Chris Wiggins, Ph.D.Associate Professor, Department of Applied Physics and Applied Mathematics
Research ThemeWithin the last decade, the need for mathematical and computational expertise to address questions of biological origin has transformed the nature of biological research. Novel biotechnologies, the unprecedented abundance and character of their data, and the promise of these approaches (in understanding both problems from basic biology as well as clinical research into disease and medicine) have demanded mathematical innovation, and consequently transformed mathematics as well. Biology now poses mathematical modeling challenges unlike those faced in mathematical biology before 10 years ago, and, in some cases, unlike those faced in any prior mathematical application. As an example, the recent sequencing of the genomes of every principal model organism in biology, along with DNA microarray data and other highthroughput novel technologies, suggests the possibility of inferring the causal interactions among the genes, which in turn requires identifying the short sequence elements to which proteins bind (thus regulating the genetic expression). Our lab has developed mathematical approaches for the inference (learning predictive models of transcriptional regulation and discovering regulatory sequence elements from microarray data), organization (inference of modules in biological networks and quantification of modularity), and analysis (predicting evolutionary mechanisms from network architecture) of biological networks. Mathematical approaches include the use of large deviation / large marginbased classifiers (machine learning), statistical inference, network analysis and graph theory, and information theory. Within the context of the nanomedicine center, we are most interested in developing related approaches for 'high throughput microscopy'statistical inference and machine learning analyses of images and movies of microscopic originboth for extracting quantitative information from these images and for inferring biological networks. NoVel, an original software tool have been developed for automated segmentation of cells in movies (figure 1,; movie 1) and measurement and analysis of normal velocity (figures 2 and 3). Also a machine learning approach to detection of multiprotein complexes in cell motility is under development (movie 2). The associated mathematical methods are helping direct future experiments by the collaborators. The significance of this research is not only in the application, where, via direct collaboration with biologists and clinicians, potential areas of impact include basic science, pharmacology, research into cellular mechanisms underlying immunology and cancer, and biomedicine. In addition, by developing 'datadriven' approaches to microscopy (building on experience with microarray data) and thus to cellular biology (building on experience with molecular biology), we hope to forge a muchneeded bridge between the 'new biomathematics,' informed by bioinformatics and statistical learning theory, with more traditional biomathematics of microscopic and mechanistic modeling (building on our experience in such PDEbased modeling at the cellular scale). Knowledge of the underlying dependences or independences among the components of the signaling pathways (i.e, the graph structure), for example, is the prerequisite for such mechanistic modeling; a highthroughput approach to microscopy yields abundant data, which are necessary to constrain and guide these models. We contend that the resulting methods will drive new relationships among data, modeling, and biomedicine. Background and EducationChris Wiggins is an assistant professor of mathematical sciences in the Department of Applied Physics and Applied Mathematics at Columbia University. He is also affiliated with Columbia's Center for Computational Biology and Bioinformatics and one of the coP.I.s in the NIHfunded MAGNet (Multiscale Analysis of Genomic and Cellular Networks) National Center for Biomedical Computation. Wiggins obtained his Ph.D. from Princeton University in theoretical physics. He was a Courant instructor at NYU, and has held visiting positions at Institut Curie (Paris), the HahnMeitner Institut (Berlin), and the Kavli Institute for Theoretical Physics (Santa Barbara). He moved to Columbia in 2001. Honors and Awards
Selected PublicationsMiddendorf M, Kundaje A, Wiggins C, Freund Y, Leslie C. Middendorf M, Kundaje A, Wiggins C, Freund Y, Leslie C. Middendorf M, Ziv E, Adams C, Hom J, Koytcheff R, Levovitz C, Woods G, Chen L, Wiggins C. Kundaje A, Middendorf M, Wiggins C, Leslie C. Middendorf M, Kundaje A, Shah M, Freund Y, Wiggins C, Leslie C. Middendorf M, Ziv E, Wiggins CH. Ziv E, Middendorf M, Wiggins CH. Ziv E, Koytcheff R, Middendorf M, Wiggins C. 
