Applies to all rns
http://www.ncbi.nlm.nih.gov/pubmed/21802130
A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language? – PubMed – NCBI
Archive for the 'SciLit' Category
A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language? – PubMed – NCBI
April 26, 2015PLOS ONE: Circular RNAs Are the Predominant Transcript Isoform from Hundreds of Human Genes in Diverse Cell Types
April 26, 2015PLOS ONE: Circular RNAs Are the Predominant Transcript Isoform from Hundreds of Human Genes in Diverse Cell Types
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0030733
Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine : Nature Medicine : Nature Publishing Group
April 26, 2015Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine : Nature Medicine : Nature Publishing Group
http://www.nature.com/nm/journal/v20/n6/abs/nm.3559.html
Describes PHIAL
The External RNA Controls Consortium: a progress report – Nature Methods
April 26, 2015Another ERCC consortia, predates exRNA
http://www.nature.com/nmeth/journal/v2/n10/full/nmeth1005-731.html
“The Race” to Clone BRCA1
April 25, 2015The Race to Clone #BRCA1 http://www.sciencemag.org/content/343/6178/1462.abstract
Lessons on #LOF mutations, synthetic lethality, silly gene names & the 2-hit hypothesis
synthetic lethality (PARP inhibitors), gene names (RING fingers)
Flies Evade Looming Targets by Executing Rapid Visually Directed Banked Turns
April 25, 2015Flies Evade…Targets by Executing Rapid…Banked Turns http://www.sciencemag.org/content/344/6180/172.abstract Amazing ultrafast #movies w/ 7.5K frames/sec & IR lighting
amazing movies in supplement
10x
April 23, 2015http://www.ncbi.nlm.nih.gov/pubmed/25477383
also
http://www.ncbi.nlm.nih.gov/pubmed/25477383
Nucleic Acids Res. 2015 Feb 27;43(4):e23. doi: 10.1093/nar/gku1252. Epub 2014 Dec 3.
Allele-specific copy number profiling by next-generation DNA sequencing. Chen H1, Bell JM2, Zavala NA2, Ji HP2, Zhang NR3.
perhaps related?
Health: Make precision medicine work for cancer care
April 20, 2015Make #precisionmedicine work for cancer http://www.nature.com/news/health-make-precision-medicine-work-for-cancer-care-1.17301 @MarkARubin1: >90% of…patients carry a mutation that may be drug-responsive
QT:{{"
“Hugely complicated genomic reports are rarely available in electronic form and are seldom tied to basic information about the patient. Whole-genome sequencing on tumour samples from nearly 14,000 people by the International Cancer Genome Consortium (ICGC), for instance, has revealed nearly 13 million mutations across the genome.
…
Since 2013, working with a team of computational biologists from Weill Cornell and the Centre for Integrative Biology at the University of Trento in Italy, my colleagues and I have conducted a pilot programme to determine the feasibility of tying genomic to clinical data in real time. So far, we have created easy-to-read reports for 250 people with cancer.
…
We have discovered that more than
"more than 90% of our patients carry a mutation that may be responsive to a known drug — although less than 10% of the patients may be eligible for a clinical trial either for logistical reasons or because there is insufficient evidence to warrant trying a non-approved drug.”
"}}
BRAF pseudogene and cancer development
April 17, 2015BRAF #Pseudogene Functions as a Competitive Endogenous RNA; [Shows it] induces Lymphoma [after alteration, in mice]
http://www.cell.com/cell/abstract/S0092-8674(15)00244-5
Cell. 2015 Apr 9;161(2):319-32. doi: 10.1016/j.cell.2015.02.043. Epub 2015 Apr 2.
Karreth FA1, Reschke M1, Ruocco A1, Ng C1, Chapuy B2, Léopold V1, Sjoberg M3, Keane TM3, Verma A4, Ala U1, Tay Y1, Wu D5, Seitzer N1, Velasco-Herrera Mdel C3, Bothmer A1, Fung J1, Langellotto F6, Rodig SJ7, Elemento O4, Shipp MA2, Adams DJ3, Chiarle R8, Pandolfi PP9.
Abstract
Research over the past decade has suggested important roles for pseudogenes in physiology and disease. In vitro experiments
demonstrated that pseudogenes contribute….
In Search of Bayesian Inference
April 12, 2015In Search of #Bayesian Inference
http://cacm.acm.org/magazines/2015/1/181628-in-search-of-bayesian-inference/fulltext Nice intuition on priors in recovering air-crash wreckage & analyzing mammographs
QT:{{”
In its most basic form, Bayes’ Law is a simple method for updating beliefs in the light of new evidence. Suppose there is some statement A that you initially believe has a probability P(A) of being correct (what Bayesians call the “prior” probability). If a new piece of evidence, B, comes along, then the probability that A is true given that B has happened (what Bayesians call the “posterior” probability) is given by
P(A|B)=P(B|A) P(A) / P(B)
where P(B|A) is the likelihood that B would occur if A is true, and P (B) is the likelihood that B would occur under any circumstances.
Consider an example described in Silver’s book The Signal and the Noise: A woman in her forties has a positive mammogram, and wants to know the probability she has breast cancer. Bayes’ Law says that to answer this question, we need to know three things: the probability that a woman in her forties will have breast cancer (about 1.4%); the probability that if a woman has breast cancer, the mammogram will detect it (about 75%); and the probability that any random woman in her forties will have a positive mammogram (about 11%). Putting these figures together, Bayes’ Law—named after the Reverend Thomas Bayes, whose manuscript on the subject was published posthumously in 1763—says the probability the woman has cancer, given her positive mammogram result, is just under 10%; in other words, about 9 out of 10 such mammogram results are false positives.
In this simple setting, it is clear how to construct the prior, since there is plenty of data available on cancer rates. In such cases, the use of Bayes’ Law is uncontroversial, and essentially a tautology—it simply says the woman’s probability of having cancer, in light of her positive mammogram result, is given by the proportion of positive mammograms that are true positives. Things get murkier when
statisticians use Bayes’ rule to try to reason about one-time events, or other situations in which there is no clear consensus about what the prior probabilities are. For example, large passenger airplanes do not crash into the ocean very often, and when they do, the
circumstances vary widely. In such cases, the very notion of prior probability is inherently subjective; it represents our best belief, based on previous experiences, about what is likely to be true in this particular case. If this initial belief is way off, we are likely to get bad inferences.
“}}
linkstream2 microblog 