Lifelike
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- From Big Data
to Big Picture
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- - Extract concepts easily -
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- - Make new connections -
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- - Leap beyond traditional research -
-- A graph-powered knowledge mining platform -
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- Lifelike has several integrated features that support knowledge mining and - collaboration among users in the biosciences field. -
-- Users can upload their own structured and unstructured data. The data is annotated in - real-time using NLP and rule-based techniques allowing it to be contextualized and - connected to global knowledge. Graph and statistical knowledge mining algorithms can - then be run across the combined user and global datasets. In this way users can explore - their own data in the broader context of existing knowledge, discovering extended paths - comprised of new and previously known relationships. -
-- Lifelike supports communication and collaboration by allowing users to create Knowledge - Maps. These are visual graph documents that can be used informally to take "visual - notes", or in a more rigorous fashion to create highly curated models that can be - analyzed with graph algorithms. Knowledge Maps are a great and easy to use tool to - extract knowledge in a visual fashion by simply dragging entities, text snippets, files - etc. onto the map. The user can then create new connections between the entities, - provide evidence for each connection and add notes and links. The map content is very - rich since the entities retain their meta-data and hyperlinks.
-- Fully integrated with a suite of technologies -
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- - Natural Language Processing -
-- Lifelike uses Artificial Intelligence (AI) and rule-based entity recognition to - automatically recognize key biological entities such as genes, proteins, diseases, - chemicals, phenomena, anatomy, proteins, species and relationships between them. It - also enables ‘on the fly’ custom annotations so users can define additional key - entities of interest. -
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- - Knowledge Reconstruction -
-- Lifelike’s drawing canvas allows users to create connected content and express - relationships between biological entities, provide evidence for those relationships - including hyperlinks and direct connections to literature and other sources. Drag - and - drop from annotated papers and enrichment tables allows for fast knowledge - reconstruction and visual note taking. Multiple maps can be merged into a - comprehensive knowledge graph for graph analysis. -
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- - Knowledge Visualization & Enrichment -
-- Lifelike provides an interactive knowledge graph visualizer that clusters - relationships by type to simplify complex graphs. Graph nodes can be expanded and - detailed supporting data can be viewed. Structured data can be uploaded and enriched - against knowledge from many sources. Statistical analysis against ontologies as - well - as semantic analysis performed on text from public databases enables users to move - from big picture view to details. -
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- - Search (Full Text and Graph Powered) -
-- Full-text and graph-powered search enables users to find non-obvious connections, - and - related concepts or find content based on synonyms. This search is seamlessly - integrated throughout the application on a button click. -
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