Biology Reference
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[37] Bartfai T, Buckley PT, Eberwine J. Drug targets: single-cell tran-
scriptomics hastens unbiased discovery. Trends Pharmacol Sci
2012;33:9 e 16.
[38] Liu L, Ye Q, Wu Y, Hsieh WY, Chen CL, Shen HH, et al.
Tracking T-cells in vivo with a new nano-sized MRI contrast
agent. Nanomedicine 2012; http://dx.doi.org/10.1016/j.nano.
2012.02.017 .
[39] Heath JR, Davis ME, Hood L. Nanomedicine targets cancer. Sci
Am 2009;300:44 e 51.
[40] Chakraborty M, Jain S, Rani V. Nanotechnology: emerging tool for
diagnostics and therapeutics. Appl Biochem Biotechnol 2011;165:
1178 e 87.
[41] Shi Q, Qin L, Wei W, Geng F, Fan R, Shin YS, et al. Single-cell
proteomic chip for profiling intracellular signaling pathways
in single tumor cells. Proc Natl Acad Sci U S A 2012;109:
419 e 24.
[42] Hodgson J. Gene sequencing's industrial revolution. Spectrum
2000;37:36 e 42.
[43] International human genome sequencing consortium. Finishing the
euchromatic sequence of the human genome. Nature 2004;431:
931 e 45.
[44] Oxford Nanopore Press release. DNA 'Strand Sequencing' on the
High-Throughput GridION Platform and Presents MinION,
a Sequencer the Size of a USB Memory Stick. Oxford: Oxford
Nanopore; 2012.
[45] American Medical Association (AMA) Proteomics, http://www.
ama-assn.org ; 2012.
[46] Juritz EI, Alberti SF, Parisi GD. PCDB: a database of pro-
tein conformational diversity. Nucleic Acids Res 2011;39:
D475 e 479.
[47] Moritz R. Institute for systems biology. Pers Commun 2012.
[48] Connor AC, McGown LB. Aptamer stationary phase for protein
capture in affinity capillary chromatography. J Chromatogr A
2006;1111:115 e 9.
[49] Zichel R, Chearwae W, Pandey GS, Golding B, Sauna ZE.
Aptamers as a sensitive tool to detect subtle modifications in
therapeutic proteins. PLoS One 2012;7:e31948.
[50] Rakhila H, Rozek T, Hopkins A, Proudman S, Cleland L, James M,
et al. Quantitation of total and free teriflunomide (A77 1726) in human
plasma by LC-MS/MS. J Pharm Biomed Anal 2011;55:325 e 31.
[51] Sung J. Molecular signatures from omics data: from chaos to
consensus. Biotechnol J 2012;7(8)946 e 57.
[52] Leek JT, Scharpf RB, Bravo HC, Simcha D, Langmead B,
Johnson WE, et al. Tackling the widespread and critical impact of
batch effects in high-throughput data. Nat Rev Genet 2010;11:733 e 9.
[53] Ein-Dor L, Zuk O, Domany E. Thousands of samples are needed to
generate a robust gene list for predicting outcome in cancer. Proc
Natl Acad Sci U S A 2006;103:5923 e 8.
[54] Quackenbush J. Microarray analysis and tumor classification.
N Engl J Med 2006;354:2463 e 72.
[55] Sirota M, Dudley JT, Kim J, Chiang AP, Morgan AA, Sweet-
Cordero A, et al. Discovery and preclinical validation of drug
indications using compendia of public gene expression data. Sci
Transl Med 2011;3:96ra77.
[56] Hibbard JH, Stockard J, Mahoney ER, Tusler M. Development of
the Patient Activation Measure (PAM): conceptualizing and
measuring activation in patients and consumers. Health Serv Res
2004;39:1005 e 26.
[57] Pleasance ED, Cheetham RK, Stephens PJ, McBride DJ,
Humphray SJ, Greenman CD, et al. A comprehensive catalogue of
somatic mutations from a human cancer genome. Nature 2010;463:
191
6.
[58] Dancey JE, Bedard PL, Onetto N, Hudson TJ. The genetic basis for
cancer treatment decisions. Cell 2012;148:409 e 20.
[59] Bonneau R, Facciotti MT, Reiss DJ, Schmid AK, Pan M, Kaur A,
et al. A predictive model for transcriptional control of physiology
in a free living cell. Cell 2007;131:1354 e 65.
[60] BarabĀ“si A-L. N Engl J Med 2007;357(4):404 e 7.
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