze, structure, perform quality control, and curate the data. Value or shares in one or more community databases are computed and attributed to each contributing member. The data is controlled to avoid identification or personalization. Third parties interested in the database information may contribute value (e.g., pay) for access and use. Value flows back to the members and to a system administrative entity.

Abstract: Systems and methods for storing protein structure information are provided. The system comprises a non-public database storing protein structure information, wherein the non-public database is coupled to a public database of non-proprietary protein structure information and to non-public sources of proprietary protein structure information. The non-public database may also be coupled to a database having protein structure information for substantially all the proteins of at least one organism genome. The method may comprise loading protein structure data from at least one public database and loading protein structure data from one or more proprietary sources of protein structure information. The public database may comprise the Protein Data Bank (PDB). Certain types of additional information are also advantageously loaded into the database. These may include classification data corresponding to at least one protein ontology.

Abstract: A system and methods for rapidly and accurately assessing ligand binding characteristics for diverse classes of protein molecules. Modeling methods are used to represent the protein molecules and simulate their interaction with ligand molecules. Protein/ligand interactions are characterized by a fingerprint analysis that permits grouping of the proteins based on predicted structural features and ligand reactivity rather than sequence similarities or homology alone.