Codetown ::: a software developer's community
Are you interested in learning about graph databases? The folks at Neo4J published a book and it's free! Here's a link to the download page: http://graphdatabases.com/
Tags:
Database representation of graph-structured information is fascinating in its own right.
I have been studying genomics technology in which graphs play a big role, both as information-structure that is the basis of certain algorithms, as well as the data driving visualizations or visually-interesting real-world structures.
As an example, here is a visualization of a protein complex that catches the eye.
See http://en.wikipedia.org/wiki/FOXP2#/media/File:Protein_FOXP2_PDB_2a...
The image is a Richardson diagram which is (mostly) automatically generated from a database describing the molecular structure of the protein. This type of diagram was invented (i.e. originally hand-drawn) by Jane Richardson, PhD.
I wonder if the book "Graph Databases" touches on this.
Presently, I am doing a research study on a particular feature of the epigenome. It involves large DNA databases (actually, structured flat files), elaborate algorithms for sequence correlation, and histone complexes. Each of these involves graph-theoretic representations and inference functions from graph structures.
The "databases" I know for DNA, the transcriptome, pathways, etc. do not lend themselves to conventional SQL, or even noSQL as far as I know to date. (Chime in anyone? )
I will be presenting a paper at the IEEE SouthCon conference in April 2015 which touches on a graph-theoretic feature of certain (sequencing) problems lending itself to massively-parallel-ization of linearly-expressable algorithms.
I am pleased to see a free book on graph databases. Thanks!
Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
Check out the Codetown Jobs group.

Recently launched in technical preview, GitHub Agentic Workflows introduce a way to automate complex, repetitive repository tasks using coding agents that understand context and intent, GitHub says. This enables workflows such as automatic issue triage and labeling, documentation updates, CI troubleshooting, test improvements, and reporting.
By Sergio De Simone
The panelists emphasize that data engineering is no longer just about "click-and-drag" UI tools; it is software engineering applied to data.
By Fabiane Nardon, Matthias Niehoff, Adi Polak, Sarah Usher
Dropbox engineers have detailed how the company built the context engine behind Dropbox Dash, revealing a shift toward index-based retrieval, knowledge graph-derived context, and continuous evaluation to support enterprise AI at scale
By Matt Foster
Uber and OpenAI are replacing static rate limits with adaptive, infrastructure-level platforms. Uber’s Global Rate Limiter utilizes probabilistic shedding to manage 80M RPS, while OpenAI’s Access Engine implements a credit waterfall to prevent user interruptions. Both architectures utilize distributed enforcement and soft controls to maintain system stability and service continuity at scale.
By Patrick Farry
Moonshot AI released Kimi K2.5, their latest open-weight multimodal LLM. K2.5 excels at coding tasks, with benchmark scores comparable to frontier models such as GPT-5 and Gemini. It also features an agent swarm mode, which can direct up to 100 sub-agents for attacking problems with parallel workflow.
By Anthony Alford
© 2026 Created by Michael Levin.
Powered by