Posts Tagged Source
While tinkering with my arduino-board (a project loosely related to processing) I came across this video on Make: explaining the basics of electronic schematics.
It reminded me of this wonderful and thought-provoking article by Y.Lazebnik “Can a biologist fix a radio?–Or, what I learned while studying apoptosis.” (see here for the .pdf).
Another example of how complexity arises from combining relatively simple building blocks, and how we go about understanding and reverse-engineering complex systems in different disciplines.
(found via SchockWellenReiter)
I just came across Marcus Wohlsen‘s book “Biopunk – Kitchen-Counter Scientists Hack the Software of Life“. It’s already been out there for a couple of months, and was discussed at some depth on boingboing by Mark Frauenfelder.
Just added it here for general interest – something to go on my wishlist – and as a soothing reminder that one is not the only crazy geek who sees the convergence of life- and information science 😉
Just ask Bill Gates. If he were a teenager today, he says, he’d be hacking biology. “Creating artificial life with DNA synthesis. That’s sort of the equivalent of machine-language programming,” says Gates, whose work for the Bill & Melinda Gates Foundation has led him to develop his own expertise in disease and immunology. “If you want to change the world in some big way, that’s where you should start — biological molecules.”
(found on wired “Geek Power: Steven Levy Revisits Tech Titans, Hackers, Idealists” By Steven Levy)
“Visual.ly” claims to be “The world’s largest community for exploring, sharing, creating, and promoting data visualizations.”
Currently, there are over 3000 visualisations available on their site. Among my current favourites is this Infographics on Communication Through The Ages by Atlassian and this topological map of the internet, also available for download as desktop-wallpaper or poster here (at peer1hosting).
Well, data visualisation requires first of all that we get the appropriate data put together. With this all-important and often painful task pandas offers some help, pandas is “… becoming the most powerful and flexible open source data analysis / manipulation tool available in any language.” – they say. Sounds good, it’s based on numPy (scientific computing package for Python), will have to try it out at some point.
(thanks to Henning Stehr for hints on visual.ly, pandas found via SchockWellenReiter)
Note to myself: upgrade my Python&skills (3.0), then check it out in-depth!
All python-enthusiasts and admirers of the big snake rejoice! The open-source software developers group TinkerPop has been writing a great stack of software for/on top of new graph databases. The group was co-founded by Marko Rodriguez and focusses on technologies in the graph database space. Among these, there is “Bulbs” (bulbflow.com) –
… an open-source Python persistence framework for graph databases and the first piece of a larger Web-development toolkit that will be released in the upcoming weeks. It’s like an ORM (Object Relational Mapping) for graphs, but instead of SQL, you use the graph-traversal language Gremlin to query the database. You can use it to connect to any Blueprints-enabled database, including TinkerGraph, Neo4j, OrientDB, Dex, and OpenRDF (and there is an InfiniteGraph implementation in development). Blueprints is a collection of interfaces, implementations, ouplementations, and test suites for the property graph data model. Blueprints is analogous to the JDBC, but for graph databases.
So far when dealing with hu-Hu-HUGE networks, the data cannot be processed in the memory of a single machine. Usually, we store the network in database tables (or similar, but worse: excel spreadsheets) describing the nodes and edges. Then you have to implement the graph-algorithm of your choice in this framework, which usually is leads to sub-optimal performance (putting it mildly). Straightforward optimizations would be for example in adressing a single node, the database could already load the adjacent edges into memory (cache) so the immediate next steps do not require additional access to the the disk-drive. Also, you might want to distribute parts of the network across several machines. Of course a carefully handcrafted and optimized object-relational mapping with tuned indices can do little wonders when you get it right, but the nagging thought remains that this can – and has to! – be dealt with in a better way. By now not only bioinformaticians and google-employees feel the occasional need to crunch BIG GRAPHS. Read the rest of this entry »
After writing a couple of sketches in processing, the urge to share it tends to become bigger. Of course processing lets you export a sketch as an application for any architecture$(windows, linux, OS/X). That has the advantage of eventually using more of the power of the local hardware, but not everybody wants to download the full program just to have a sneak-peek preview how it looks like in action. Processing also let’s you generate an applet that can be included in web-pages. In case you are not maintaining your own web-server, OpenProcessing comes in very handy in a couple of aspects.
Read the rest of this entry »