Here is the latest bag of tweets^*, which covers March 2011.

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

• Calculating similarity of two users on Twitter http://bit.ly/dY6nai (h/t metaoptimizeqa, 27 Mar)
• 6 Free E-Books on Learning to Program with Python http://j.mp/g6GiQE #python (h/t tdhopper, 27 Mar)
• Network medicine: a network-based approach to human disease. http://ff.im/zMFDD (h/t kshameer, 27 Mar)
• Great article about graph processing concepts and Google Pregel: http://horicky.blogspot.com/2010/07/google-pregel-graph-processing.html (h/t sbtourist, 27 Mar)
• New post: Easily embedding R inside a Qt application with a full example of the ‘density slider’. http://goo.gl/zWjeR (h/t eddelbuettel, 25 Mar)
• #Biostar codebase on github: https://github.com/ialbert/biostar-central #python (h/t yokofakun, 25 Mar)
• #stata ’s #ice add-on is really powerful: Multiple imputation using chained equations: Issues & guidance for practice DOI: 10.1002/sim.4067 (h/t berndweiss, 24 Mar)
• The Many Uses of Q-Q Plots: My last four posts have dealt with boxplots and some… http://goo.gl/fb/wn7UE #rstats (h/t Rbloggers, 24 Mar)
• Free E-Book on “Text Algorithms” (by M. Crochemore/W. Rytter. OUP, 1994) http://bit.ly/gDcHJ1 (h/t mxlearn, 24 Mar)
• Creating my perfect citation system using LaTeX http://bit.ly/giHkuw #greader (h/t neilfws, 24 Mar)
• The data science tool kit: OCR, geocoding, text processing, etc. all on a open source VM! http://www.datasciencetoolkit.org/ #rstats #hadoop (h/t cmastication, 23 Mar)
• blogged about Gene–Environment Interactions in Human Disease http://is.gd/RkLrne #GXE (h/t moorejh, 23 Mar)
• Applied #rstats for the quantitative social scientist [PDF] http://bit.ly/hNUlWw ‘h/t drewconway, 23 Mar)
• impressed by #Choosel, an #opensource framework and tool for #dataviz by @lgrammel http://j.mp/bvhcHb (h/t JanWillemTulp, 23 Mar)
• There is also a good discussion about where to start with category theory (also rec. CWM and CTCS) at MathOverflow: http://bit.ly/8jxtow (h/t mdreid, 23 Mar)
• Using genome-wide pathway analysis to unravel the etiology of complex diseases http://ff.im/zxAyk (h/t kshameer, 22 Mar)
• what happens if u look all wikipedia articles with an historic reference and visualize by year on the world map? this: http://bit.ly/fLxAgP (h/t al3xandr3, 22 Mar)
• LLM3D: a log-linear modeling-based method to predict functional gene regulatory interactions from gen… http://bit.ly/fhK9Sp #citeulike (h/t neilfws, 22 Mar)
• There’s still time: Read and comment on the revised Standards for Educ and Psych Testing http://teststandards.org/index.htm @psychometrics (h/t psychometrix, 21 Mar)
• waffles: machine learning command line tools: http://waffles.sourceforge.net/ (h/t mikedewar, 21 Mar)
• some interesting #stackoverflow tag clouds if you are into that sort of thing http://goo.gl/e6ZkV (h/t codinghorror, 21 Mar)
• Great Machine Learning exercises with R. http://al3xandr3.github.com/ #rstats (h/t i_314, 21 Mar)
• An introduction to probability and statistics using Python http://ow.ly/4igsW via @boris_gorelik (h/t SciPyTip, 20 Mar)
• The Joy of #Clojure MEAP is now complete and ready for download: http://t.co/XDGGOF (h/t liebke, 19 Mar)
• P. Donneley: Quantifying the Underestimation of Relative Risks from Genome-Wide Association Studies http://goo.gl/fNPKD #GWAS (h/t genetics_blog, 18 Mar)
• New GenABEL Website, and more *ABEL software #rstats #GWAS http://goo.gl/fb/7LUK3 (h/t genetics_blog, 18 Mar)
• Interesting idea, and good start: basic ggplot2 network graphs http://bit.ly/flrYDh #rstats #sna (h/t drewconway, 18 Mar)
• Data Analysis and Manifold Learning. Course notes. Recommended http://bit.ly/e7c8s2 (h/t gappy3000, 18 Mar)
• Interactome Networks and Human Disease http://ff.im/zub1u (h/t kshameer, 18 Mar)
• RT @visualisingdata New on visualisingdata.com | Part 1: The essential collection of visualisation resources http://bit.ly/fgkey5 (h/t Biff_Bruise, 17 Mar)
• New blog post with revised statistical analyses of #canabalt scores using #rstats and #jags http://bit.ly/eR5uhb (h/t johnmyleswhite, 17 Mar)
• Great read for anyone interested in Foundations of Statistics: http://arxiv.org/abs/1006.3868 Profs. Gelman & Shalizi do a great job. #stats (h/t suncoolsu, 17 Mar)
• Good stuff for Data Mining and Cancer. http://1.usa.gov/hfwtxh https://www.oncomine.org/ #datamining #cancer (h/t i_314, 17 Mar)
• @vsbuffalo Here’s one: http://odin.mdacc.tmc.edu/~kdo/geneclust/ (h/t JohnDCook, 17 Mar)
• Milk: (Yet Another) Machine Learning Toolkit for Python http://bit.ly/fmL4KP (h/t mxlearn, 16 Mar)
• 2 more #Protovis tutorials by @jcukier More fun with arrays: http://j.mp/gECJ8R, analysis of the Map projections example: http://j.mp/hRQQiY (h/t JanWillemTulp, 16 Mar)
• RT @SignMagazine Making information beautiful and clear - a Significance toolkit on data visualisation - read for free http://ow.ly/4fwPA (h/t Biff_Bruise, 16 Mar)
• Variation across the allele frequency spectrum http://ff.im/zsx49 (h/t kshameer, 16 Mar)
• Infectious diseases not immune to genome-wide association http://ff.im/zsx48 (h/t kshameer, 16 Mar)
• Hints of hidden heritability in GWAS http://ff.im/zsx46 (h/t kshameer, 16 Mar)
• Think you can’t create web apps in #rstats? @jeffreyhorner replicated Google ngrams using Rack and ggplot2 (h/t nyhackr, 16 Mar)
• two extra pieces of my #protovis tutorial on data http://bit.ly/fk7RR1 http://bit.ly/h8l9jd (h/t jcukier, 15 Mar)
• RT @metacode: Network Analysis Basics (and applications to online networks) http://ur1.ca/3ixi5 27 slides (@RessiveNetworks) #SNA (h/t RessiveNetworks, 15 Mar)
• Where the UNIX philosophy breaks down http://bit.ly/92p5Zv (h/t CompSciFact , 15 Mar)
• Ooh, a comp bio for beginners tutorial - ADMIXTURE, R, PLINK - by @razibkhan. (Featuring… New Kids on the Block!): http://bit.ly/g6wZ8p (h/t mary_carmichael, 15 Mar)
• GHC 7.0 status update http://post.ly/1kccq (h/t irr, 15 Mar)
• This is useful (if you make maps of the world): A gallery of map projections: http://spatial.ly/fB8tS9 (h/t spatialanalysis, 15 Mar)
• Unifying Gene Expression Measures from Multiple Platforms Using Factor Analysis http://bit.ly/hAEZ7Y #citeulike (h/t neilfws, 15 Mar)
• French project #Datalift aims to develop a platform for publishing & interlinking heterogeneous data on the Web of Data: http://datalift.org (h/t nicolastorzec, 15 Mar)
• Beyond clinical phenotype: The biologic integratome http://1.usa.gov/hurOiL #readcast (h/t kshameer, 14 Mar)
• I just entered my @visualizingorg #dataviz submission http://j.mp/fmLNu3 http://yfrog.com/h2qpep It’s built in #D3 http://j.mp/fB0uJ6 (h/t JanWillemTulp, 14 Mar)
• A Review of Phase 2-3 Clinical Trial Designs http://bit.ly/hvDZeA (h/t StatFact, 14 Mar)
• The Data Structures of Python http://bit.ly/gBuIRo “We read Knuth so you don’t have to.” (h/t vsbuffalo, 14 Mar)
• Critical Assessment of Massive Data Analysis (CAMDA) http://www.camda.info/ #bioinformatics #bigdata #datamining #genomics (h/t kshameer, 14 Mar)
• Bioscala https://github.com/bioscala/bioscala/ #scala #bioinformatics (h/t yokofakun, 13 Mar)
• PyCon 2011: Introduction to Parallel Computing on an NVIDIA GPU using PyCUDA http://goo.gl/fb/cYU9R (h/t ThePSF, 13 Mar)
• People ask why I like Common Lisp. I think this short page does a very good explaining why: http://bit.ly/h1JhMZ (h/t vsbuffalo, 13 Mar)
• Motion charts in R. http://code.google.com/p/google-motion-charts-with-r/ (h/t inverseofverse, 12 Mar)
• Ensemble Learning for Variable selection; an easy read too! http://bit.ly/i31OF1 (h/t mxlearn, 12 Mar)
• Bolt Online Learning Toolbox in Python - Very cool. http://is.gd/dClHGz (h/t ChrisDiehl, 12 Mar)
• Features of Common Lisp http://post.ly/1jf5g (h/t irr, 12 Mar)
• What to demand from a scientific computing language http://ow.ly/4cDfn Presentation by Peter Norvig (h/t SciPyTip, 11 Mar)
• Here are the slides of my #pycon talk on statistical machine learning for text classification with @scikit_learn http://slidesha.re/i9dIZz (h/t ogrisel, 12 Mar)
• RT @kbradnam: A few years ago I gave a talk on ‘Trust and mistrust in bioinfo’. I think it holds up very well today: http://t.co/skQDVYr (h/t vsbuffalo, 12 Mar)
• agamemnon 0.1.1: A graph database built on top of cassandra http://bit.ly/h4rhbK (h/t pipy, 10 Mar)
• 10 papers every programmer should read (at least twice) http://bit.ly/jOjxv (h/t CompSciFact, 10 Mar)
• Science magazine special on data (requires free registration): http://bit.ly/ea2jMy (h/t algoriffic, 10 Mar)
• Comparison of Collaborative Filtering Algorithms by Cacheda et al. ACM TWEB. Vol.5(1) http://bit.ly/ffGMjb (PDF) HT @lemire (h/t chengweiwei, 10 Mar)
• #ESS complement #rautoyas, provides automatically created yasnippets for #Rstats functions. http://bit.ly/hiaACf, http://bit.ly/govY3J (h/t suncoolsu, 10 Mar)
• “Feature Selection Using Principal Feature Analysis” http://bit.ly/dH26Hk (h/t vsbuffalo, 10 Mar)
• Great Heatmaps from Microarray Data with Python and R. Tutorial and Code. http://bit.ly/fylawX #rstats #rpy #bioconductor (h/t i_314, 10 Mar)
• Dalliance: interactive genome viewing on the web http://ff.im/zo1on (h/t kshameer, 10 Mar)
• Clojure or Scala for bioinformatics/biostatistics/medical research http://goo.gl/fb/SvHPt #clojure #SO (h/t planetclojure, 9 Mar)
• Stata Blog: Understanding matrices intuitively, part 2, eigenvalues and eigenvectors http://bit.ly/gEvknE (h/t Stata, 9 Mar)
• Release candidate of LyX 2 published http://ow.ly/4arKB (h/t TeXtip, 9 Mar)
• http://jdk7.java.net/preview/ Java™ Platform, Standard Edition 7 Developer Preview Release (h/t yokofakun, 8 Mar)
• RT @TopologyFact: What are good books for computational geometry? http://bit.ly/hfBnGC (h/t CompSciFact, 8 Mar)
• my notes on #ngs variant-calling, realignment methods here: http://github.com/brentp/bio-playground/tree/master/ngs-notes #bioinformatics (h/t brent_p, 8 Mar)
• This is a great intuitive example to explain how a factor model works http://bit.ly/geOyrP (h/t gappy3000, 8 Mar)
• A brief introduction to “apply” in R: http://t.co/Zi (h/t RforBusiness, 8 Mar)
• If you are into #SemanticWeb and #Logic, have a look at “Semantic Web Technologies: From Theory To Practice” by @AxelPolleres: bit.ly/h0tGV5 (h/t nicolastorzec, 8 Mar)
• Computing on the Language in R http://t.co/D0bUFzK (h/t gappy3000, 7 Mar)
• UniSNP: uniquely mapped SNPs from dbSNP (build 129) and HapMap (release 27) http://1.usa.gov/gE3Ou0 #genomics #bioinformatics (h/t kshameer, 7 Mar)
• What are the ‘hot topics’ in MachineLearning right now? http://bit.ly/gRWxbz (h/t mxlearn, 7 Mar)
• Great list of machine learning tutorials http://bit.ly/fNnl3Q (h/t drewconway, 7 Mar)
• A philosophy of clean data, by @hadleywickham http://bit.ly/hnnqIO (h/t drewconway, 7 Mar)
• Programmatic representation of #INCEPTION : tribute to Nolan in “C” Language and a bit of assembly (x86): http://bit.ly/fszU8U #geek (h/t onertipaday, 7 Mar)
• Best use of #Protovis I’ve ever seen - http://bit.ly/iaZPMa - can anyone point to anything better? #visualization (h/t MetaThis, 7 Mar)* Ruby, Python, and Science http://bit.ly/g5QdKM (h/t SciPyTip , 6 Mar)
• J programming language source is now available under GPL version 3 http://www.jsoftware.com/source.htm (h/t hakankj, 6 Mar)
• Incredible! reMap - a visual semantic browser of the Visual Complexity database - http://bit.ly/eHhOwv (h/t MetaThis, 6 Mar)
• New blog post Creating a pdf of your favorite tweets with Apache FOP http://goo.gl/JOfzc (h/t yokofakun, 6 Mar)
• Mapping the nation’s well-being: results from Gallup’s quality of life survey http://t.co/ys (h/t nytgraphics, 5 Mar)
• @janwillemtulp it’s in my openprocessing sketches http://bit.ly/hPt1QI it’s suite simple (h/t jcukier, 5 Mar)
• #scala + #processing = va.lent.in/blog/2011/03/0… How to use the power of Scala in visual art. (h/t valyard, 4 Mar)
• “Genetic Facebook: how genes influence social networks” http://bit.ly/gDfxGk So visible behavioral phenotypes cause social groups. Who knew? (h/t vsbuffalo, 3 Mar)
• #GeoSPARQL, a proposed spatial extension to #SPARQL for dealing with geographic information: http://bit.ly/gEhrqt. #OGC #SemTech2011 (h/t nicolastorzec, 3 Mar)
• #git add some color to git diff, etc., with git config –global color.ui auto http://bit.ly/iaSTpf (h/t onelinetips, 3 Mar)
• Benchmark for several Python machine learning packages: http://fseoane.net/ml-benchmarks/ (h/t fpedregosa, 3 Mar)
• Natural Language Processing (almost) from Scratch. (arXiv:1103.0398v1 [cs.LG]) http://bit.ly/h17Puw part of the exciting Bottou conjecture (h/t sclopit, 3 Mar)
• RT @ahier: A vision for a patient-centered health information system (pdf) http://bit.ly/eg5dNO (h/t kshameer, 3 Mar)
• Brendan W. McAdams walks us through MapReduce with MongoDB 1.8 and Java. Visit http://bit.ly/ex4L45 for more info. #nosql #mongodb (h/t nosqldatabases, 2 Mar)
• If you don’t already know about #Python and #Unicode, then have a look at this nice summary by @kumar303: http://bit.ly/eF4sqD. Via @radar (h/t nicolastorzec, 2 Mar)
• Tip of the Week: DAnCER for disease-annotated epigenetics data http://bit.ly/hXkGdS #bioinformatics #genomics (h/t OpenHelix, 2 Mar)
• Check out #Eurographics Digital Library for many inspirational research papers on #infovis and related subjects: http://j.mp/fNHRqt (h/t JanWillemTulp, 2 Mar)
• Register for EuroVis 2011 in Bergen, Norway! http://tinyurl.com/4vmu3ce Important: secure your accommodation in Bergen soon! See you! :-) (h/t HelwigHauser, 2 Mar)
• ABCL Dev: Bootstrapping Quicklisp on ABCL http://tinyurl.com/4fjme37 (h/t planet_lisp, 2 Mar)
• First Steps at Building a Classifier with Mahout http://bit.ly/gRskcs (h/t mxlearn, 1 Mar)
• RT @chengweiwei @mathupdate Solving #Sudoku: A pencil-and-paper algorithm by J. Crook http://sns.ly/RJcey2 (h/t moorejh, 1 Mar)
• Lots of health data released via Health Indicators Warehouse http://datafl.ws/18h (h/t flowingdata, 1 Mar)