Michael Bittner

Michael Bittner Ph.D.

Professor and Co-Director
Computational Biology Division

Head
Measurement & Inference Lab

Michael Bittner Ph.D.

Biologists' increasing abilities to make simultaneous measurements of the abundance, linear structure, or modification level of many members of a particular class of bio-molecules (DNA, RNA, and protein) in cells or tissues have produced a tremendous increase in the resolution at which cellular activities can be viewed, and as a result, an intriguing set of new analytic problems. How can we use such information to discern what cellular processes are active in a given sample? Can the differences in such survey data be used to distinguish healthy tissues from diseased ones, or to differentiate types of diseases such as cancer into subgroups based on molecular typing for the purposes of prognosis or treatment decisions?

The first measurement technology to allow broad measurement of one of the cell's dynamically regulated systems was the use of microarray systems to survey the relative abundance of mRNA transcripts present in a cell. The laboratory has spent much effort over the last six years in increasing the precision and accuracy of such measurements, and establishing objective measures of the quality of each of the individual measurements in these large series of measurements. Simultaneously, many approaches to use these well-characterized measurements to gain insight into the molecular processes of healthy and diseased cells have been developed in collaborations with a variety of signal processing engineers, mathematicians, logicians and statisticians worldwide. The earliest methods were based predominantly on the most simple mathematical approaches, correlation and distributional tests. These allowed the classification of tissue samples on the basis of their similarity, and then the determination of the genes most differential between the sample sets, leading to useful tumor classification methods and providing insight into how the process of altering the regulation of the very diverse set of genes that must have their activity levels changed as a cancer cell becomes actively metastatic can be triggered.

In the course of these studies it became apparent that though such tools are quite good at looking for alterations that can largely be explained by a very simple cause, they do not provide much insight into the mechanics of gene regulation or into processes that are controlled by the interactions of many genes. A variety of analytic methods that are capable of recognizing multi-gene interactions that may contribute to phenotypic changes have been developed. Such methods typically require much more computational power and have resulted in an ongoing collaboration with the current members of TGen's High Performance Computing team. Two themes have developed from this work. One is that it is important to consider a given cellular expression state in a cell or tissue as a context within which to interpret possible patterns of interaction. This is very commonsensical, since many of the gene products present in a cell regulate the current level of transcriptional activity of the genome. The second major theme is that to deduce information about regulation in the complex control system that operates in the cell, it is important to devise analyses based on models of the operation of that system. This too makes sense, if the regulatory role of a gene presents in ways that are both quantitatively and qualitatively different when this gene is simultaneously present with another gene, then methods that cannot account for this contingency will not detect this form of information. Developing analytic tools that are able to detect gene interactions that contribute to phenotypic regulation and developing new measurement systems to allow rapid validation of the inferred regulatory relationships will be the central areas of the lab's research.

  • Chen, Y., Dougherty, E.R., Bittner, M.L.., Ratio-based decisions and the quantitative analysis of cDNA microarray images J. Biomedical Optics 2, 364-374 1997
  • Duggan, D., Bittner, M., Chen, Y., Meltzer, P., and Trent, J.M.. , Expression profiling using cDNA microarrays. Nature Genetics 21, 10-14 1999
  • Kim, S., Dougherty, E.R., Chen, Y., Sivakumar, K., Meltzer, P., Trent, J.M., Bittner, M.L.. , Multivariate measurement of gene expression relationships. Genomics 67(2), 201-9 2000
  • Bittner, M., Meltzer, P., Chen, Y., Jiang, Y., Seftor, M., Hendrix, M., Radmacher, R., Simon, R., Yakhini, Z., Ben-Dor, A., Sampas, N., Dougherty, E. R., Wang, E., Marincola, F., Gooden, G., Lueders, J., Glatfelter, A., Pollock, P., Carpten, J., Gillanders, E., Leja, D., Dietrich, K., Beaudry, C., Berens, M., Alberts, D., Sondak, V., Hayward, N., Trent, J. M.. , Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature 406, 536-540 2000
  • Loftus, S. K., D. M. Larson, L. L. Baxter, A. Antonellis, Y. Chen, X. Wu, Y. Jiang, M. Bittner, J. A. Hammer, 3rd and W. J. Pavan., Mutation of melanosome protein RAB38 in chocolate mice Proc Natl Acad Sci U S A 99(7): 4471-6 2002
  • Chen, Y., Kamat, V., Dougherty, E. R., Bittner, M.L., Meltzer, P.S., Trent, J.M.., Ratio statistics of gene expression levels and applications to microarray data analysis Bioinformatics 18(9), 1207-1215 2002
  • Weeraratna, A., Jiang, Y., Hostetter, G., Rosenblatt, K., Duray, P., Bittner, M., Trent, J.M.., Wnt5a signaling directly affects cell motility and invasion of metastatic melanoma Cancer Cell 1(3), 279-288 2002
  • Hashimoto Ronaldo F., Dougherty Edward R., Brun Marcel, Zhou Z., Bittner Michael L., Trent Jeffrey M.., Efficient Selection of Feature Sets Possessing High Coefficients of Determination Based on Incremental Determinations. Signal Processing Vol. 83 (4), pp. 695-712. 2003
  • Amundson, S.A., R.A. Lee, C.A. Koch-Paiz, M.L. Bittner, P. Meltzer, J.M. Trent, and A.J. Fornace, Jr.., Differential Responses of Stress Genes to Low Dose-Rate gamma Irradiation Mol Cancer Res. 1(6): p. 445-52 2003
  • Zhou, X., Wang, X., Pal, R., Ivanov, I., Bittner, M. L., and E. R. Dougherty., A Bayesian Connectivity-Based Approach to Constructing Probabilistic Gene Regulatory Networks Bioinformatics Vol. 20. No. 17. 2004
  • R. F. Hashimoto, S. Kim, I. Shmulevich, W. Zhang, M. L. Bittner, E. R. Dougherty.., A Directed-Graph Algorithm to Grow Genetic Regulatory Subnetworks from Seed Genes Based on Strength of Connection Bioinformatics 20 (8): 1241-1247 2004
  • Amundson, S.A., K.T. Do, L. Vinikoor, C.A. Koch-Paiz, M.L. Bittner, J.M. Trent, P. Meltzer, and A.J. Fornace, Jr.., Stress-specific signatures: expression profiling of p53 wild-type and -null human cells. Oncogene 24(28): p. 4572-9 2005
  • Pal, R., Datta, A., Bittner, M. L., and E. R. Dougherty. , Intervention in Context-Sensitive Probabilistic Boolean Networks. Bioinformatics 24(28): p. 4572-9. 2005
  • Pal, R., A. Datta, A.J. Fornace, Jr., M.L. Bittner, and E.R. Dougherty. , Boolean relationships among genes responsive to ionizing radiation in the NCI 60 ACDS. Bioinformatics 21(8): p. 1542-9 2005
  • Carpten JD, Faber AL, Horn C, Donoho GP, Briggs SL, Robbins CM, Hostetter G, Boguslawski S, Moses TY, Savage S, Uhlik M, Lin A, Du J, Qian YW, Zeckner DJ, Tucker-Kellogg G, Touchman J, Patel K, Mousses S, Bittner M, Schevitz R, Lai MH, Blanchard KL, Thomas JE., A transforming mutation in the pleckstrin homology domain of AKT1 in cancer. Nature 26; 448(7152):439-44. 2007
  • Salvatore, G., T. C. Nappi, P. Salerno, Y. Jiang, C. Garbi, C. Ugolini, P. Miccoli, F. Basolo, M. D. Castellone, A. M. Cirafici, R. M. Melillo, A. Fusco, M. L. Bittner and M. Santoro., A cell proliferation and chromosomal instability signature in anaplastic thyroid carcinoma. Cance Res 67(21): 10148-58 2007
  • Kim, S., I. Sen and M. Bittner., Mining molecular contexts of cancer via in-silico conditioning. Comput Syst Bioinformatics Conf, 6: 169-79 2007
  • Martins, D. C., U. M. Braga-Neto, R. F. Hashimoto, M. L. Bittner and E. R. Dougherty., Intrinsically Multivariate Predictive Genes. IEEE Journal of Signal Processing 2(3): 424-439. 2008
  • Amundson SA, Do KT, Vinikoor LC, Lee RA, Koch-Paiz CA, Ahn J, Reimers M, Chen Y, Scudiero DA, Weinstein JN, Trent JM, Bittner ML, Meltzer PS, Fornace AJ Jr., Integrating global gene expression and radiation survival parameters across the 60 cell lines of the National Cancer Institute Anticancer Drug Screen Cancer Res 68(2):415-24 2008
  • Dougherty ER, Brun M, Trent JM, Bittner ML. , Conditioning-based modeling of contextual genomic regulation. IEEE/ACM Trans Comput Biol Bioinform 6(2):310-20 2009
  • Hostetter G, Kim S, Savage S, Gooden G, Alla L, Barrett M, Zhang J, Watanabe A, Einspahr J, Alberts D, Prasad A, Nickoloff B, Carpten J, Trent J, Bittner M., Random DNA fragmentation allows detection of single-copy, single-exon alterations of copy number by oligonucleotide array CGH in clinical FFPE samples. Nucleic Acids Res Feb;38(2):e9. 2010
  • Mousses, S., Wagner, U., Chen, Y., Kim, J.W., Bubendorf, L., Bittner, M., Pretlow, T., Elkahloun, A.G., Trepel, J., Kallioniemi O-P., Failure of hormone therapy in prostate cancer involves systematic restoration of androgen responsive genes and activation of rapamycin sensitive signaling. Oncogene 20(46),6718-23 2001
  • Monni, O., Bärlund, M., Mousses, S., Kononen, K., Sauter, G., Heiskanen, M., Paavola, P., Avela, K., Chen, Y., Bittner, M.L., & Kallioniemi, A.. , Comprehensive copy number and gene expression profiling of the 17q23 amplicon in human breast cancer. PNAS 98(10),5711-5716 2001
  • Suh, E., Russ, D., Dougherty, E., Kim, S., Bittner, M.L., Chen, Y., Martino, R.., Parallel Computation for Coefficients of Determination in the Context of Multivariate Gene-Expression Analysis. International Journal of Computer Research Nova Science Books and Journals 2003
  • Kim, S., Li, H., Dougherty, E.R., Cao, N., Chen, Y., Bittner, M.L., Suh, E. B.. , Can Markov Chain Mimic Biological Regulation? ournal of Biological Systems 10(4), 337-358. 2002
  • Ermolaeva O., Rastogi M., Pruitt K.D., Schuler G.D., Bittner M.L., Chen Y., Simon R., Meltzer P., Trent J .M., Boguski M.S.. , Data management and analysis for gene expression arrays. Nat Genet 20(1), 19-23 1998
  • Khan J., Simon R., Bittner M., Chen Y., Leighton S.B., Pohida T., Smith P.D., Jiang Y., Gooden G.C., Trent J .M., Meltzer P.S.., Gene expression profiling of alveolar rhabdomyosarcoma with cDNA microarrays. Cancer Res 15;58(22), 5009-13 1998
  • DeRisi J., Penland L., Brown P.O., Bittner M.L., Meltzer P.S., Ray M., Chen Y., Su Y.A., Trent J .M.., Use of cDNA microarray to analyse gene expression patterns in human cancer. Nat Genet 14(4), 457-460 1996
  • Hedenfalk, I., Duggan, D., Chen, Y., Radmacher, M., Bittner, M., Simon, R., Meltzer, P., Gusterson, B., Esteller, M., Kallioniemi, O., Wilfond, B., Borg, A., and Trent, J.., Gene expression profiles in hereditary breast cancer N. Engl. J. Med. 344, 539-48 2001
  • Luo, J., Duggan, D., Chen, Y., Sauvageot, J., Ewing, C., Bittner, M., Trent, J.M., and Isaacs, W.B.., Human Prostate Cancer and Benign Prostatic Hyperplasia: Molecular Dissection by Gene Expression Profiling Cancer Research 61, 4683-4688 2001
  • Sen, I., Verdicchio, M., Jung, S., Trevino, R., Bittner, M. and Kim, S. , Context-Specific Gene Regulations in Cancer Gene Expression Data. Pacific Symposium on Biocomputing, Jan 5-9, 2009, Big Island, Hawaii, US. 2009
  • Hashimoto, R.F., Kim, S., Shmulevich, I., Zhang, W., Bittner, M.L. and Dougherty, E.R., Growing genetic regulatory networks from seed genes. Bioinformatics, 20, 1241-1247. 2004
  • R. Bomprezzi, M. Ringnér, S. Kim, M. Bittner, J. Khan, Y. Chen, A. Elkahloun1, A. Yu, B. Bielekova, P. Meltzer, R. Martin, H. McFarland, J. Trent.., Gene Expression Profiling in Multiple Sclerosis Distinguishes Patients From Healthy Controls. Human Molecular Genetics 12(17): 2191-99 2003
  • Kim, S., Dougherty, E.R., Barrera, J., Chen, Y., Bittner, M. L., Trent, J.M.. , Strong Feature Sets from Small Samples. Journal of Computational Biology 9(1), 127-146. 2002
  • Sekulic A, Kim SY, Hostetter G, Savage S, Einspahr JG, Prasad A, Sagerman P, Curiel-Lewandrowski C, Krouse R, Bowden T, Warneke J, Alberts DS, Pittelkow MR, DiCaudo D, Nickoloff BJ, Trent JM, Bittner M, Loss of Inositol Polyphosphate 5-Phosphatase Is an Early Event in Development of Cutaneous Squamous Cell Carcinoma. Cancer Prev Res 3(10); 1277-83 2010
  • Weeraratna, A., Jiang, Y., Hostetter, G., Rosenblatt, K., Duray, P., Bittner, M., Trent, J.M.., Wnt5a signaling directly affects cell motility and invasion of metastatic melanoma. Cancer Cell, 1(3), 279-288. 2002
  • B. Hanczar, J. Hua, C. Sima, J. Weinstein, M. Bittner, and E. R. Dougherty. , Small-sample precision of roc-related estimates Bioinformatics vol. 26(6), 822-830 2010
  • Q. Xu, J. Hua, Z. Xiong, M.L. Bittner, and E. R. Dougherty. , The Effect of Microarray Image Compression on Expression-Based Classification. Signal, Image and Video Processing doi: 10.1007/s11760-008-0059-2, 2008
  • E.R. Dougherty, J. Hua, and M.L. Bittner., Validation of computational methods in genomics. Current Genomics vol. 8, 1-19. 2007
  • J. Hua, Y. Balagurunathan, Y. Chen, J. Lowey, M.L. Bittner, Z. Xiong, E. Suh, and E.R. Dougherty., Normalization benefits microarray-based classification. EURASIP Journal on Bioinformatics and Systems Biology, vol. 2006 2006
  • Sekulic A, Bittner M, Bruhn L, Pittelkow M, Trent J, Identification of growth-promoting networks differentially activated in CDKN2A wild-type melanoma tumors J Invest Dermatol 128(Suppl 1):S226. 2008
  • Khan, J., Bittner, M.L., Saal, L.H., Teichmann, U., Azorsa, D.O., Gooden, G.C., Pavan, W.P., Trent, J.M., and Meltzer, P.S.., cDNA microarrays detect activation of a myogenic transcription program by the PAX3-FKHR fusion oncogene. Proc Natl Acad Sci U S A 96:13264-13269 1999
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