Skip to main content

Biomedical Informatics for Cancer Research: Introduction

  • Chapter
  • First Online:
Biomedical Informatics for Cancer Research

Abstract

Biomedical informatics encompasses a set of disciplines focused on developing, implementing, and perfecting the use of informatics and computational tools in biomedical research and clinical care. In this volume, we focus on a number of areas crucial to the establishment of state-of-the-art informatics methods and systems to support cancer research. We provide motivation for undertaking such developments and deployments, a quick overview of the field, and hopes for the impact on cancer treatment and survival in this introduction.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Ambite JL, Knoblock CA, Muslea I, Philpot A (2001) Compiling source descriptions for efficient and flexible information integration. J Intell Inf Syst 16(2):149–187

    Article  Google Scholar 

  • Baggerly KA, Morris JS, Coombes KR (2004) Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments. Bioinformatics 20:777–785

    Article  PubMed  CAS  Google Scholar 

  • Baggerly KA, Morris JS, Edmonson SR et al (2005) Signal in noise: evaluating reported reproducibility of serum proteomic tests for ovarian cancer. J Natl Cancer Inst 97:307–309

    Article  PubMed  CAS  Google Scholar 

  • Berry DA, Iversen ES Jr, Gudbjartsson DF et al (2002) BRCAPRO validation, sensitivity of genetic testing of brca1/brca2, and prevalence of other breast cancer susceptibility genes. J Clin Oncol 20:2701–2712

    Article  PubMed  CAS  Google Scholar 

  • Carter H, Chen S, Isik L et al (2009) Cancer-specific high-throughput annotation of somatic mutations: Computational prediction of driver missense mutations. Cancer Res 69:6660

    Article  PubMed  CAS  Google Scholar 

  • Cho KR, Vogelstein B (1992) Genetic alterations in the adenoma–carcinoma sequence. Cancer 70:1727–1731

    Article  PubMed  CAS  Google Scholar 

  • Collen MF (1991) A brief historical overview of hospital information system (HIS) evolution in the United States. Int J Biomed Comput 29:169–189

    Article  PubMed  CAS  Google Scholar 

  • Coombes KR, Wang J, Baggerly KA (2007) Microarrays: retracing steps. Nat Med 13:1276–1277

    Article  PubMed  CAS  Google Scholar 

  • Druker B (2001) Signal transduction inhibition: results from phase I clinical trials in chronic myeloid leukemia. Semin Hematol 38:9–14

    Article  PubMed  CAS  Google Scholar 

  • Edgar R, Domrachev M, Lash AE (2002) Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30:207–210

    Article  PubMed  CAS  Google Scholar 

  • Enterline JP, Lenhard RE, Blum BI et al (1994) OCIS: 15 years experience with patient-centered computing. MD Comput 11:83–91

    Article  PubMed  CAS  Google Scholar 

  • Favaro JP, George DJ (2005) Targeted therapy in renal cell carcinoma. Expert Opin Invest Drugs 14:1251–1258

    Article  CAS  Google Scholar 

  • Geissbuhler A (2003) Building man-man-machine synergies. Experiences from the Vanderbilt and Geneva clinical information systems. Int J Med Informatics 69:127–133

    Article  CAS  Google Scholar 

  • Hammond WE, Stead WW et al (1980) Functional characterisitics of a omputerized medical record. Methods Inf Med 19:157–162

    Article  CAS  Google Scholar 

  • Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100:57–70

    Article  CAS  Google Scholar 

  • Humphreys BL, Lindberg DA (1993) The UMLS project: making the conceptual connection between users and the information they need. Bull Med Libr Assoc 81:170–177

    PubMed  CAS  Google Scholar 

  • Irizarry RA, Bolstad BM, Collin F et al (2003) Summaries of affymetrix genechip probe level data. Nucleic Acids Res 31:e15

    Article  PubMed  Google Scholar 

  • Katz S, Irizarry RA, Lin X et al (2006) A summarization approach for affymetrix genechip data using a reference training set from a large, biologically diverse database. BMC Bioinformatics 7:464

    Article  PubMed  Google Scholar 

  • Kerr MK, Afshari CA, Bennett L et al (2002) Statistical analysis of a gene expression microarray experiment with replication. Stat Sin 12:203–218

    Google Scholar 

  • Lin J, Gan CM, Zhang X et al (2007) A multidimensional analysis of genes mutated in breast and colorectal cancers. Genome Res 17:1304–1318

    Article  PubMed  CAS  Google Scholar 

  • Lukashin AV, Fuchs R (2001) Analysis of temporal gene expression profiles: clustering by simulated annealing and determining the optimal number of clusters. Bioinformatics 17:405–414

    Article  PubMed  CAS  Google Scholar 

  • Maglott D, Ostell J, Pruitt KD et al (2007) Entrez gene: gene-centered information at NCBI. Nucleic Acids Res 35:D26–D31

    Article  PubMed  CAS  Google Scholar 

  • Miller SJ (2000) The national comprehensive cancer network (NCCN) guidelines of care for nonmelanoma skin cancers. Dermatol Surg 26:289–292

    Article  PubMed  CAS  Google Scholar 

  • Moloshok TD, Klevecz RR, Grant JD et al (2002) Application of Bayesian decomposition for analysing microarray data. Bioinformatics 18:566–575

    Article  PubMed  CAS  Google Scholar 

  • Parkinson H, Sarkans U, Shojatalab M et al (2005) Arrayexpress – a public repository for microarray gene expression data at the EBI. Nucleic Acids Res 33:D553–D555

    Article  PubMed  CAS  Google Scholar 

  • Parmigiani G, Berry D, Aguilar O (1998) Determining carrier probabilities for breast cancer-susceptibility genes BRCA1 and BRCA2. Am J Hum Genet 62:145–158

    Article  PubMed  CAS  Google Scholar 

  • Parsons DW, Jones S, Zhang X et al (2008) An integrated genomic analysis of human glioblastoma multiforme. Science 321:1807–1812

    Article  PubMed  CAS  Google Scholar 

  • Rada R, Finley S (2004) The aging of a clinical information system. J Biomed Informatics 37: 319–324

    Article  PubMed  CAS  Google Scholar 

  • Rubin DL, Lewis SE, Mungall CJ et al (2006) National center for biomedical ontology: advancing biomedicine through structured organization of scientific knowledge. OMICS 10:185–198

    Article  PubMed  CAS  Google Scholar 

  • Sackett DL, Rosenberg WMC et al (1996) Evidence based medicine: what it is and what it isn’t. BMJ 312:71–72

    Article  PubMed  CAS  Google Scholar 

  • Shojania KJ and Grimshaw JM (2005) Evidence-Based Quality Improvement: The State of the Science. Health Affairs 24(1):138–150

    Article  PubMed  CAS  Google Scholar 

  • Shortell SM, Rundall TG et al (2007) Improving Patient Care by Linking Evidence-Based Medicine and Evidence-Based Management. JAMA 298(6):673–676

    Article  PubMed  CAS  Google Scholar 

  • Strogatz SH (2001) Exploring complex networks. Nature 410:268–276

    Article  PubMed  CAS  Google Scholar 

  • Szyperski C (1997) Component Software, 1st Edition. ACM, New York

    Article  PubMed  CAS  Google Scholar 

  • The Cancer Genome Atlas Research Network (2008) Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 455:1061–1068

    Article  Google Scholar 

  • Thorisson GA, Stein LD (2003) The SNP consortium website: past, present and future. Nucleic Acids Res 31:124–127

    Article  PubMed  CAS  Google Scholar 

  • Ventura AC, Jackson TL, Merajver SD (2009) On the role of cell signaling models in cancer research. Cancer Res 69:400–402

    Article  PubMed  CAS  Google Scholar 

  • Wilt TJ, Bloomfield HE, Macdonald R et al (2004) Effectiveness of statin therapy in adults with coronary heart disease. Arch Intern Med 164:1427–1436

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Michael F. Ochs .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

Ochs, M.F., Casagrande, J.T., Davuluri, R.V. (2010). Biomedical Informatics for Cancer Research: Introduction. In: Ochs, M., Casagrande, J., Davuluri, R. (eds) Biomedical Informatics for Cancer Research. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-5714-6_1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4419-5714-6_1

  • Published:

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-5712-2

  • Online ISBN: 978-1-4419-5714-6

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics