a molecule ranking algorithm for mining biological semantic networks
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a molecule ranking algorithm for mining biological semantic networks
CrRank: A Multilayered Network Algorithm for Ranking. Social Media users. ⢠Outperform Google's PageRank. ⢠Outperform Common Centrality Measures.
MOLECRANK: A MOLECULE RANKING ALGORITHM FOR MINING BIOLOGICAL SEMANTIC NETWORKS AHMED ABDEEN HAMED, PH.D. K N OW L E D G E E N G I N E E R @ DATA P L AT FO R M S C I E N T I F I C I N FO R M AT I O N M A N AG E M E N T MERCK & CO. AG ATA L E S Z C Z Y Ń S K A , P H . D . P RO D U C T OW N E R / B U S I N E S S A N A LYST S C I E N T I F I C I N FO R M AT I O N M A N AG E M E N T MSD
MAIN RESEARCH QUESTION Problem: • Precious biological knowledge is cap3vated in literature • Answering biological ques3ons is not possible without further processing • Can we design algorithms that provide highly relevant content and provide it fast? § Ex: Given a molecule search query against a literature dataset: can we find the most specific instances?
Sec. 6.2.1
MOLECULE NOTION OF SPECIFICITY 1. The more aFached a molecule to a given biological feature, the more specific and most most useful 2. The more knowledge we gather about the molecule, the more we know where it can be ranked 3. The opposite is also valid
METHODS AND APPROACH • Given a literature dataset we need the following • A feature selec3on process to extract biological en33es • Using Machine Learning • Ontology
• An expressive Linked Data model • Graph database • Query Mechanism • Ranking as a Post-processing step
Sec. 6.2
OVERALL ARCHITECTURE Ranking and Outputting Results
Ranked Molecules
Merck Literature PubMed
MolecRank Algorithm
Text Mining Process
Pre-processing Step
Post-processing Step
Network Construction Process
JSON-LD Transformation + Ingestion
RDF4J WorkBench Query Portal
RDF4J TripleStore
Sec. 6.2
SEARCHING PUBMED FOR A DATASET
Sec. 6.2
COLLECTING THE ABSTRACTS AS MEDLINE
Sec. 6.2
BIOLOGICAL FEATURES EXTRACTED
EXPRESSIVE JSON LINKED DATA
Sec. 6.2
VISUAL REPRESENTATION OF THE GRAPH
INGESTING JSON-LD INTO A TRIPLE STORE
FINDING FEATURES FOR PMID:27690219
DISPLAYING/EXPORTING RESULT
QUERYING MORE THAN ONE PUBMED DOC
QUERY RESULT CAPTURING CONTEXT
POST-PROCESSING SPARQL RESULTS • Expor3ng the query results into a CSV • Construc3ng a network such as follows
EMERGENT NETWORK
MOLECRANK: MOLECULE RANKING ALGORITHM
CURRENT WORK • Algorithm is implementa3on phase • Rigorous experiments • Fine tuning the JSON-LD data model
PRIOR SUCCESSFUL WORK • CrRank: A Multilayered Network Algorithm for Ranking Social Media users • Outperform Google’s PageRank • Outperform Common Centrality Measures • Guarantees a unique ranking mechanism to each node in the network
ACKNOWLEDGEMENT • Adam Sotona: For the Halyard triple store • [“https://merck.github.io/Halyard/tools.html”] • Mark Schreiber: Director of SIM Data Platform
