a graph-based, large-scale data model for NLP cross-referencing

I find myself in a situation where my team needs to combine several natural language processing (NLP) [1] techniques, each conducted upon the same large set of texts, to derive critical business conclusions. Particularly, we need a way to cross-reference analyses based on common key words across sentences. Toward that end, I designed the following […]

picking stocks by graph database (part one)

Historical stock price data comes readily available at daily resolution. So we calculated the Granger causality for each pair of stocks we hold data for, at one and two day lags (testing the question “does daily percent change in volume for stock X Granger cause daily percent change in adjusted close price for stock Y?”). […]

graph database for heterogeneous biological data

To assist with a project I’m working on, I recently implemented a substantial portion of DisGeNET as a graph database. Furthermore, I added MeSH, OMIM, Entrez, and GO into the database to facilitate linking of data between these sources. Here I briefly describe these data sources, describe graph databases, and then show how use of […]

graph database for gene annotation

Lately I’ve been experimenting with graph databases using Neo4j and the Cypher query language. To get a feel for these tools, I created the following gene annotation network. The Cypher commands I used are discussed in this post, followed by a demonstration of querying the database. Creating the Graph Database We are creating the following […]