Bioinformatics and genomic medicine

Genetics in Medicine

Volumn 4, Issue 6 SUPPL., 2002, Pages

  Kim, Ju Han ^a  

^a BOSTON CHILDREN S HOSPITAL   (United States)

Author keywords

Bioinformatics; DNA microarray; Functional genomics; Genomic medicine; Proteomics

Indexed keywords

ALGORITHM; BIOCHIP; BIOINFORMATICS; CLINICAL PRACTICE; CONFERENCE PAPER; DATA BASE; FILTRATION; FUNCTIONAL GENOMICS; GENE MAPPING; INFORMATION PROCESSING; MEDICAL LITERATURE; MEDICAL RESEARCH; MULTIVARIATE ANALYSIS; PROTEOMICS; BIOLOGY; FORECASTING; GENOMICS; HUMAN; MEDICAL GENETICS; PROTEIN MICROARRAY; REVIEW;

COMPUTATIONAL BIOLOGY; FORECASTING; GENETICS, MEDICAL; GENOMICS; HUMANS; PROTEIN ARRAY ANALYSIS;

EID: 0037676231     PISSN: 10983600     EISSN: None     Source Type: Journal    
DOI: 10.1097/00125817-200211001-00013     Document Type: Conference Paper

References (50)

1. Collen MF. A history of medical informatics in the United States 1950 to 1990. American Medical Informatics Association, 1995.
2. Altman RB. The interactions between clinical informatics and bioinformatics: a case study. J Am Med Inform Assoc 2000;7:439-443.
3. Miller PL. Opportunities at the intersection of bioinformatics and health informatics: a case study. J Am Med Inform Assoc 2000;7:431-438.
4. Rinfleisch TC, Brutlag DL. Directions for clinical research and genomic research into the next decade: implications for informatics. J Am Med Inform Assoc 1998;5:404-411.
5. Altman RB. Bioinformatics in support of molecular medicine. Proc AMIA Symp 1998:53-61.
6. Kohane IS. Bioinformatics and clinical informatics: the imperative to collaborate [editorial comment]. J Am Med Inform Assoc 2000;7:512-515.
7. Schuchhardt J, Beule D, Malik A, Wolski E, Eickhoff H, Lehrach H, Herzel H. Normalization strategies for cDNA microarrays. Nucleic Acids Res 2000;28:E47.
8. Wildsmith SE, Archer GE, Winkley AJ, Lane PW, Bugelski PJ. Maximization of signal derived from cDNA microarrays. Biotechniques 2001;30:202-206, 208.
9. Kepler TB, Crosby L, Morgan KT. Normalization and analysis of DNA microarray data by self-consistency and local regression. Genome Biol 2002;3:RESEARCH0037.
10. Tseng GC, Oh M, Rohlin L, Liao JC, and Wong WH. Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variation and assessment of gene effects. Nucleic Acids Res 2001;29:2549-2557.
11. Yang YH, Dudoit S, Luu P, Speed TP. Normalization for cDNA microarray data. SPIE BiOS 2001, San Jose, CA, January 2001.
12. Tamayo P, Slonim D, Mesirov J, Zhu Q, Kitareewan S, Dmitrovsky E, Lander ES, Golub TR. Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc Natl Acad Sci U S A 1999;96:2907-2912.
13. DeRisi J, Penland L, Brown PO, Bittner ML, Meltzer PS, Ray M, Chen Y, Su YA, Trent JM. Use of a cDNA microarray to analyse gene expression patterns in human cancer. Nat Genet 1996;14:457-460.
14. Heller RA, Schena M, Chai A, Shalon D, Bedilion T, Gilmore J, Woolley DE, Davis RW. Discovery and analysis of inflammatory disease-related genes using cDNA microarrays. Proc Natl Acad Sci U S A 1997;94:2150-2155.
15. Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, Aach J, Ansorge W, Ball CA, Causton HC, Gaasterland T, Glenisson P, Holstege FC, Kim IF, Markowitz V, Matese JC, Parkinson H, Robinson A, Sarkans U, Schulze-Kremer S, Stewart J, Taylor R, Vilo J, Vingron M. Minimum information about a microarray experiment (MIAME): toward standards for microarray data. Nat Genet 2001;29:365-371.
16. Perou CM. Show me the data! Nat Genet 2001;29:373.
17. Hilsenbeck S, Friedrichs W, Schiff R, O'Connell P, Hansen R, Osborne C, Fuqua SW. Statistical analysis of array expression data as applied to the problem of Tamoxifen resistance. J Natl Cancer Inst 1999;91:453-459.
18. Yeung KY, Ruzzo WL. Principal component analysis for clustering gene expression data. Bioinformatics 2001;17:763-774.
19. Shepard RN. Multidimensional scaling, tree-fitting, and clustering. Science 1980;210:390-397.
20. Bittner M, Meltzer P, Chen Y, Jiang Y, Seftor E, Hendrix M, Radmacher M, Simon R, Yakhini Z, Ben-Dor A, Sampas N, Dougherty E, Wang E, Marincola F, Gooden C, Lueders J, Glatfelter A, Pollock P, Carpten J, Gillanders E, Leja D, Dietrich K, Beaudry C, Berens M, Alberts D, Sondak V. Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature 2000;406:536-540.
21. Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A 1998;95:14863-14868.
22. Iyer VR, Eisen MB, Ross DT, Schuler G, Moore T, Lee JCF, Trent JM, Staudt LM, Hudson J Jr, Boguski MS, Lashkari D, Shalon D, Botstein D, Brown PO. The transcriptional program in the response of human fibroblasts to serum. Science 1999;283:83-87.
23. Butte AJ, Kohane IS. Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. Pac Symp Biocomput 2000:418-429.
24. Kohonen T. Self-organized formation of topologically correct feature maps. Biol Cybern 1982;43:59-69.
25. Tavazoie S, Hughes JD, Campbell MJ, Cho RJ, Church GM. Systematic determination of genetic network architecture. Nat Genet 1999;22:281-285.
26. Tamayo P, Slonim D, Mesirov J, Zhu Q, Kitareewan S, Dmitrovsky E, Lander E, Golub TR. Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc Natl Acad Sci U S A 1999;96:2907-2712.
27. Sharan R, Shamir R. CLICK: a clustering algorithm with applications to gene expression analysis. Proc Int Conf Intell Syst Mol Biol 2000;8:307-316.
28. Kim JH, Ohno-Machado L, Kohane IS. Unsupervised learning from complex data: the matrix incision tree algorithm. Pac Symp Biocomput 2001:30-41.
29. Lee K, Kim JH, Chung TS, Moon BS, Lee H, Kohane IS. Evolution strategy applied to global optimization of clusters in gene expression data of DNA microarrays. Proceedings of IEEE Congress on Evolutionary Computation, Seoul, Korea, May 27-30, 2001:845-850.
30. Yeung KY, Fraley C, Murua A, Raftery AE, Ruzzo WL. Model-based clustering and data transformations for gene expression data. Bioinformatics 2001;17:977-987.
31. Yeung KY, Haynor DR, Ruzzo WL. Validating clustering for gene expression data. Bioinformatics 2001;17:309-318.
32. Kim JH, Kohane IS, Ohno-Machado L. Visualization and evaluation of clusters for exploratory analysis of gene expression data. J Biomed Inform. In press.
33. Brown MPS, Grundy WB, Lin D, Christianini N, Sugnet CW, Furgey TS, Haussler D. Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc Natl Acad Sci U S A 2000;97:262-267.
34. Heyer LJ, Kruglyak S, Yooseph S. Exploring expression data: identification and analysis of coexpressed genes. Genome Res 1999;9:1106-1115.
35. Jenssen TK, Laegreid A, Komorowski J, Hovig E. A literature network of human genes for high-throughput analysis of gene expression. Nat Genet 2001;28:21-28.
36. Rebhan M, Chalifa-Caspi V, Prilusky J, Lancet D. GeneCards: a novel functional genomics compendium with automated data mining and query reformulation support. Bioinformatics 1998;14:656-664.
37. Park JC, Kim HS, Kim JJ. Bidirectional incremental parsing for automatic pathway identification with combinatory categorial grammar. Pac Symp Biocomput 2001:396-407.
38. Tavazoie S, Hughes JD, Campbell MJ, Cho RJ, Church GM. Systematic determination of genetic network architecture. Nat Genet 1999;22:281-285.
39. Zhu Z, Pilpel Y, Church GM. Computational identification of transcription factor binding sites via a transcription-factor-centric clustering (TFCC) algorithm. J Mol Biol 2002;318:71-81.
40. Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA, Bloomfield CD, Lander ES. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 1999;286:531-537.
41. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, Boldrick JC, Sabet H, Tran T, Yu X, Powell JI, Yang L, Marti GE, Moore T, Hudson J Jr, Lu L, Lewis DB, Tibshirani R, Sherlock G, Chan WC, Greiner TC, Weisenburger DD, Armitage JO, Warnke R, Staudt LM, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000;403:503-511.
42. Weinstein JN, Myers TG, O'Connor PM, Friend SH, Fornace AJ Jr, Kohn KW, Fojo T, Bates SE, Rubinstein LV, Anderson NL, Buolamwini JK, van Osdol WW, Monks AP, Scudiero DA, Sausville EA, Zaharevitz DW, Bunow B, Viswanadhan VN, Johnson GS, Wittes RE, Paull KD. An information-intensive approach to the molecular pharmacology of cancer. Science 1997;275:343-349.
43. Tomita M. Whole-cell simulation: a grand challenge of the 21st century. Trends Biotechnol 2001;19:205-210.
44. Ideker T, Thorsson V, Ranish JA, Christmas R, Buhler J, Eng JK, Bumgarner R, Goodlett DR, Aebersold R, Hood L. Integrated genomic and proteomic analyses of a systematically perturbed metabolic network. Science 2001;292:929-934.
45. Chicurel M. Databasing the brain. Nature 2000;406:822-825.
46. Brinkley JF. Structural informatics and its applications in medicine and biology. Acad Med 1991;66:589-591.
47. Brown FK. Chemoinformatics: what is it and how does it impact drug discovery? Annu Rep Med Chem 1998;33:375-384.
48. Hann M, Green R. Chemoinformatics: a new name for an old problem. Curr Opin Chem Biol 1999:379-383.
49. Degoulet P, Fischi M. Introduction to clinical informatics. New York: Springer, 1997.
50. Friede A, Blum HL, McDonald M. Public health informatics: how information-age technology can strengthen public health. Annu Rev Public Health 1995;16:239-252.