Posts Tagged ‘x78totwvemail’

How the NSA Almost Killed the Internet | Threat Level | Wired.com

April 29, 2014

How the #NSA Almost Killed the #Internet: Will personal data need to be stored in country of origin?
http://www.wired.com/threatlevel/2014/01/how-the-us-almost-killed-the-internet HT @fpine (1/2)

Good qt from Myhrvold: considering… threat of terrorists with bio.. degrees… tough surveillance measures might not be so bad. (2/2)

QT:{{”
There are others who argue that we may regret even modest constraints on the NSA. Former Microsoft research head Nathan Myhrvold recently wrote a hair-raising treatise arguing that, considering the threat of terrorists with biology degrees who could wipe out a good portion of humanity, tough surveillance measures might not be so bad. Myhrvold calls out the tech companies for hypoc-risy. They argue that the NSA should stop exploiting information in the name of national security, he says, but they are more than happy to do the same thing in pursuit of their bottom lines. “The cost is going to be lower efficiency in finding terrorist plots–and that cost means blood,” he says. “}}

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Finding the lost treasures in exome sequencing data

April 6, 2014

Finding lost treasures in #exome sequencing data. Mining off-target, often noncoding, reads from 1000G, TCGA, ESP, &c
http://www.ncbi.nlm.nih.gov/pubmed/23972387

Rachel Aviv: The Scientist Who Took on a Leading Herbicide Manufacturer : The New Yorker

February 20, 2014

http://www.newyorker.com/reporting/2014/02/10/140210fa_fact_aviv The Scientist Who Took on a Leading Herbicide Manufacturer: #Syngenta persecuting T Hayes over #atrazine
http://www.newyorker.com/reporting/2014/02/10/140210fa_fact_aviv HT @flcho

The draft genome of sweet orange (Citrus sinensis) – Nat Genet.

January 24, 2014

The draft #genome of sweet orange: Nearly 30K genes in only ~370 Mb + #RNAseq to find key Vitamin C genes
http://www.nature.com/ng/journal/v45/n1/full/ng.2472.html

The authors present a draft genome of sweet orange (Citrus sinensis) which covers 87.3% of the relatively compact orange genome
(approximately 367 Mb). Self-alignment of the citrus genome sequences identified one ancient triplication event, which was shared with a number of diverse plants including Arabidopsis thaliana, and no recent whole genome duplication events partially explaining the compact size of its genome. A combination of short sequence repeat (SSR) and SNP markers revealed that sweet orange is an interspecific hybrid between pummelo and mandarin (1:3 in genome composition with female of pummelo origin). Characterization of the unique protein coding genes in the citrus genome and the transcriptome analysis (RNA-Seq and RNA-PET) derived from different tissues in the citrus plant were used to identify the specific genes that are involved in the accumulation of Vitamin C in its fruit (the rate limiting GalUR in the galacturonate pathway is present in 12 copies which are developmentally regulated). Overall, the genome has almost 30,000 genes.

The draft genome of sweet orange (Citrus sinensis).
Xu Q, Chen LL, …., Ruan Y.
Nat Genet. 2013 Jan;45(1):59-66.
PMID: 23179022

Comprehensive long-span paired-end-tag mapping reveals characteristic patterns of structural variations in epithelial cancer genomes – Genome Res.

December 27, 2013

Long-span PET mapping reveals characteristic patterns of #SVs in… cancer [v norm] genomes, but no MEIs or small events
http://genome.cshlp.org/content/early/2011/04/05/gr.113555.110.abstract

The described study used long paired-end-tags (PET) to analyze and compare SVs in cancer and normal genomes. It determined the prevalence of different types of SVs in normal and cancer sample. Overall, the results are interesting and convincing on a qualitative level; however, for the reasons outlined below, more precise and quantitative delineation of the observed effects is highly desirable.

1) Small sample size of normal genomes (only 2 normal genomes)

2) Validation rate was low (< 77%) for everything except deletions, and for singletons it was even lower. .

3) Long PET is not good for finding smaller events (few kbps). Thus, this analysis missed smaller scale SVs and cancer rearrangements.

4) While there is a discussion about breakpoints and associated repeats, it is not very informative as breakpoint locations were not determined to basepair resolution.

5) No MEI were considered — particularly, no cancer MEI were considered in the analysis, while recently it was found that somatic retrotransposition occurs in cancer (Lee et al., PMID: 22745252)..

Comprehensive long-span paired-end-tag mapping reveals characteristic patterns of structural variations in epithelial cancer genomes –

Hillmer AM, Yao F, Inaki K, Lee WH, Ariyaratne PN, Teo AS, Woo XY, Zhang Z, Zhao H, Ukil L, Chen JP, Zhu F, So JB, Salto-Tellez M, Poh WT, Zawack KF, Nagarajan N, Gao S, Li G, Kumar V, Lim HP, Sia YY, Chan CS, Leong ST, Neo SC, Choi PS, Thoreau H, Tan PB, Shahab A, Ruan X, Bergh J, Hall P, Cacheux-Rataboul V, Wei CL, Yeoh KG, Sung WK, Bourque G, Liu ET, Ruan Y.

Genome Res. 2011 May;21(5):665-75. doi: 10.1101/gr.113555.110. Epub 2011 Apr 5.

Evidence of Abundant Purifying Selection in Humans for Recently Acquired Regulatory Functions

December 6, 2013

Evidence of Abundant Purifying Selection in Humans for Recently Acquired Regulatory Functions
L Ward & M Kellis
http://www.sciencemag.org/content/337/6102/1675.abs

In general we know that conservation across species and within humans are correlated. In this paper the authors focus on emphasize the exceptions to this trend. They show that although only ~5% of the human genome is conserved across mammals, regulatory regions in an additional 4% of the genomes are conserved amongst humans. They also show that some elements are conserved across mammals but lack functional activity from ENCODE data and also do not show purifying selection amongst humans. The authors pinpoint regulatory regions near color vision and nerve-growth genes for that show human-specific constraint. This has been criticized in various publications since there are other genes that are higher up in the authors’ list but harder to explain for lineage-specific constraint.

Epigenomic alterations in localized and advanced prostate cancer – Neoplasia

November 27, 2013

Summary for:

“Epigenomic Alterations in Localized and Advanced Prostate Cancer” Lin PC, Giannopoulou E, Park K, Mosquera JM, Sboner A, Tewari AK, Garraway LA, Beltran H, Rubin MA*, Elemento O*. 2013. Epigenomic alterations in localized and advanced prostate cancer. Neoplasia

http://www.ncbi.nlm.nih.gov/pubmed/23555183

In this paper, the authors take advantage of new advances in reduced representation bisulfite sequencing, a method for measuring DNA methylation patterns genome-wide, with high coverage and
single-nucleotide resolution, to study methylation patterns in prostate cancer. Working with a prostate cancer cohort already studied with DNA-Seq and RNA-Seq analyses, the authors identified
differentially methylated regions (DMRs), comparing the methylation of prostate cancer samples to benign prostate samples. The analysis found an increase in DNA methylation in prostate cancer samples, and that the methylation was more diverse and heterogeneous compared to the patterns of benign samples. Furthermore, it was found that genes near hypermethylated DMRs tended to have decreased expression, while genes near hypomethylated DMRs tended to have increased expression. Additional analyses revealed that breakpoints associated with prostate-cancer-specific deletions, duplications, and translocations tended to be highly methylated in benign prostate tissue. Finally, a study of CpG islands at different stages of prostate cancer (benign vs. PCa vs. CRPC (castration-resistant prostate cancer)) revealed that certain islands become increasingly methylated with disease severity. The authors used this data as the basis for two classification models: one to discriminate between benign prostate tissue and PCa tissue, and another to discriminate between PCa tissue and CRPC tissue. Both models demonstrated high sensitivity and specificity, indicating that CpG islands with high discriminatory power could serve as a diagnostic basis for predicting disease aggressiveness. Finally, additional analyses revealed that breakpoints associated with
prostate-cancer-specific deletions, duplications, and translocations tended to be highly methylated in benign prostate tissue.

HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants

November 27, 2013

http://nar.oxfordjournals.org/content/40/D1/D930.long

HaploReg explores functional annotations, such as chromatin states in varied cell types, sequence conservation, regulatory motif
alterations and eQTLs, of linked SNPs or indels within LD block of queried SNPs. The output provides a the guide to develop hypotheses of functional impact of non-coding variants, especially GWAS SNPs. HaploReg is currently limited to known variants (e.g. 1000 Genome variants and dbSNPs) and is unable to deal with private variants.

Ken Auletta: Can the Guardian Take Its Aggressive Investigations Global? : The New Yorker

October 29, 2013

Beyond staring down the PM: Can the Guardian Take Its Aggressive Investigations [to a] Global [Brand]? http://www.newyorker.com/reporting/2013/10/07/131007fa_fact_auletta via @Kernos501

staring down the PM to become a global brand

ANNALS OF COMMUNICATIONS
FREEDOM OF INFORMATION
A British newspaper wants to take its aggressive investigations
global, but money is running out.
http://www.newyorker.com/reporting/2013/10/07/131007fa_fact_auletta

D. T. Max: After Twitter and Square, What is Jack Dorsey’s Next Move? : The New Yorker

October 29, 2013

After [big hits at] Twitter and Square, What is @Jack Dorsey’s Next Move: Being a very rich artist! http://www.newyorker.com/reporting/2013/10/21/131021fa_fact_max MT @Sharmason

TWO-HIT WONDER

Jack Dorsey, of Twitter, is now making big money at Square—and is out
to prove that he’s more than a lucky man.

http://www.newyorker.com/reporting/2013/10/21/131021fa_fact_max