Julian's Polymath Explorations

  This is a very gentle introduction to the subject.  The subtitle is inspired by university courses such as "Physics for Poets"!  (if you're technically inclined, there's an alternate article for you.) It has been said that "The language of physics (or of God) is math".  On a similar note, it could be said that: The language of the biological world - or of any subject or endeavor involving complexity - is networks ('meshes') What is a network?  Think of  it as the familiar 'friends of friends' diagram from social media. Everywhere one turns in biology, there's a network – at the cellular level, tissue level, organ level, ecosystem level.  The weather and other earth systems are networks.  Human societal organization is a network.  Electrical circuits, the Internet, our own brains...  Networks are everywhere! What can we do with networks, to better understand the world around us, or to create something that we need? Broadly ...

(UPDATED May 2024)   Now that we have discussed a full technology stack based on Neo4j (or other graph databases), and that we a design and implementation available from the open-source project BrainAnnex.org  , what next?  What shall we build on top? Well, how about  Full-Text Search ?  This article is part of a growing, ongoing series on Graph Databases and Neo4j Full-Text Searching/Indexing The Brain Annex open-source project includes an implementation of a design that uses the convenient services of its Schema Layer , to provide indexing of word-based documents using Neo4j. The python class FullTextIndexing ( source code ) provides the necessary methods, and it can parse both plain-text and HTML documents (for example, used in "formatted notes"); parsing of PDF files and other formats will be added at a later date. No grammatical analysis ( stemming or lemmatizing ) is done on the text.  However, a long list of common word ("stop ...

Putting it All Together : a Technology Stack on top of a (Neo4j) Graph Database (UPDATED June 2024)  For many practical use cases, one needs a full data-management solution, not just a database.   So, armed with the Schema Layer discussed in the previous part , the next natural step is to add a web API and possibly a User Interface . This article is part of a growing,  ongoing  series  on Graph Databases and Neo4j   The Web API Layer / Data Manager The Web API Layer ("Data Manager")  is in some ways the most straightforward layer - because the "heavy lifting" is done by the Schema Layer.   I've been involved in projects that utilized an inadequate Schema Layer - and in those situations the API Layer ends up taking on an immense amount of responsibility that don't logically belong there; the end result being a lot of difficult, error-prone and non-modular development that feels like "pulling teeth"! By contrast, with a...

So, you want to build a python app or Jupyter notebook to utilize Neo4j, but aren't too keen on coding a lot of string manipulation to programmatic create ad-hoc Cypher queries?   You're in the right place: the NeoAccess library can do take care of all that, sparing you from lengthy, error-prone development that requires substantial graph-database and software-development expertise! This article is part 4 of a growing,  ongoing  series  on Graph Databases and Neo4j   "NeoAccess" is the bottom layer of the technology stack provided by the BrainAnnex open-source project .  All layers are very modular, and the NeoAccess library may also be used by itself , entirely separately from the rest of the technology stack.  (A diagram of the full stack is shown later in this article.) NeoAccess interacts with the Neo4j Python driver , which is provided by the Neo4j company, to access the database from Python; the API to access that driver is very p...

So, you have an itch to test-drive Neo4j and its Cypher query language.  Maybe you want to learn it, or evaluate it, or introduce colleagues/clients to it.  And you wish for: fast, simple and free! Well, good news: the Neo4j company kindly provides a free, short-term hosted solution called "the Neo4j sandbox" .  Extremely easy to set up and use! This article is part 2 of a growing, ongoing series on Graph Databases and Neo4j Register (free) for the Neo4j "Sandbox" Go to sandbox.neo4j.com , and register with a working email and a password.  That's it! Note that this same email/password will also let you into the Neo4j Community Forums and Support ; the same login for all: very convenient! Launch your instance - blank or pre-populated After registering, go to  sandbox.neo4j.com  , and follow the steps in the diagram below (the choices might differ, but the "Blank Sandbox" should always be there): Too good to be true?  Is there...

You have a general idea of what Graph Databases - and Neo4j in particular - are...  But how to get started?  Read on! This article is part 3 of a growing,  ongoing  series  on Graph Databases and Neo4j   If you're new to graph databases, please check out part 1 for an intro and motivation about them.  There, we discussed an example about an extremely simple database involving actors, movies and directors...  and saw how easy the Cypher query language makes it to answer questions such as "which directors have worked with Tom Hanks in 2016" - questions that, when done with relational databases and SQL, turn into a monster of a query and an overly-complicated data model involving a whopping 5 tables! In this tutorial, we will actually carry out that query - and get acquainted with Cypher and the Neo4j browser interface in the process.  This is the dataset we'll be constructing: Get the database in place If you don't already have a datab...

UPDATED Apr. 2023 - I'm excited by ChatGPT 's possibilities in terms of facilitating advanced learning .  For example, I got enlightening answers to questions that I had confronted when I first studied neuroscience.  The examples below are taken from a very recent session I had with ChatGPT (mid Jan. 2023.) Source: https://neurosciencestuff.tumblr.com In case you're not familiar with ChatGPT, it's a very sophisticated "chatbot" - though, if you call it that way, it'll correct you!  'I am not a "chatbot", I am a language model, a sophisticated type of AI algorithm trained on vast amounts of text data to generate human-like text'. For a high-level explanation of how ChatGPT actually works - which also gives immense insight into its weaknesses, there's an excellent late Jan. 2023 talk by Stephen Wolfram, the brilliant author of the Mathematica software and of Wolfram Alpha , a product that could be combined with ChatGPT to imp...