Here is the latest bag of tweets^*, which covers January 2013.

(*) These are interesting news that I found on Twitter and that I archive periodically.

• kshameer: Interpreting scientific literature: A primer. http://t.co/7nCK8MWT (19 Jan)
• daringfireball: Enable Quick Look for Markdown Files: http://t.co/xWLqroND (19 Jan)
• costofknowledge: Mathematicians aim to take publishers out of publishing http://t.co/wDrs0AUz (19 Jan)
• peteskomoroch: Computational Social Science course at Columbia w/ @jakehofman http://t.co/GzoOg3uX via @prismatic (19 Jan)
• mja: Personality disorders as alternative behavioral strategies rather than diseases: http://t.co/bUr1QBO2 (19 Jan)
• moclanmomo: #1!!! ;) RT @jstatsoft: JSS growth over the last 4 years http://t.co/wWZSvkFp #statistics #openaccess #MetricsBogusUnlessURHigh (19 Jan)
• Prismatic: Blog Post: “Bringing functional to the front-end: Clojure + ClojureScript for the web” http://t.co/h8WXwOKX (18 Jan)
• siah: “Models and Algorithms for Crowdsourcing Discovery” [PhD dissertation] http://t.co/Ml1onPyx #pdftribute (15 Jan)
• savinger: I did the @nodejs logo in CSS. http://t.co/vySzVz73 (15 Jan)
• eddelbuettel: A first and simple Boost example with Rcpp at the Rcpp Gallery: http://t.co/y9De8Gt1 #rcpp #rstats (15 Jan)
• pushthings4ward: Would be nice to filter the datasets by domain RT @smfrogers: All our datasets: the complete index http://t.co/9huDlSrx | #ddj (15 Jan)
• kdnuggets: How to find useful external data (key question for most data mining tasks) http://t.co/hMtvzAy2 (15 Jan)
• blattnerma: What Python installations are scientists using? - .py in the sky http://t.co/FXEhsDyB via @astrofrog (15 Jan)
• revodavid: The four D’s of programming’s future, according to @edd: Data, Distributed, Device, Democratized: http://t.co/q5cuRVsP #rstats (12 Jan)
• neilfws: “The electronic pre-print with open discussion will soon become commonplace”; Sydney Brenner on #altmetrics in 1996 - http://t.co/O7Rk4pSI (11 Jan)
• MongoDB: Slides from “Building Your First Application with MongoDB” Webinar http://t.co/AwTA04el (10 Jan)
• Atabey_Kaygun: New post: finding all paths between a given pair of vertices in a directed graph http://t.co/NHYhs41e (10 Jan)
• siah: How to implement an algorithm from a scientific paper http://t.co/V9UgKeVB (10 Jan)
• hadleywickham: Understanding how #rstats functions work: https://t.co/0feobBZP. Feedback appreciated! (9 Jan)
• pathogenomenick: Messing around with Flux http://t.co/QEY2632e (9 Jan)
• onertipaday: “@MarekHlavac: @onertipaday ‘stargazer’ for beautiful #LaTeX tables in #rstats: https://t.co/1wh62Xdr " (8 Jan)
• carlislerainey: “Data have their value only when confronted with a useful theory.” http://t.co/ivEP2IKW (8 Jan)
• carlislerainey: I just realized that @JustinEsarey has a methodology blog. Check it out and RT to others. http://t.co/B3bSqEQi (6 Jan)
• moorejh: #Datascience #datamining RT @analyticbridge The curse of #bigdata: http://t.co/iJeeMWlZ (6 Jan)
• jedisct1: Yet another tool to monitor the progress of data through a pipe: https://t.co/uP8W1N9u (6 Jan)
• akuhn: Smalltalk for the JVM, anyone? http://t.co/4MGh3HMK (6 Jan)
• carlislerainey: Many academics that “don’t have time to blog” have plenty to write detailed, well-structured e-mail replies and flames. http://t.co/HaloBe8u (6 Jan)
• johnmyleswhite: The best description of higher-order functions, functors and monads I’ve ever read: http://t.co/26HmDvwP (6 Jan)
• greglinden: Don’t miss Peter Norvig’s latest blog post, especially the setup at the beginning and the data at the very end. http://t.co/ADelkHxA (6 Jan)
• cartoDB: New blog post on how CartoDB makes #D3 maps a breeze. Check it out http://t.co/EW9WbMOH #js #mapping (5 Jan)
• Atabey_Kaygun: A Simple Monte Carlo Integration Implementation in Lisp http://t.co/NHYhs41e (5 Jan)
• FGRibreau: HTML KickStart - lean html building blocks for rapid website production #webdev // Bootstrap-like http://t.co/gX9rN31z (5 Jan)
• albertocairo: Wow MT @visualisingdata Collection of data viz/infographics books: http://t.co/ulfuMWuE … & http://t.co/4mT9OHqV … & http://t.co/yquAX78f … (5 Jan)
• tdhopper: Useful boilerplate code regarding dictionaries in Python http://t.co/v2kUpPdh (5 Jan)
• viatropos: Unbelievable. This is the ultimate database. https://t.co/ryvsw7kC brew|npm install orientdb (5 Jan)
• druvus: Will Scientists Ever Move to #Python 3? http://t.co/r4VP4HGf #bioinformatics (5 Jan)
• StatsInTheWild: 2012: The Year in Graphics http://t.co/rtKWMvj0 (5 Jan)
• yokofakun: Semantic technologies in healthcare and life sciences (J. Biomedical Sematics collection ) : http://t.co/Wta1Bb0d (5 Jan)
• planetclojure: Part 4 of Exploring Google Analytics data using Clojure, Incanter and MongoDB http://t.co/FCaMEQqg (5 Jan)
• planetclojure: Tweeking Emacs modeline for Clojure Development http://t.co/TExU9XR6 (5 Jan)
• GuidoStevens: Mining Wikipedia with Hadoop and Pig for Natural Language Processing http://t.co/mCikCRia #semanticweb #stanbol #i18n (5 Jan)
• mdallastella: “The #Clojure Style Guide” http://t.co/wYDpfKg8 (5 Jan)
• pathogenomenick: What your choice of statistical software says about you … http://t.co/XPdEsPx4 (5 Jan)
• planetclojure: List Comprehensions in Eight Lines of Clojure http://t.co/PNpCj6cI (4 Jan)
• jakevdp: From the @scikit_learn mailing list: a free PDF draft of an excellent data analysis text: http://t.co/pwUrUzQO (4 Jan)
• SciPyTip: A month of mathematical software http://t.co/Ej8A5Yt3 (4 Jan)
• codingai: ipy_table - Easily create richly formatted data tables in IPython Notebooks http://t.co/qKSYJ0iv (4 Jan)
• i_314: Bayesian statistical methods for genetic association studies. PDF paper: http://t.co/9MuLzgFS #genetics #bioinformatics #stats (4 Jan)
• moebio: random numbers with seed, a simple and ‘respectable’ algorithm http://t.co/OGoMFQB0 (4 Jan)
• promptsh: Lisp Lore: A Guide to Programming the Lisp Machine, a Lisp Machine manual from 1986. http://t.co/Sq51uD2i (4 Jan)
• ThomasCabrol: The Near Future of Data Analysis by @hadleywickham http://t.co/a5U4I2OC via @dataiku (4 Jan)
• HarlanH: Statistical Inference, Michael Oakes; and “Likelihood inference” by @civilstat http://t.co/ij8p9aNU #statistics (4 Jan)
• gappy3000: Factor analysis. As usual in Shalizi’s posts, something new, something old, something confused and something bold. http://t.co/SutostKP (4 Jan)
• pentalibra: RT @mercifr1: How @hadleywickham paves the (his) way of data analysis’ future with #rstats + #d3js – http://t.co/SKvFqNmZ (4 Jan)
• luke_edington: Algorithms, data help ID clinical trial candidates - FierceHealthIT: http://t.co/N8vGbmwj (4 Jan)
• grossbart: Need to visualize hierarchical data? Here’s an overview of tree visualizations: http://t.co/m8IIS7wx (4 Jan)
• Rbloggers: Let’s Rapplicate!: (This article was first published on rapporter, and kindly contributed to R-blogge… http://t.co/dvj5bztu #rstats (3 Jan)
• Piboonrungroj: A Brief History of S Language http://t.co/GmEGvR9q #rstats (3 Jan)
• paulblaser: A survey of Bayesian predictive methods for model assessment, selection and comparison - http://t.co/zvcRt4Ga (3 Jan)
• centerofmath: The Manual of Mathematical Magic (Free download) – http://t.co/MiNPRIwJ (2 Jan)
• promptsh: Z: A Small (and awesome, ed.) Language Inspired By Markdown http://t.co/Xw5xxHjV (2 Jan)
• albertocairo: Intriguing: The Programming Historian, Python and HTML-based free textbook for the Digital Humanities http://t.co/vJTYdXX3 via @Adam_Crymble (1 Jan)
• mikedewar: #d3py has made it into ipython courtesy of @DGleebits! http://t.co/GujnAMvs (1 Jan)