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Andres Kriete, Ph.D.
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Associate Professor, School of Biomedical Engineering, Science & Health Systems
Office: Bossone 707-B Email: ak3652@drexel.edu
Phone: 215.895.6163
Laboratory Web Page: Click Here to Visit Laboratory Web Page
Research Keywords:
Systems Biology of Aging, Aging Physiome, High-Content Cellular Bioimaging, Multiscale Modeling
Personal News:
Systems biology is an unexploited opportunity to decipher the complexities of aging. We are using genome-wide gene expression analysis, molecular assays and fluorescence microscopy as experimental techniques to investigate mechanisms of cellular aging in humans. We integrate experimental data and novel theoretical concepts by computer simulations of cellular mechanisms to predict functional alterations.
We have recently described a novel stress-response pathway in the physiologically prevailing quiescent state in early-passage fibroblasts from older donors. This stress- and inflammatory profile correlated with an upreguation of the NF-kB transcription factor binding activity. The paper has been published in Immunity and Ageing, 2008.
Our underlying systems biology framework is reviewed in Ageing Research Reviews. An overview of computational approaches in biology is provided in a book on Computational Systems Biology (co-edited with Roland Eils).
Current team (from left): Michael Quien (Protein Interactome - Coriell/Rutgers), Uli Rodeck (Skin Biology - TJU), Glenn Booker (Systems Biology of Aging - Drexel IST & Biomed), Nirupama Yalamanchili-Shah (Cell Assays, Imaging & Systems Modeling - Drexel Biomed), Andres Kriete (PI, Biology of Aging, Systems Biology & Bioimaging, Drexel Biomed), Kelli Mayo (Gene Expression Analysis in Aging - Drexel & UMDNJ), David Boorman (Bioinformatics and Aging - Drexel Biomed), Viraj Shah (Multiscale Modeling - Drexel Biomed), Amitabh Verma (Image Analysis - Drexel Biomed).
Classes I am teaching include (Office hours Wednesday 3-4 pm):
Biomedical Imaging Systems I + III (BMES 421/621 + 423/623) - Image acquisition in biomedicine, fluorescence and confocal microscopy, detectors, systems theory, image segmentation & analysis, object-oriented approaches, image compression, 3D visualization, deconvolution.
Biosystems Modeling/Computational Systems Biology (BMES 545) - This course provides computational methods used in systems biology: pathway and circuitry, feedback and control, cellular automata, sets of partial differential equations, stochastic analysis and biostatistics. Investigation of signaling networks and multiscale modeling, tools and methods are also included.
Pharmacogenomics/Pharmacology (BMES 604) - A major industrial application of bioinformatics and increasingly systems biology is in pharmacogenomics. The course includes topics in drug target development, screening, genotyping, SNPs, protein docking, toxicology and personalized medicine.
Experimental Design and Biostatistics (BMES 315/515) - Experimental design, power analysis, advanced statistical techniques, regulated studies, applications in image analysis and bioinformatics.
Summer teaching activity:
Int. Course on 3D Microscopy of Living Cells, Vancouver
Conferences:
Since 1988 I am involved in organizing an international conference series on modern microscopy Focus on Microscopy . The next meeting will be held in March 2010 in Shanghai.
In 2007, I organized a workshop on the Biology of Aging at the Santa Fe Institute, NM entitled Complexities of Aging in Biological Systems .
Related 2009 meetings include a Systems Biology of Human Aging workshop at NIH.
Active Research Projects:
1) Our research on the biology of aging is focussed on an integrated experimental and computational approach to develop a model for cellular aging. This work is conducted in collaboration with Uli Rodeck (Thomas Jefferson University), William Bosl (Harvard Medical School) and in affiliation with the Monell Chemical Senses Center in Philadelphia (aging of olfactory neurons).
2) Modeling on the physiome level includes a lung modeling project as part of the multiscale modeling initiative IMAG at NIH-NIBIB together with Penn State University. Our multiscale lung model LungSim is available from the SimTK modeling repository at Stanford University.
3) We are implementing novel computational frameworks to study spatio-temporal processes and interactions on multiscales, from cells to organs, from intracellular processes to physiology. Long term goal of this research is to provide insights into aging related mechanisms, sensitivity and robustness at different levels of biological organization, scaling properties, emerging aging phenotypes in tissues including skin, lung and sensory receptor epithelia.
Publications:
Kriete A, Mayo KL. Atypical mechanisms of NF-kB activation and aging. Experimental Gerontology, 2009 Apr 44(4):250-255
Kriete A, Mayo KL, Yalamanchili N, Beggs W, Bender P, et al. Cell Autonomous Expression of inflammatory genes in biologically aged fibroblasts associated with elevated NF-kappaB activity. Immun Ageing. 2008 Jul 16;5:5.
Kelder B, Boyce K, Kriete A, Clark R, Berryman DE, Nagatomi S, List EO, Braughler M, Kopchick JJ. CIDE-A is expressed in liver of old mice and in type 2 diabetic mouse liver exhibiting steatosis. Comp Hepatol. 2007 May 1;6:4.
Kriete A, Papazoglou E, Edrissi B, Pais H, Pourrezaei K.Automated quantification of quantum-dot-labelled epidermal growth factor receptor internalization via multiscale image segmentation.J Microsc. 2006 Apr;222(Pt 1):22-7.
Kriete A, Sokhansanj BA, Coppock DL, West GB. Systems approaches to the networks of aging. Ageing Res Rev. 2006, 5(4), 434-448.
Kriete A. Biomarkers of aging: combinatorial or systems model? Science, Sci Aging Knowledge Environ. 2006 Jan 4; 2006(1):pe1.
Yalamanchili N, Zak DE, Ogunnaike BA, Schwaber JS, Kriete A, Kholodenko BN. Quantifying gene network connectivity in silico: scalability and accuracy of a modular approach. Syst Biol (Stevenage) 2006 Jul, 153(4):236-46.
Kriete A. Bridging biological scales by state-space analysis using molecular, tissue cytometric and physiological data. Cytometry A. 2006, 69A(3):113-116.
Boyce K, Kriete A, Nagatomi S, Kelder B, Coschigano K, Kopchick J. Gene enrichment of microarray data guided by tissue phenotypic co-variants in a Type II Diabetes study. OMICS 2005, 9(3): 252-266
Kriete A, Boyce K. Automated tissue analysis - a bioinformatics perspective. Methods Inf Med 2005, 44(1):32-7.
Weber, R.; Proctor, J.M.; Waldstein, I.; Kriete A. (2005) Case-base reasoning for modeling complex systems. In Muoz-Avila, H., and Ricci, F. (Eds.) Case-Based Reasoning Research Development. Lecture Notes Computer Science 3620, Springer, pp. 625-639
Kriete A, Anderson MK, Love B, Freund J, Caffrey JJ, Young MB, Sendera TJ, Magnuson SR, Braughler JM. Combined histomorphometric and gene-expression profiling applied to toxicology. Genome Biol. 2003, 4(5):R32. Epub
Young MB, DiSilvestro MR, Sendera TJ, Freund J, Kriete A, Magnuson SR. Analysis of gene expression in carbon tetrachloride-treated rat livers using a novel bioarray technology. Pharmacogenomics J. 2003, 3(1):41-52.
Kriete A, Naim M, Schafer L. Quality measures in applications of image restoration. Scanning. 2001 Sep-Oct; 23(5):313-9.
Kriete A, Schwebel T. 3-D TOP-A software package for the topological analysis of image sequences. J Struct Biol 1996, 116(1):150-4.
Kriete A, Wagner HJ. A method for spatio-temporal (4-D) data representation in confocal microscopy: application to neuroanatomical plasticity. J Microscopy 1993, 169:27-31.
Masters B., Kriete A, Kukulies J. Ultraviolet confocal fluorescence microscopy of the in-vitro cornea: redox metabolic imaging. Applied Optics 1992 32(4):592-596.
Montag M, Spring H, Trendelenburg, MF, Kriete A. Methodical aspects of 3-D reconstruction of chromatin architecture in mouse trophoblast giant nuclei, J. of Microscopy 1990, 158(2):225-233
Kriete A, Schäffer R, Harms H, Aus HM. Computer based cytophotometry analysis of thyroid tumors in imprint. J Cancer Res Clin Oncol 1985, 109: 252-256
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