Geeleher cites http://genome.CSHLP.org/content/early/2017/08/28/gr.221077.117?top=1 … Novel pharmacogenomic biomarkers by imputing drug response in cancer..from…genomics studies #ASHG17
http://genome.cshlp.org/content/early/2017/08/28/gr.221077.117?top=1
Posts Tagged ‘cancer’
Discovering novel pharmacogenomic biomarkers by imputing drug response in cancer patients from large genomics studies
October 21, 2017Assembly-based inference of B-cell receptor repertoires from short read RNA sequencing data with V’DJer | Bioinformatics | Oxford Academic
September 30, 2017Assembly-based inference of Bcell receptor repertoires from..RNAseq w/
V’DJer https://academic.OUP.com/bioinformatics/article/32/24/3729/2525640/Assembly-based-inference-of-B-cell-receptor Less diversity assoc w/ long survival
Breaking Into The Brain | Chemical & Engineering News
September 22, 2017Breaking Into the #Brain
http://CEN.ACS.org/articles/92/i2/Breaking-Brain.html Contrasts potential for drug discovery in neuro-diseases v #cancer (which is “easier”)
interesting brain v cancer contrast
Whole-genome landscapes of major melanoma subtypes : Nature : Nature Research
September 4, 2017Hayward, Nicholas K., et al. "Whole-genome landscapes of major melanoma subtypes." Nature 545.7653 (2017): 175-180.
Whole-genome landscapes of…#melanoma subtypes http://www.Nature.com/nature/journal/vaop/ncurrent/full/nature22071.html Sun-exposed cutaneous w. many C>T SNVs v acral/mucosal w. many SVs
Naked mole rats: Can they help us cure cancer? – Slate Magazine
July 31, 2017Naked mole rats: Can they help..cure cancer?
http://www.Slate.com/articles/health_and_science/the_mouse_trap/2011/11/naked_mole_rats_can_they_help_us_cure_cancer_.html Live >6x longer than C57BL/6 & have “insectile” queen-domimated society
A Big Bang model of human colorectal tumor growth : Nature Genetics : Nature Research
June 7, 2017https://www.nature.com/ng/journal/v47/n3/full/ng.3214.html
Big Bang model of…tumor growth, v. slow #evolution under selection https://www.Nature.com/ng/journal/v47/n3/full/ng.3214.html #Cancer is born w/ key mutations all there
Andrea Sottoriva,
Haeyoun Kang,
Zhicheng Ma,
Trevor A Graham,
Matthew P Salomon,
Junsong Zhao,
Paul Marjoram,
Kimberly Siegmund,
Michael F Press,
Darryl Shibata
& Christina Curtis
Nature Genetics 47, 209–216 (2015) doi:10.1038/ng.3214
Cell Signaling by Receptor Tyrosine Kinases: Cell
May 20, 2017[category scilit]
Cell signaling by #RTKs Nice 1st fig showing 20 sub-families and architecture of extra- & intra- cellular domains
A.I. Versus M.D.
May 7, 2017AI v MD by @DrSidMukherjee http://www.NewYorker.com/magazine/2017/04/03/ai-versus-md great progress finding skin #cancer. Eventually, continuous monitoring via iPhone pics
QT:{{"
“In June, 2015, Thrun’s team began to test what the machine had learned from the master set of images by presenting it with a “validation set”: some fourteen thousand images that had been diagnosed by dermatologists (although not necessarily by biopsy). Could the system correctly classify the images into three diagnostic categories—benign lesions, malignant lesions, and non-cancerous growths? The system got the answer right seventy-two per cent of the time. …Two board-certified dermatologists who were tested alongside did worse: they got the answer correct sixty-six per cent of the time.
…
“There’s one rather profound thing about the network that wasn’t fully emphasized in the paper,” Thrun told me. In the first iteration of the study, he and the team had started with a totally naïve neural network. But they found that if they began with a neural network that had already been trained to recognize some unrelated feature (dogs versus cats, say) it learned faster and better. Perhaps our brains function similarly. Those mind-numbing exercises in high school—factoring polynomials, conjugating verbs, memorizing the periodic table—were possibly the opposite: mind-sensitizing.”
"}}
Genes, environment, and “bad luck” | Science
March 26, 2017Genes, environment & bad luck
http://science.ScienceMag.org/content/355/6331/1266 To what degree are #cancer mutations due to replication error (3rd factor), not 1st 2?
discusses R v D correlation
Stem cell divisions, somatic mutations, cancer etiology, and cancer prevention Cristian Tomasetti1,2,*, Lu Li2, Bert Vogelstein3,*
Science 24 Mar 2017:
Vol. 355, Issue 6331, pp. 1330-1334
DOI: 10.1126/science.aaf9011
http://science.sciencemag.org/content/355/6331/1330
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