linkstream2 microblog

http://www.amazon.com/Turings-Cathedral-Origins-Digital-Universe/dp/1400075998

http://www.newyorker.com/magazine/2015/05/11/overkill-atul-gawande

http://wikibon.org/blog/big-data-statistics/

#Machinelearning applications in…genomics
http://www.nature.com/nrg/journal/v16/n6/full/nrg3920.html Nice overview of key distinctions betw generative & discriminative models

In their review, “Machine learning in genetics and genomics”, Libbrecht and Noble overview important aspects of application of machine learning to genomic data. The review presents illustrative classical genomics problems where machine learning techniques have proven useful and describes the differences between supervised, semi-supervised and unsupervised learning as well as generative and discriminative models. The authors discuss considerations that should be made when selecting the right machine learning approach depending on the biological problem and data at hand, provide general practical guidelines and suggest possible solutions to common challenges.

Identification of #Asthma Phenotypes Using Cluster Analysis
http://www.atsjournals.org/doi/abs/10.1164/rccm.200906-0896OC#.VWk-gFxViko 5 canonical groups based on lung function, meds usage, &c

Canonical clustering of asthmatic patients into different groups

http://www.nytimes.com/2015/05/26/science/review-digital-doctor-robert-wachter.html?_r=0

http://www.newscientist.com/article/mg22630221.600-how-to-clone-a-mammoth-but-should-we.html?cmpid=RSS|NSNS|2012-GLOBAL|online-news#.VWRThkaYqVo

Analysis of the Sputum Transcriptome Discriminates Clinical Phenotypes of Asthma http://www.atsjournals.org/doi/abs/10.1164/rccm.201408-1440OC Consistent blood expression patterns

Noninvasive Analysis of the Sputum Transcriptome Discriminates
Clinical Phenotypes of Asthma (ATS Journals)

Yan, X., Chu, J.-H., Gomez, J., Koenigs, M., Holm, C., He, X., Perez,
M. F., Zhao, H., Mane, S., Martinez, F. D., Ober, C., Nicolae, D. L.,
Barnes, K. C., London, S. J., Gilliland, F., Weiss, S. T., Raby, B.
A., Cohn, L., and Chupp, G. L. “Non-Invasive Analysis of the Sputum
Transcriptome Discriminates Clinical Phenotypes of Asthma” American
Journal of Respiratory and Critical Care Medicine (2015):
doi:10.1164/rccm.201408-1440OC,

QT:{{"
Conclusions: There are common patterns of gene expression in the
sputum and blood of children and adults that are associated with near
fatal, severe and milder asthma.
"}}

https://urldefense.proofpoint.com/v2/url?u=http-3A__journals.plos.org_ploscompbiol_article-3Fid-3D10.1371_journal.pcbi.1002487&d=AwICaQ&c=-dg2m7zWuuDZ0MUcV7Sdqw&r=k13szPaSoN-FV15yTT5Guyx7KbJMywtSANe0quSPJ-Q&m=bZIFAkNSi8NF1wbG2V3qEghExU8S5lNbi8SfpDZkiUE&s=18b9riJMEqLSMyVP1_3d4Ks4iq_F_glF-97Hwn9SPps&e=

http://www.newyorker.com/magazine/2015/05/04/the-engineers-lament