Abstract: A method implements evidence network navigation. The method includes receiving a user input corresponding to an entity of an ontology library; and generating an evidence graph using the user input, wherein the evidence graph includes an evidence node representing the entity from the ontology library and includes an evidence edge representing a file that includes the entity in a result graph, and wherein the result graph includes a result node representing the entity and a result edge representing a semantic relationship of the result node in a sentence from the file. The method further includes presenting the evidence graph.

Abstract: A method implements an experiment architect. The method includes receiving an entity identifier; searching a plurality of result graphs using the entity identifier to identify a file comprising content corresponding to the entity identifier; and presenting a figure from the file in response to identifying the file.

Abstract: A method implements an evidence result network. The method includes receiving a file; tokenizing a sentence from the file to generate a set of tokens; processing the set of tokens to generate a tree for the sentence. The method further includes processing the tree to generate a graph for the sentence; processing the graph to identify correspondences between nodes of the graphs and types of entities of an ontology library; and presenting the graph.

Abstract: A method implements reagent selection. The method includes receiving a search request comprising an entity type and an entity name; searching biomedical data to identify a set of biomedical sources that correspond to the entity name using an ontology library; and presenting an image from a biomedical source, of the set of biomedical sources, wherein the image corresponds to the entity name.

Abstract: A method exposes risk types of biomedical information. The method includes processing a plurality of result graphs to generate an evidence graph, in response to a query; presenting the evidence graph with a node corresponding to a result graph of the plurality of result graphs, wherein the result graph corresponds to a file; and presenting the node with a risk icon indicating a subset of files is identified with one or more risk types.

Abstract: A method may include acquiring one or more image texts from an image of a document, segmenting the image into one or more sub-images using the one or more image texts, determining, by applying a machine learning model, one or more experimental techniques of one or more experiments for the one or more sub-images, and adding, to a knowledge base, one or more mappings of the one or more sub-images to the one or more experiments.

Abstract: A method may include acquiring one or more image texts from an image of a document, segmenting the image into one or more sub-images using the one or more image texts, determining, by applying a machine learning model, one or more experimental techniques of one or more experiments for the one or more sub-images, and adding, to a knowledge base, one or more mappings of the one or more sub-images to the one or more experiments.