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BIOMED Faculty Details: Andres Kriete, Ph.D.
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Andres Kriete, Ph.D.   [Details
Associate Director for Graduate Studies and Academic Operations, School of Biomedical Engineering, Science & Health Systems
Office: Bossone 718-B  Email:
Phone: 215.895.6163
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Research Keywords:
Systems Biology of Aging, Robustness, Control Theory, Aging Physiome, Evolutionary Theories, Skin Cancer, Bioimaging
Personal News:
The systems biology of aging is an emerging endeavor taking an integrative view of a biological process that disturbs a broad range of cellular and physiological functions in a complex and global fashion. We explore concepts from engineering (complex systems, robustness, control theory) to decipher the biology of aging at the intersection of experimental, computational and theoretical biology. We investigate cellular regulation in skin fibroblasts from donors of different age, as well as skin cancer tissues and cell lines in collaboration with our clinical partners.

We have suggested that aging is a robustness tradeoff of complex evolutionary systems (BioSystems, 2013), which provides evolutionary theories of aging with an engineering-oriented view. In a contribution for PLOS Computational Biology we described how feedback loop motifs from control theory in conjunction with rule-based descriptors can be used to assemble generic whole cell models predicting the progression of aging. The approach demonstrates the interaction of ongoing damage, stress response and adaptive-regulatory mechanisms. These models can be executed rapidly and repeatedly to study the effect of molecular mechanisms on the aging phenotype [see also corresponding Press Release on 'Fuzzy Logic predicts Aging'].

Systems Biology of Aging Conferences:
In 2007 a first workshop on the Systems Biology of Aging was held at the Santa Fe Institute, NM, entitled Complexities of Aging in Biological Systems. Subsequent 2008 and 2009 meetings promoting systems approaches in aging included seminars held at ASU and NIH-NIA under the title of "Systems Biology in Human Aging", which was continued as SBHA-2010 in Philadelphia.
Andres Kriete has received training in computational biology in academic, clinical and industrial environments. He joined Drexel University in 2003 and currently is Associate Director of Graduate Studies and Academic Operations at the School of Biomedical Engineering, Science and Health Systems.
Active Research Projects:
1) Cell Aging. Nirupama Yalamanchili (Drexel Biomed), Kelli Mayo Danowski (UMDNJ/Univ. of Michigan, Ann Arbor), Uli Rodeck (Thomas Jefferson University). We are investigating cells from donors of different age by genome-wide gene expression analysis, molecular assays and fluorescence microscopy. We have described a cell-autonomous stress response pathway in the physiologically prevailing quiescent state in skin fibroblasts aged in-vivo. This stress- and inflammatory profile correlated with an upregulation of the NF-kB transcription factor binding activity (see our publication in Immunity and Ageing, 2008). In collaboration with the Monell Chemical Senses Center we participate in the investigation of aging in olfactory neurons.
2) Skin Cancer. Chetana Sunkari (Drexel Biomed), David Alfego (Drexel Biomed), Boaz Tirosh (Hebrew University) and Jouni Uitto (Thomas Jefferson University). We study photoaging as a risk factor for skin cancer with a diagnostic and therapeutic perspective.
3) Computational Modeling. Glenn Booker (Drexel IST), Drew Clearfield (Drexel Biomed), William Bosl (Harvard Medical School). We collaborate on the fuzzy-logic software Bionet, deposited at the SimTK modeling repository at Stanford University.
A physiome lung project as part of the multiscale modeling initiative IMAG at NIH-NIBIB has been developed together with Penn State University. The model LungSim is available for download from SimTK.
4) Aging Pathways. Visish Srinivasan (Drexel College of Medicine/Baylor College), Michal Jazwinski (Tulane Univ.), Dirk Bohmann (Univ. of Rochester). We investigate pathways that are conserved, from yeast to humans.
5) Aging Initiative at Drexel: Collaborators are Christian Sell and Eishi Noguchi (Drexel College of Medicine).

Related courses:
Biosimulation (BMES 372) and Principles of Biological Systems Analysis (BMES 511) - These courses provide conceptual, mathematical and computational methods to analyze and simulate complex biological systems. Systems biology applications include: pathway and circuitry, feedback and control, cellular automata, ODE/PDE and stochastic analysis. 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 covers drug target development, screening, genotyping, SNPs, protein docking, toxicology and personalized medicine.

Biostatistics, Bioinformatics and Experimental Design (BMES 310/510 and 315/515) - This sequence introduces biostatistical analysis fundamental applied to bioinformatics, genomics, and cell biology. Topics include data analysis, hypothesis testing, power analysis, advanced statistical techniques, clustering, genotype-phenotype correlations, experimental designs, regulated studies, and applications.

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 and modeling, deconvolution.


Kriete A, Eils R. Computational Systems Biology, 2005, and 2nd edition, 2013 Elsevier - Academic Press

Selected Journal Articles:
Kriete A. Robustness and Aging - A Systems Level Perspective. BioSystems, April 2013
Kriete A, Lechner M, Clearfield D, Bohman D. Computational Systems Biology of Aging. Wiley Interdisciplinary Syst. Biol. Med. Reviews 2011 Jul 3(4): 414-428 Abstract & Images
Shrinivasan V, Kriete A, Sacan A, Jazwinski M. Comparing the yeast retrograde response and NF-kB stress responses. Aging Cell 2010 Dec 9(6): 933-941
Kriete A, Bosl WJ, Booker G. Rule-based cell systems model of aging using feedback loop motifs mediated by stress responses. PLoS Comput Biol. 2010 Jun 17;6(6):e1000820.
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. 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 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, 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.

See more publications on PubMed

Misc. Discoveries: 3769 Arthurmiller. See Solar Systems Dynamics, Jet Propulsion Lab, Caltech
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