References
1. Martin Hilbert M, Lopez P. The world’s technological capacity to store, communicate, and compute information. Science. 2011;332:60–65.
2. Schmidt S. Data is exploding: the 3 V’s of big data. Business Computing World May 15, 2012.
3. An assessment of the impact of the NCI cancer Biomedical Informatics Grid (CaBIG). Report of the Board of Scientific Advisors Ad Hoc Working Group, National Cancer Institute, March, 2011. Available from: http://deainfo.nci.nih.gov/advisory/bsa/bsa0311/caBIGfinalReport.pdf; viewed January 31, 2013.
4. Komatsoulis GA. Program announcement to the CaBIG community. Available from: National Cancer Institute August 31, 2012; https://cabig.nci.nih.gov/program_announcement; August 31, 2012; viewed.
5. Freitas A, Curry E, Oliveira JG, O’Riain S. Querying heterogeneous datasets on the linked data web: challenges, approaches, and trends. Available from: IEEE Internet Computing. 2012;16:24–33 http://www.edwardcurry.org/publications/freitas_IC_12.pdf; 2012; viewed September 25, 2012.
6. Drake TA, Braun J, Marchevsky A, et al. A system for sharing routine surgical pathology specimens across institutions: the Shared Pathology Informatics Network (SPIN). Hum Pathol. 2007;38:1212–1225.
7. Francis M. Future telescope array drives development of exabyte processing. Ars Technica April 2, 2012.
8. Markoff J. A deluge of data shapes a new era in computing. The New York Times December 15, 2009.
9. Harrington JD, Clavin W. NASA’s WISE mission sees skies ablaze with Blazars. April 12, 2002; NASA Release 12-109.
10. Core techniques and technologies for advancing Big Data science. National Science Foundation program solicitation NSF 12-499, June 13, 2012. Available from: http://www.nsf.gov/pubs/2012/nsf12499/nsf12499.txt; viewed September 23, 2012.
11. Bianciardi G, Miller JD, Straat PA, Levin GV. Complexity analysis of the Viking labeled release experiments. Intl J Aeronautical Space Sci. 2012;13:14–26.
12. Hayes A. VA to apologize for mistaken Lou Gehrig’s disease notices. Available from: CNN August 26, 2009; http://www.cnn.com/2009/POLITICS/08/26/veterans.letters.disease; August 26, 2009; viewed September 4, 2012.
13. Hall PA, Lemoine NR. Comparison of manual data coding errors in 2 hospitals. J Clin Pathol. 1986;39:622–626.
14. Berman JJ. Doublet method for very fast autocoding. BMC Med Inform Decis Mak. 2004;4:16.
15. Berman JJ. Nomenclature-based data retrieval without prior annotation: facilitating biomedical data integration with fast doublet matching. In Silico Biol. 2005;5:0029.
16. Swanson DR. Undiscovered public knowledge. Libr Q. 1986;56:103–118.
17. Wallis E, Lavell C. Naming the indexer: where credit is due. The Indexer. 1995;19:266–268.
18. Krauthammer M, Nenadic G. Term identification in the biomedical literature. J Biomed Inform. 2004;37:512–526.
19. Berman JJ. Methods in medical informatics: fundamentals of healthcare programming in Perl, Python, and Ruby. Boca Raton, FL: Chapman and Hall; 2010.
20. Shah NH, Jonquet C, Chiang AP, Butte AJ, Chen R, Musen MA. Ontology-driven indexing of public datasets for translational bioinformatics. BMC Bioinform. 2009;10(Suppl. 2):S1.
21. Cohen T, Whitfield GK, Schvaneveldt RW, Mukund K, Rindflesch T. EpiphaNet: an interactive tool to support biomedical discoveries. J Biomed Discov Collab. 2010;5:21–49.
22. Swanson DR. Fish oil, Raynaud’s syndrome, and undiscovered public knowledge. Perspect Biol Med. 1986;30:7–18.
23. Reed DP. Naming and synchronization in a decentralized computer system. MIT 1978; Doctoral Thesis.
24. Joint NEMA/COCIR/JIRA Security and Privacy Committee (SPC). Identification and allocation of basic security rules in healthcare imaging systems September, 2002; Available from: http://www.medicalimaging.org/wp-content/uploads/2011/02/Identification_and_Allocation_of_Basic_Security_Rules_In_Healthcare_Imaging_Systems-September_2002.pdf; September, 2002; viewed January 10, 2013.
25. Kuzmak P, Casertano A, Carozza D, Dayhoff R, Campbell K. Solving the problem of duplicate medical device unique identifiers: High Confidence Medical Device Software and Systems (HCMDSS) workshop. Philadelphia, PA June 2-3, 2005; Available from: http://www.cis.upenn.edu/hcmdss/Papers/submissions/; June 2-3, 2005; viewed August 26, 2012.
26. Health Level 7 OID Registry. Available from: http://www.hl7.org/oid/frames.cfm; viewed August 26, 2012.
27. Leach P, Mealling M, Salz R. A Universally Unique IDentifier (UUID) URN namespace. Request for Comment 4122, Standards Track. Available from: Network Working Group August 26, 2012; http://www.ietf.org/rfc/rfc4122.txt; August 26, 2012; viewed.
28. Berman JJ. Confidentiality for medical data miners. Art Intell Med. 2002;26:25–36.
29. Patient Identity Integrity. A White Paper by the HIMSS Patient Identity Integrity Work Group, December 2009. Available from: http://www.himss.org/content/files/PrivacySecurity/PIIWhitePaper.pdf; viewed September 19, 2012.
30. Berman JJ. Biomedical informatics. Sudbury, MA: Jones and Bartlett; 2007.
31. Pakstis AJ, Speed WC, Fang R, et al. SNPs for a universal individual identification panel. Hum Genet. 2010;127:315–324.
32. Katsanis SH, Wagner JK. Characterization of the standard and recommended CODIS markers. J Foren Sci 2012; Aug 24.
33. Department of Health and Human Services. 45 CFR (Code of Federal Regulations), Parts 160 through 164 Standards for Privacy of Individually Identifiable Health Information (Final Rule). Fed Reg. 2000;65(250):82461–82510.
34. Department of Health and Human Services. 45 CFR (Code of Federal Regulations), 46 Protection of Human Subjects (Common Rule). Fed Reg. 1991;56:28003–28032.
35. Berman JJ. Concept-match medical data scrubbing: how pathology datasets can be used in research. Arch Pathol Lab Med. 2003;127:680–686.
36. Berman JJ. Comparing de-identification methods. Available from: http://www.biomedcentral.com/1472-6947/6/12/comments/comments.htm; March 31, 2006; viewed January 31, 2013.
37. Knight J. Agony for researchers as mix-up forces retraction of ecstasy study. Nature. 2003;425:109.
38. Sainani K. Error: what biomedical computing can learn from its mistakes. Biomed Comput Rev 2011;12–19 Fall.
39. Palanichamy MG, Zhang Y. Potential pitfalls in MitoChip detected tumor-specific somatic mutations: a call for caution when interpreting patient data. BMC Cancer. 2010;10:597.
40. Bandelt H, Salas A. Contamination and sample mix-up can best explain some patterns of mtDNA instabilities in buccal cells and oral squamous cell carcinoma. BMC Cancer. 2009;9:113.
41. Harris G. U.S Inaction lets look-alike tubes kill patients. The New York Times August 20, 2010.
42. Flores G. Science retracts highly cited paper: study on the causes of childhood illness retracted after author found guilty of falsifying data. The Scientist June 17, 2005.
43. Gowen LC, Avrutskaya AV, Latour AM, Koller BH, Leadon SA. Retraction of: Gowen LC, Avrutskaya AV, Latour AM, Koller BH, Leadon SA. Science. 1998 Aug 14;281(5379):1009-12. Science. 2003;300:1657.
44. Pearson K. The grammar of science. London: Adam and Black; 1900.
45. Berman JJ. Racing to share pathology data. Am J Clin Pathol. 2004;121:169–171.
46. Scamardella JM. Not plants or animals: a brief history of the origin of kingdoms Protozoa, Protista and Protoctista. Intl Microbiol. 1999;2:207–216.
47. Madar S, Goldstein I, Rotter V. Did experimental biology die? Lessons from 30 years of p53 research. Cancer Res. 2009;69:6378–6380.
48. Zilfou JT, Lowe SW. Tumor suppressive functions of p53. Cold Spring Harb Perspect Biol 2009;a001883 00.
49. Berman JJ. Taxonomic guide to infectious diseases: understanding the biologic classes of pathogenic organisms. Waltham: Academic Press; 2012.
50. Suggested Upper Merged Ontology (SUMO). The OntologyPortal. Available from: http://www.ontologyportal.org; viewed August 14, 2012.
51. de Bruijn J. Using ontologies: enabling knowledge sharing and reuse on the Semantic Web. Digital Enterprise Research Institute Technical Report DERI-2003-10-29, October 2003. Available from: http://www.deri.org/fileadmin/documents/DERI-TR-2003-10-29.pdf; viewed August 14, 2012.
52. Guarro J, Gene J, Stchigel AM. Developments in fungal taxonomy. Clin Microbiol Rev. 1999;12:454–500.
53. Nakayama R, Nemoto T, Takahashi H, et al. Gene expression analysis of soft tissue sarcomas: characterization and reclassification of malignant fibrous histiocytoma. Modern Pathol. 2007;20:749–759.
54. Richard Cote R, Reisinger F, Martens L, Barsnes H, Vizcaino JA, Hermjakob H. The ontology lookup service: bigger and better. Nucleic Acids Res. 2010;38:W155–W160.
55. Neumann T, Weikum G. xRDF3X: Fast querying, high update rates, and consistency for RDF databases. Proceedings of the VLDB Endowment. 2010;3:256–263.
56. Berman JJ. A tool for sharing annotated research data: the “Category 0” UMLS (Unified Medical Language System) vocabularies. BMC Med Inform Decis Mak. 2003;3:6.
57. Kuchinke W, Ohmann C, Yang Q, et al. Heterogeneity prevails: the state of clinical trial data management in Europe - results of a survey of ECRIN centres. Trials. 2010;11:79.
58. Berman JJ, Edgerton ME, Friedman B. The Tissue Microarray Data Exchange Specification: a community-based, open source tool for sharing tissue microarray data. BMC Med Inform Dec Mak. 2003;3:5.
59. Deutsch EW, Ball CA, Berman JJ, et al. Minimum Information Specification For In Situ Hybridization and Immunohistochemistry Experiments (MISFISHIE). Nature Biotechnol. 2008;26:305–312.
60. Gates S. Qualcomm v Broadcom: The federal circuit weighs in on “patent ambushes”. Available from: http://www.mofo.com/qualcomm-v-broadcom—the-federal-circuit-weighs-in-on-patent-ambushes-12-05-2008; December 5, 2008; viewed January 22, 2013.
61. Cahr D, Kalina I. Of pacs and trolls: how the patent wars may be coming to a hospital near you. ABA Health Lawyer. 2006;19:15–20.
62. Duncan M. Terminology version control discussion paper: the chocolate teapot. Available from: Medical Object Oriented Software Ltd September 15, 2009; http://www.mrtablet.demon.co.uk/chocolate_teapot_lite.htm; September 15, 2009; viewed August 30, 2012.
63. Cavalier-Smith T. The phagotrophic origin of eukaryotes and phylogenetic classification of Protozoa. Int J Syst Evol Microbiol. 2002;52(Pt 2):297–354.
64. Jennings N. On agent-based software engineering. Art Intell. 2000;117:277–296.
65. Berman JJ. Ruby programming for medicine and biology. Sudbury, MA: Jones and Bartlett; 2008.
66. Forsyth J. What sank the Titanic? Scientists point to the moon. Reuters March 7, 2012.
67. Shane S. China inspired interrogations at Guantanamo. The New York Times July 2, 2008.
68. Greenhouse L. In court ruling on executions, a factual flaw. The New York Times July 2, 2008.
69. Berman JJ. Zero-check: a zero-knowledge protocol for reconciling patient identities across institutions. Arch Pathol Lab Med. 2004;128:344–346.
70. Booker D, Berman JJ. Dangerous abbreviations. Hum Pathol. 2004;35:529–531.
71. Berman JJ. Pathology abbreviated: a long review of short terms. Arch Pathol Lab Med. 2004;128:347–352.
72. Available from: Patient safety in American hospitals. HealthGrades July, 2004; http://www.healthgrades.com/media/english/pdf/hg_patient_safety_study_final.pdf; July, 2004; viewed September 9, 2012.
73. Gordon R. Great medical disasters. New York: Dorset Press; 1986; p. 155—60.
74. Vital signs: unintentional injury deaths among persons aged 0-19 years; United States, 2000-2009. Centers for disease Control and Prevention Morbidity and Mortality Weekly Report (MMWR). April 16, 2012;61:1–7.
75. Rigler T. DOD discloses new figures on Korean War dead. Army News Service May 30, 2000.
76. Frey CM, McMillen MM, Cowan CD, Horm JW, Kessler LG. Representativeness of the surveillance, epidemiology, and end results program data: recent trends in cancer mortality rate. JNCI. 1992;84:872.
77. Ashworth TG. Inadequacy of death certification: proposal for change. J Clin Pathol. 1991;44:265.
78. Kircher T, Anderson RE. Cause of death: proper completion of the death certificate. JAMA. 1987;258:349–352.
79. Walter SD, Birnie SE. Mapping mortality and morbidity patterns: an international comparison. Intl J Epidemiol. 1991;20:678–689.
80. Pennisi E. Gene counters struggle to get the right answer. Science. 2003;301:1040–1041.
81. How many genes are in the human genome? Human Genome Project information June 10, 2012; Available from: http://www.ornl.gov/sci/techresources/Human_Genome/faq/genenumber.shtml; June 10, 2012; viewed.
82. Mitchell KJ, Becich MJ, Berman JJ, et al. Implementation and evaluation of a negation tagger in a pipeline-based system for information extraction from pathology reports. MEDINFO. 2004;2004:663–667.
83. Pollack A. Forty years’ war: taking risk for profit, industry seeks cancer drugs. The New York Times September 2, 2009.
84. Berkrot B, Pierson R. OSI sees $2 billion Tarceva sales by 2011. Reuters Feb 23, 2006.
85. Irizarry RA, Warren D, Spencer F, et al. Multiple-laboratory comparison of microarray platforms. Nat Methods. 2005;2:345–350.
86. Mathelin C, Cromer A, Wendling C, Tomasetto C, Rio MC. Serum biomarkers for detection of breast cancers: a prospective study. Breast Cancer Res Treat. 2006;96:83–90.
87. Kolata G. Cancer fight: unclear tests for new drug. The New York Times April 19, 2010.
88. Begley CG, Ellis LM. Drug development: raise standards for preclinical cancer research. Nature. 2012;483:531–533.
89. Begley S. In cancer science, many ‘discoveries’ don’t hold up. Reuters Mar 28, 2012.
90. Venet D, Dumont JE, Detours V. Most random gene expression signatures are significantly associated with breast cancer outcome. PLoS Comput Biol. 2011;7:e1002240.
91. Gatty H. Finding your way without map or compass. Mineola: Dover; 1958.
92. Levenberg K. A method for the solution of certain non-linear problems in least squares. Q App Math. 1944;2:164–168.
93. Marquardt DW. An algorithm for the least-squares estimation of nonlinear parameters. SIAM J Appl Math. 1963;11:431–441.
94. Lee J, Pham M, Lee J, et al. Processing SPARQL queries with regular expressions in RDF databases. BMC Bioinform. 2011;12(Suppl. 2):S6.
95. Thompson CW. The trick to D.C police force’s 94% closure rate for 2011 homicides. The Washington Post February 19, 2012.
96. Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Statist Assn. 1958;53:457–481.
97. SEER. Surveillance epidemiology end results. National Cancer Institute April 22, 2013; Available from: http://seer.cancer.gov/; April 22, 2013; viewed.
98. Berman JJ, Moore GW. The role of cell death in the growth of preneoplastic lesions: a Monte Carlo simulation model. Cell Prolif. 1992;25:549–557.
99. Perez-Pena R. New York’s tally of heat deaths draws scrutiny. The New York Times August 18, 2006.
100. Chiang S. Heat waves, the “other” natural disaster: perspectives on an often ignored epidemic. Global Pulse American Medical Student Association 2006.
101. Shah S, Horne A, Capella J. Good data won’t guarantee good decisions. Harv Bus Rev. April, 2012.
102. White T. Hadoop: the definitive guide. O’Reilly Media 2009.
103. Owen S, Anil R, Dunning T, Friedman E. Mahout in action. Shelter Island, NY: Manning Publications Co; 2012.
104. Janert PK. Data analysis with open source tools. O’Reilly Media 2010.
105. Lewis PD. R for medicine and biology. Sudbury: Jones and Bartlett Publishers; 2009.
106. Segaran T. Programming collective intelligence: building smart Web 2.0 applications. O’Reilly Media 2007.
107. Wu X, Kumar V, Quinlan JR, et al. Top 10 algorithms in data mining. Knowl Inf Syst. 2008;14:1–37.
108. Zhang L, Lin X. Some considerations of classification for high dimension low-sample size data. Available from: Stat Methods Med Res 2011 Nov 23; http://smm.sagepub.com/content/early/2011/11/22/0962280211428387.long; 2011 Nov 23; viewed January 26, 2013.
109. Szekely GJ, Rizzo ML. Brownian distance covariance. Ann Appl Stat. 2009;3:1236–1265.
110. Reshef DN, Reshef YA, Finucane HK, et al. Detecting novel associations in large data sets. Science. 2011;334:1518–1524.
111. Marsaglia G, Tsang WW. Some difficult-to-pass tests of randomness. Available from: J Stat Software. 2002;7:1–8 http://www.jstatsoft.org/v07/i03/paper; 2002; viewed September 25, 2012.
112. Cleveland Clinic: build an efficient pipeline to find the most powerful predictors. Innocentive September 8, 2011; https://www.innocentive.com/ar/challenge/9932794; September 8, 2011; viewed September 25, 2012.
113. Wu D, Hugenholtz P, Mavromatis K, et al. A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea. Nature. 2009;462:1056–1060.
114. Woese CR, Fox GE. Phylogenetic structure of the prokaryotic domain: the primary kingdoms. PNAS. 1977;74:5088–5090.
115. Mayr E. Two empires or three? PNAS. 1998;95:9720–9723.
116. Woese CR. Default taxonomy: Ernst Mayr’s view of the microbial world. PNAS. 1998;95:11043–11046.
117. Bamshad MJ, Olson SE. Does race exist? Sci Am 2003;78–85 December.
118. Wadman M. Geneticists struggle towards consensus on place for ‘race’. Nature. 2004;431:1026.
119. Gerlinger M, Rowan AJ, Horswell S, et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med. 2012;366:883–892.
120. Molyneux G, Smalley MJ. The cell of origin of BRCA1 mutation-associated breast cancer: a cautionary tale of gene expression profiling. J Mammary Gland Biol Neoplasia. 2011;16:51–55.
121. Sainani K. Meet the skeptics: why some doubt biomedical models, and what it takes to win them over. Biomed Comput Rev 2012 June 5.
122. Ioannidis JP. Microarrays and molecular research: noise discovery? The Lancet. 2005;365:454–455.
123. Salmon F. Recipe for disaster: the formula that killed Wall Street. Wired Magazine February 23, 2009; 17:03.
124. Ransohoff DF. Rules of evidence for cancer molecular-marker discovery and validation. Nat Rev Cancer. 2004;4:309–314.
125. Innovation or stagnation: challenge and opportunity on the critical path to new medical products. U.S. Department of Health and Human Services, Food and Drug Administration 2004.
126. Wurtman RJ, Bettiker RL. The slowing of treatment discovery, 1965-1995. Nat Med. 1996;2:5–6.
127. Saul S. Prone to error: earliest steps to find cancer. The New York Times July 19, 2010.
128. Benowitz S. Biomarker boom slowed by validation concerns. J Natl Cancer Inst. 2004;96:1356–1357 Comment. Realistic assessment of the slowdown in translational science in the cancer field.
129. Abu-Asab MS, Chaouchi M, Alesci S, et al. Biomarkers in the age of omics: time for a systems biology approach. OMICS. 2011;15:105–112.
130. Weigelt B, Reis-Filho JS. Molecular profiling currently offers no more than tumour morphology and basic immunohistochemistry. Breast Cancer Res. 2010;12:S5.
131. Moyer VA, on behalf of the U.S. Preventive Services Task Force. Screening for prostate cancer: U.S Preventive Services Task Force recommendation statement. Ann Intern Med 2011; May 21.
132. Ioannidis JP, Panagiotou OA. Comparison of effect sizes associated with biomarkers reported in highly cited individual articles and in subsequent meta-analyses. JAMA. 2011;305:2200–2210.
133. Shariff SZ, Cuerden MS, Jain AK, Garg AX. The secret of immortal time bias in epidemiologic studies. J Am Soc Nephrol. 2008;19:841–843.
134. Khurana V, Bejjanki HR, Caldito G, Owens MW. Statins reduce the risk of lung cancer in humans: a large case-control study of US veterans. Chest. 2007;131:1282–1288.
135. Jemal A, Murray T, Ward E, et al. Cancer statistics, 2005. CA Cancer J Clin. 2005;55:10–30.
136. Jacobs EJ, Newton CC, Thun MJ, Gapstur SM. Long-term use of cholesterol-lowering drugs and cancer incidence in a large United States cohort. Cancer Res. 2011;71:1763–1771.
137. Suissa S, Dellaniello S, Vahey S, Renoux C. Time-window bias in case-control studies: statins and lung cancer. Epidemiology. 2011;22:228–231.
138. Boyd D. Privacy and publicity in the context of Big Data. Open Government and the World Wide Web (WWW2010). North Carolina: Raleigh; April 29, 2010; Available from: http://www.danah.org/papers/talks/2010/WWW2010.html; April 29, 2010; viewed August 26, 2012.
139. Li W. The more-the-better and the less-the-better. Bioinformatics. 2006;22:2187–2188.
140. Chavez E, Navarro G, Baeza-Yates R, Marroquin JL. Searching in metric spaces. ACM Comput Surveys. 2001;33:273–321.
141. Philippe H, Brinkmann H, Lavrov DV, et al. Resolving difficult phylogenetic questions: why more sequences are not enough. PLoS Biol. 2011;9:e1000602.
142. Bergsten J. A review of long-branch attraction. Cladistics. 2005;21:163–193.
143. Van den Broeck J, Cunningham SA, Eeckels R, Herbst K. Data cleaning: detecting, diagnosing, and editing data abnormalities. PLoS Med. 2005;2:e267.
144. Bickel PJ, Hammel EA, O’Connell JW. Sex bias in graduate admissions: data from Berkeley. Science. 1975;187:398–404.
145. Baker SG, Kramer BS. The transitive fallacy for randomized trials: if A bests B and B bests C in separate trials, is A better than C? BMC Med Res Methodol. 2002;2:13.
146. Tatsioni A, Bonitsis NG, Ioannidis JP. Persistence of contradicted claims in the literature. JAMA 2007;2517–2526.
147. Ye Q, Worman HJ. Primary structure analysis and lamin B and DNA binding of human LBR, an integral protein of the nuclear envelope inner membrane. J Biol Chem. 1994;269:11306–11311.
148. Waterham HR, Koster J, Mooyer P, et al. Autosomal recessive HEM/Greenberg skeletal dysplasia is caused by 3-beta-hydroxysterol delta(14)-reductase deficiency due to mutations in the lamin B receptor gene. Am J Hum Genet. 2003;72:1013–1017.
149. Ecker JR, Bickmore WA, Barroso I, Pritchard JK, Gilad Y, Segal E. Genomics: ENCODE explained. Nature. 2012;489:52–55.
150. Rosen JM, Jordan CT. The increasing complexity of the cancer stem cell paradigm. Science. 2009;324:1670–1673.
151. Mallett S, Royston P, Waters R, Dutton S, Altman DG. Reporting performance of prognostic models in cancer: a review. BMC Med. 2010;30:21.
152. Ioannidis JP. Is molecular profiling ready for use in clinical decision making? Oncologist. 2007;12:301–311.
153. Fifty-six year trends in U.S cancer death rates. Available from: In: SEER Cancer Statistics Review 1975—2005. National Cancer Institute September 19, 2012; http://seer.cancer.gov/csr/1975_2005/results_merged/topic_historical_mort_trends.pdf; September 19, 2012; viewed.
154. Cohen J. The earth is round (p < .05). Am Psychol. 1994;49:997–1003.
155. Rosenberg T. Opinionator: armed with data, fighting more than crime. The New York Times May 2, 2012.
156. Hoover JN. Data, analysis drive Maryland government. Information Week March 15, 2010.
157. Howe J. The rise of crowdsourcing. Wired. 2006;14:06.
158. Robins JM. The control of confounding by intermediate variables. Stat Med. 1989;8:679–701.
159. Robins JM. Correcting for non-compliance in randomized trials using structural nested mean models. Commun Stat Theory Methods. 1994;23:2379–2412.
160. Lohr S. Google to end health records service after it fails to attract users. The New York Times Jun 24, 2011.
161. Schwartz E. Shopping for health software, some doctors get buyer’s remorse. Available from: The Huffington Post Investigative Fund Jan 29, 2010; http://www.huffingtonpost.com/2010/01/29/shopping-for-health-softw_n_442653.html; Jan 29, 2010; viewed January 31, 2013.
162. Heeks R, Mundy D, Salazar A. Why health care information systems succeed or fail. Available from: Institute for Development Policy and Management, University of Manchester June 1999; http://www.sed.manchester.ac.uk/idpm/research/publications/wp/igovernment/igov_wp09htm; June 1999; viewed July 12, 2012.
163. Littlejohns P, Wyatt JC, Garvican L. Evaluating computerised health information systems: hard lessons still to be learnt. Br Med J. 2003;326:860–863.
164. Linder JA, Ma J, Bates DW, Middleton B, Stafford RS. Electronic health record use and the quality of ambulatory care in the United States. Arch Intern Med. 2007;167:1400–1405.
165. Gill JM, Mainous AG, Koopman RJ, et al. Impact of EHR-based clinical decision support on adherence to guidelines for patients on NSAIDs: a randomized controlled trial. Ann Fam Med. 2011;9:22–30.
166. Lohr S. Lessons from Britain’s health information technology fiasco. The New York Times Sept. 27, 2011.
167. Dismantling the NHS national programme for IT. Department of Health Media Centre Press Release September 22, 2011; Available from: http://mediacentre.dh.gov.uk/2011/09/22/dismantling-the-nhs-national-programme-for-it/; September 22, 2011; viewed June 12, 2012.
168. Whittaker Z. UK’s delayed national health IT programme officially scrapped. ZDNet September 22, 2011.
169. Fitzgerald G, Russo NL. The turnaround of the London Ambulance Service Computer-Aided Dispatch system (LASCAD). Eur J Inform Syst. 2005;14:244–257.
170. Kappelman LA, McKeeman R, Lixuan Zhang L. Early warning signs of IT project failure: the dominant dozen. Inform Syst Manag. 2006;23:31–36.
171. Arquilla J. The Pentagon’s biggest boondoggles. The New York Times March 12, 2011.
172. FIPS PUB 119-1. Supersedes FIPS PUB 119. 1985 November 8. Federal Information Processing Standards Publication 119-1 1995 March 13. Announcing the standard for ADA. Available from: http://www.itl.nist.gov/fipspubs/fip119-1.htm; viewed August 26, 2012.
173. Ariane 501 inquiry board report. Available from: http://esamultimedia.esa.int/docs/esa-x-1819eng.pdf; July 19, 1996 viewed August 26, 2012.
174. Mars Climate Orbiter. Mishap Investigation Board. Phase I Report. ftp://ftp.hq.nasa.gov/pub/pao/reports/1999/MCO_report.pdf; November 10, 1999.
175. Sowers AE. Funding research with NIH grants: a losing battle in a flawed system. The Scientist. 1995;9 Oct. 16.
176. Pogson G. Controlled English: enlightenment through constraint. Language Technol. 1988;6:22–25.
177. Schneier B. A plea for simplicity: you can’t secure what you don’t understand. Available from: Information Security November 19, 1999; http://www.schneier.com/essay-018.html; November 19, 1999; viewed September 3, 2012.
178. Vlasic B. Toyota’s slow awakening to a deadly problem. The New York Times February 1, 2010.
179. Valdes-Dapena P. Pedals, drivers blamed for out of control Toyotas. CNN Money February 8, 2011.
180. Drew C. U-2 spy plane evades the day of retirement. The New York Times March 21, 2010.
181. Riley DL. Business models for cost effective use of health information technologies: lessons learned in the CHCS II project. Stud Health Technol Inform. 2003;92:157–165.
182. Leveson NG. A new approach to system safety engineering. 2002; Self-published ebook.
183. Weiss TR. Thief nabs backup data on 365,000 patients. Available from: Computerworld January 26, 2006; http://www.computerworld.com/s/article/108101/Update_Thief_nabs_backup_data_on_365_000_patients; January 26, 2006; viewed August 21, 2012.
184. Noumeir R, Lemay A, Lina J. Pseudonymization of radiology data for research purposes. J Digit Imaging. 2007;20:284–295.
185. The ComputerWorld honors program case study. Available from: http://www.cwhonors.org/case_studies/NationalCancerInstitute.pdf; viewed August 31, 2012.
186. Olavsrud T. How to avoid big data spending pitfalls. Available from: CIO May 08, 2012; http://www.cio.com/article/705922/How_to_Avoid_Big_Data_Spending_Pitfalls; May 08, 2012; viewed July 16, 2012.
187. The Standish Group Report: Chaos. Available from: http://www.projectsmart.co.uk/docs/chaos-report.pdf; 1995 viewed September 19, 2012.
188. Available from: The human genome project race. UC Santa Cruz Center for Biomolecular Science and Engineering March 28, 2009; http://www.cbse.ucsc.edu/research/hgp_race; March 28, 2009.
189. Smith B. caBIG has another fundamental problem: it relies on “incoherent” messaging standard. Cancer Lett. 2011;37.
190. Robinson D, Paul Frosdick P, Briscoe E. HL7 Version 3: an impact assessment. NHS Information Authority 2001; March 23.
191. Eccles M, McColl E, Steen N, et al. Effect of computerised evidence based guidelines on management of asthma and angina in adults in primary care: cluster randomised controlled trial. BMJ. 2002;325 October 26.
192. Self-published paper, published Scheff TJ. Peer review: an iron law of disciplines. Available from: May 27, 2002; http://www.soc.ucsb.edu/faculty/scheff/23.html; May 27, 2002; viewed September 1, 2012.
193. Boyd LB, Hunicke-Smith SP, Stafford GA, et al. The caBIG life science business architecture model. Bioinformatics. 2011;27:1429–1435.
194. Guidelines for ensuring and maximizing the quality, objectivity, utility, and integrity of information disseminated by federal agencies. Fed Reg. 2002;67.
195. Sass JB, Devine Jr JP. The Center for Regulatory Effectiveness invokes the Data Quality Act to reject published studies on atrazine toxicity. Environ Health Perspect. 2004;112:A18.
196. Tozzi JJ, Kelly Jr WG, Slaughter S. Correspondence: data quality act: response from the Center for Regulatory Effectiveness. Environ Health Perspect. 2004;112:A18–A19.
197. Cranor C. Scientific inferences in the laboratory and the law. Am J Public Health. 2005;95:S121–S128.
198. Copyright Act, Section 107, limitations on exclusive rights: fair use. Available from: http://www.copyright.gov/title17/92chap1.html; viewed September 18, 2012.
199. The Digital Millennium Copyright Act of 1998 U.S. Copyright Office Summary. Available from: http://www.copyright.gov/legislation/dmca.pdf; viewed August 24, 2012.
200. No Electronic Theft (NET) Act of 1997 (H.R. 2265). Statement of Marybeth Peters the Register of Copyrights before the Subcommittee on Courts and Intellectual Property Committee on the Judiciary. United States House of Representatives 105th Congress, 1st Session. September 11, 1997. Available from: http://www.copyright.gov/docs/2265_stat.html; viewed August 26, 2012.
201. The Freedom of Information Act. 5 U.S.C. 552. Available from: http://www.nih.gov/icd/od/foia/5usc552.htm; viewed August 26, 2012.
202. Greenbaum D, Gerstein M. A universal legal framework as a prerequisite for database interoperability. Nature Biotechnol. 2003;21:979–982.
203. Perlroth N. Digital data on patients raises risk of breaches. The New York Times December 18, 2011.
204. Frieden T. VA will pay $20 million to settle lawsuit over stolen laptop’s data. CNN January 27, 2009.
205. Mathieson SA. UK government loses data on 25 million Britons: HMRC chairman resigns over lost CDs. ComputerWeekly.com 2007; 20 November 20.
206. Sack K. Patient data posted online in major breach of privacy. The New York Times September 8, 2011.
207. Broad WJ. U.S accidentally releases list of nuclear sites. The New York Times June 3, 2009.
208. Framingham Heart Study. Available from: Clinical Trials.gov October 16, 2012; http://www.clinicaltrials.gov/ct/show/NCT00005121; October 16, 2012; viewed.
209. Appeal from the Superior Court in Maricopa County Cause No. CV2005-013190. Available from: http://www.azcourts.gov/Portals/89/opinionfiles/CV/CV070454.pdf; viewed August 21, 2012.
210. Informed consent and the ethics of DNA research. The New York Times April 23, 2010.
211. Markoff J. Troves of personal data, forbidden to researchers. The New York Times May 21, 2012.
212. Vogel HW. Monatsbericht der Konigl. Academie der Wissenschaften zu Berlin July 10, 1879.
213. Boorse HA, Motz L. The world of the atom. vol. 1 New York: Basic Books; 1966.
214. Harris G. Diabetes drug maker hid test data, files indicate. The New York Times July 12, 2010.
215. Nissen SE, Wolski K. Effect of rosiglitazone on the risk of myocardial infarction and death from cardiovascular causes. N Engl J Med. 2007;356:2457–2471.
216. Meier B. For drug makers, a downside to full disclosure. The New York Times May 23, 2007.
217. Roush W. The Gulf Coast: a victim of global warming? Technol Rev 2005; September 24.
218. McNeil DG. Predicting flu with the aid of (George) Washington. The New York Times May 3, 2009.
219. Khan A. Possible earth-like planets could hold water: scientists cautious. Los Angeles Times November 7, 2012.
220. Sharing publication-related data and materials: responsibilities of authorship in the life sciences. Washington, DC: The National Academies Press; 2003; Available from: http://www.nap.edu/openbook.php?isbn=0309088593; 2003; viewed September 10, 2012.
221. Guidance for sharing of data and resources generated by the molecular libraries screening centers network (mlscn): addendum to rfa rm-04-017. July 22, 2004; NIH notice not-rm-04-014. Available from http://grants.nih.gov/grants/guide/notice-files/NOT-RM-04-014.html; July 22, 2004; viewed September 19, 2012.
222. Berman JJ. De-identification. Available from: Washington, DC: U.S. Office of Civil Rights (HHS), Workshop on the HIPAA Privacy Rule’s De-identification Standard; March 8-9, 2010; http://hhshipaaprivacy.com/assets/4/resources/Panel1_Berman.pdf; March 8-9, 2010; viewed August 24, 2012.
223. National Science Board. Science & Engineering Indicators Arlington, VA: National Science Foundation; 2000; (NSB-00-1).
224. Bossuyt PM, Reitsma JB, Bruns DE, et al. Standards for reporting of diagnostic accuracy The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration. Clin Chem. 2003;49:7–18.
225. Ioannidis JP. Why most published research findings are false. PLoS Med. 2005;2:e124.
226. Ioannidis JP. Some main problems eroding the credibility and relevance of randomized trials. Bull NYU Hosp Jt Dis. 2008;66:135–139.
227. Pueschel M. National outcomes database in development. U.S. Medicine 2000; December.
228. Cook TD, Shadish WR, Wong VC. Three conditions under which experiments and observational studies produce comparable causal estimates: new findings from within-study comparisons. J Policy Analy Manage. 2008;27:724–750.
229. Bornstein D. The dawn of the evidence-based budget. The New York Times May 30, 2012.
230. Ledley RS, Lusted LB. Reasoning foundations of medical diagnosis. Science. 1959;130:9–21.
231. Shortliffe EH. Medical expert systems: knowledge tools for physicians. West J Med. 1986;145:830–839.
232. Heathfield H, Bose D, Kirkham N. Knowledge-based computer system to aid in the histopathological diagnosis of breast disease. J Clin Pathol. 1991;44:502–508.
233. Grady D. Study finds no progress in safety at hospitals. The New York Times November 24, 2010.
234. Goldberg SI, Niemierko A, Turchin A. Analysis of data errors in clinical research databases. AMIA Annu Symp Proc 2008;242–246.
235. Shelby-James TM, Abernethy AP, McAlindon A, Currow DC. Handheld computers for data entry: high tech has its problems too. Trials. 2007;8:5.
236. Berner ES, Graber ML. Overconfidence as a cause of diagnostic error in medicine. Am J Med. 2008;121:S2–S23.
237. Tetlock PE. Expert political judgment: how good is it? How can we know?. Princeton: Princeton University Press; 2005.
238. Thaler RH. The overconfidence problem in forecasting. The New York Times August 21, 2010.
239. Janssens ACJW, vanDuijn CM. Genome-based prediction of common diseases: advances and prospects. Hum Mol Genet. 2008;17:166–173.
240. Michiels S, Koscielny S, Hill C. Prediction of cancer outcome with microarrays: a multiple random validation strategy. The Lancet. 2005;365:488–492.
241. Fifty years of DNA: from double helix to health, a celebration of the genome. National Human Genome Research Institute April, 2003; Available from: http://www.genome.gov/10005139; April, 2003; viewed September 19, 2012.
242. Wade N. Scientist at work: David B Goldstein, a dissenting voice as the genome is sifted to fight disease. The New York Times September 16, 2008.
243. Cohen J. The Human Genome, a decade later. Technol Rev 2011; Jan-Feb.
244. Gisler M, Sornette D, Woodard R. Exuberant innovation: The Human Genome Project. Available from: Cornell University Library Mar 15, 2010; http://arxiv.org/ftp/arxiv/papers/1003/1003.2882.pdf; Mar 15, 2010; viewed September 22, 2012.
245. Anthony S. What can you do with a supercomputer? ExtremeTech 2012; March 15.
246. Dear colleague letter - US ignite: the next steps. National Science Foundation Announcement NSF 12-085, June 12, 2012.
247. Manyika J, Chui M, Brown B, et al. Big data: the next frontier for innovation, competition, and productivity. McKinsey Global Institute 2011; June.
248. Berman JJ. Perl programming for medicine and biology. Sudbury, MA: Jones and Bartlett; 2007.
249. Olson S, Beachy SH, Giammaria CF, Berger AC. Integrating large-scale genomic information into clinical practice: workshop summary. Washington, DC: The National Academies Press; 2012.
250. Orwell G. Tiptree. UK: Signet; 1984; 1950.
251. LaFraniere S. Files vanished, young Chinese lose the future. The New York Times July 27, 2009.
252. Cipra BA. The best of the 20th century: editors name top 10 algorithms. SIAM News. 2000;33.
253. Mell P, Grance T. The NIST definition of cloud computing Recommendations of the National Institute of Standards and Technology. 2011; NIST Publication 800-145NIST September.
254. Paskin N. Identifier interoperability: a report on two recent ISO activities. D-Lib Mag. 2006;12:1–23.
255. Worldwide LHC Computing Grid. Available from: European Organization for Nuclear Research 2008; http://public.web.cern.ch/public/en/lhc/Computing-en.html; 2008; 2008 viewed September 19, 2012.
256. Carpenter JR, Kenward MG. Missing data in randomised control trials: a practical guide. Available from: http://www.hta.nhs.uk/nihrmethodology/reports/1589.pdf; November 21, 2007; viewed June 28, 2011.
257. Berman JJ, Moore GW. Spontaneous regression of residual tumor burden: prediction by Monte Carlo Simulation. Anal Cell Pathol. 1992;4:359–368.
258. McGauran N, Wieseler B, Kreis J, Schuler Y, Kolsch H, Kaiser T. Reporting bias in medical research - a narrative review Trials. 2010;11:37.
259. Dickersin K, Rennie D. Registering clinical trials. JAMA. 2003;290:51.
260. Brin S, Page L. The anatomy of a large-scale hypertextual Web search engine. Comput Networks ISDN Syst. 1998;33:107–117.
261. Stross R. The algorithm didn’t like my essay. The New York Times June 9, 2012.
262. Sawyer R, Berman JJ, Borkowski A, Moore GW. Elevated prostate-specific antigen levels in black men and white men. Mod Pathol. 1996;9:1029–1032.
263. Yank V, Rennie D, Bero LA. Financial ties and concordance between results and conclusions in meta-analyses: retrospective cohort study. BMJ. 2007;335:1202–1205.
264. Mead CN. Data interchange standards in healthcare IT—computable semantic interoperability: now possible but still difficult, do we really need a better mousetrap? J Healthc Inf Manag. 2006;20:71–78.
265. Committee on Mathematical Foundations of Verification, Validation, and Uncertainty QuantificationBoard on Mathematical Sciences and Their Applications, Division on Engineering and Physical Sciences, National Research Council. Assessing the reliability of complex models: mathematical and statistical foundations of verification, validation, and uncertainty quantification. Available from: National Academy Press 2012 January 29, 2013; http://www.nap.edu/catalog.php?record_id=13395; 2012 January 29, 2013; viewed.