Archive for category Networks
Google started to roll out the Knowledge Graph, intended to be more about things rather than just strings. Delivering and disambiguating related content based on semantic network associations sounds great, if this really is a step forward to move out of the filter-bubble remains to be seen. Overall, it seems to be related to the idea of a conceptual graph, and wikipedia forms a big chunk of the underlying knowledge-base.
techcrunch.com “Google Just Got A Whole Lot Smarter, Launches Its Knowledge Graph”
Googles official blog “Introducing the Knowledge Graph: things, not strings”
lifehacker.com “Google Knowledge Graph Brings Smarter Semantic Results to Your Google Searches”
webpronews.com “Knowledge Graph: Google Gets Tight With Wikipedia“
This one is so crisp and up-to-date it’s not even available yet in the non-virtual world: Santigold‘s new album “Master of My Make-Believe” will be out 23rd April (UK) / May 1st (US).
Seems the beancounters can’t find a proper box for this one in their desperate attempts to classify it, whether it’s retro dub, Neo Wave, hip-hop, drum’n’base or alternative – whatever, I don’t care as long as it sounds great and soothes my ears. Nice baseline – Yep, pump up the volume and enjoy!
Just in time I found this review “Network Science Reveals The Cities That Lead The World’s Music Listening Habits” on technologyreview.com via Social Foraging (“Dynamics of Social Interaction”, curated by Ashish Umre).
The evidence that ideas and fashions spread through society like viruses or like wildfire is compelling. Numerous studies have examined the networks in which this spread takes place and with increasingly large data sets to work with, researchers have become increasingly confident in their network-centric view of the world. These tools are teasing apart the large scale behaviour of humanity in ever increasing resolution.
The original article “The Geographic Flow of Music” by Conrad Lee and Pádraig Cunningham is available on arXiv:1204.2677v1.
Pearl‘s book on “Causality” has been on my shelf for a while now. I also read it, a few times, but never managed to get through it in one go, cover to cover. Consequently, I haven’t come to grips with all details, implications and equations yet. No reason to worry about my intellectual capabilities, it’s quite fundamental and takes time to sink in. Now Judea Pearl has been awarded the 2011 ACM Turing Award – Congratulations!
The annual Association for Computing Machinery (ACM) A.M. Turing Award, sometimes called the “Nobel Prize in Computing,” recognizes Pearl for his advances in probabilistic and causal reasoning. His work has enabled creation of thinking machines that can cope with uncertainty, making decisions even when answers aren’t black or white. […]
The UCLA computer science professor is widely credited with coining the term “Bayesian Network,” which refers to a statistical model ACM describes as mimicking “the neural activities of the human brain, constantly exchanging messages without benefit of a supervisor.” Bayesian networks have been used to, among other things, analyze biological data for studies of medicine and diseases.
Here is a chance to see him talk for yourself:
“I compute, therefore I understand” – More videos are here on theScienceNetwork.
found via networkworld.com: Judea Pearl, a big brain behind artificial intelligence, wins Turing Award. See also on the ACM NEWS “Judea Pearl Wins 2011 ACM Turing Award“.
The International Molecular Exchange Consortium IMEx is the latest effort of data-providers to integrate Protein-Interaction Data –
- A non-redundant set of protein-protein interaction data from a broad taxonomic range of organisms
- the data in standards compliant download formats (MITAB or PSI-MI XML 2.5)
- Expertly curated from direct submissions or peer-reviewed journals to a consistent high standard.[ … aiming to … ]
- Develop and work to a single set of curation rules when capturing data from both directly deposited interaction data or from publications in peer-reviewed journals
- Make these interaction available in a single search interface on a common website
- Make all IMEx records freely accessible under the Creative Commons Attribution License
If you’ve been looking for that one-stop shop for getting a representative dataset of Protein-Protein Interactions, this just looks like it. There is an overview available on youtube (see below)
… and a training course on “Networks and Pathways Bioinformatics for Biologists” will take place at EMBL-EBI in May.
You probably have seen the hairballs resulting from a force-directed layout of complex biological networks. What do they tell you? Well, that the networks are rather complex. But for much more detailed analysis the classical visualizations are actually quite useless. The hiveplot is an attempt to provide
A laudable goal, if it works in practice for you and your data – check it out. In addition there is an R package available for creating hive plots in 2D and 3D called HiveR.
Also see Krzywinski M, Birol I, Jones S, Marra M (2011). Hive Plots — Rational Approach to Visualizing Networks. Briefings in Bioinformatics (doi: 10.1093/bib/bbr069).
Thanks to Lucy Colwell for the hint!