Work in collaboration with the PSC-VB team and the Duke Center for InVivo Microscopy (CIVM) with support from the National Library of Medicine.Volumetric datasets (CT, MRI, EM, etc.) on the gigabyte scale are relativelycommon in the basic and clinic al Life Sciences, and datasets on the terabytescale will become increasingly common in the near f...
Creator:
Wetzel, Art W. (Pittsburgh Supercomputing Center)
Created:
2006-01-12
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
he reverse engineering of biological networks is an important andinteresting problem. Two examples of such networks are generegulatory networks, and the relationship of voxels in the brain. Wedescribe a method for determining possible 'wiring diagrams' for suchnetworks. The method is based on computational algebra, and a keypart of the method us...
Creator:
Stillman, Michael E. (Cornell University)
Created:
2006-09-19
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Cellular information processing is carried out by complex biomolecular networksthat are able to function reliably despite environmental noise and genetic mutations.The robustness and evolvability of biological systems is supported in part by neutralnetworks and neutral spaces that allow for the preservation of phenotype despite underlyinggenotyp...
Creator:
Myers, Christopher R. (Cornell University)
Created:
2008-04-24
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Biological networks that arise in signal transduction, metabolism, gene control or other cellular functions frequently involve many steps and many levels of control, but are remarkably reliable in producing the desired output in response to inputs. In this talk we will discuss general characteristics such as sensitivity and adaptation of network...
Creator:
Othmer, Hans G. (University of Minnesota, Twin Cities)
Created:
2008-01-16
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Consider the system of reaction rate equations (RRE) describing a chemical network with the reaction rate constants considered to be unknown parameters. The talk shall describe a statistical approach to identifying the 'most likely network' from a given set of RRE coefficient estimates. The idea relies on mapping the estimated reaction constants...
Creator:
Rempala, Grzegorz A. (University of Louisville)
Created:
2008-05-13
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
The spiking dynamics of simultaneously recorded neurons from a small region of cortex reflect the local network structure of excitatory and inhibitory connections between observed neurons, as well as the time varying response of the neurons to their many unobserved and correlated inputs. Inference about the local network is easily contaminated b...
Creator:
Geman, Stuart (Brown University); Harrison, Matthew T (Brown University)
Created:
2011-10-27
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Sensor networks are poised to impact society in fundamental ways analogous to the impact of the networked personal computers. The rapid development of small-scale sensors coupled with wireless ad hoc networking capability foreshadows a day when our physical surroundings will wake up with sensory data, assuming it does not drown in the data first...
Creator:
Ghrist, Robert (University of Pennsylvania)
Created:
2009-01-22
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
This work introduces Graphon Mean Field Game (GMFG) theory for the analysis of non-cooperative dynamical games involving agent modelled as controlled stochastic systems distributed over networks of unbounded size. One component is the profoundly influential new graphon theory of large networks and their infinite limits due to Lovasa'z and cowork...
Creator:
Caines, Peter (McGill University)
Created:
2018-05-11
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Energy networks are becoming increasingly decentralized and exhibit new forms of coupling. For instance, during the polar vortex of 2014, sustained low temperatures in the Midwest region of the U.S. resulted in unusually high gas demands from buildings in urban areas. This led to shortages of natural gas that propagated to California, Massachuse...
Creator:
Zavala, Victor M. (University of Wisconsin, Madison)
Created:
2016-05-11
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Systems as diverse as the world wide web, Internet or the cell are described by highly interconnected networks with amazingly complex structure. Recent studies indicate that the evolution of these complex networks is governed by simple but generic laws, resulting in apparently universal architectural features. I will discuss this amazing order c...
Creator:
Barabási, Albert-László (Northeastern University)
Created:
2009-04-28
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Sequence-based computational approaches have revolutionized biological understanding. However, they can fail to explain some biological phenomena. Since proteins aggregate to perform a function instead of acting in isolation, the connectivity of a protein interaction network (PIN) will provide additional insight into the inner working on the cel...
Creator:
Przulj, Natasha (Imperial College London)
Created:
2012-02-28
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
The set of tools for thinking hard about sampling and measurement-level aspects of scientific studies is among the earliest areas of statistics tobe worked out. However, it arguably is not among the sexier topic areas. In network analysis, perhaps partly as a result of this fact, it is not infrequent that we find ourselves inclined to quickly mo...
Creator:
Kolaczyk, Eric (Boston University)
Created:
2012-02-28
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Preferential attachment is a powerful mechanism explaining the emergence of scaling in growing networks. If new connections are established preferentially to more popular nodes in a network, then the network is scale-free. Here we show that not only popularity but also similarity is a strong force shaping the network structure and dynamics. We d...
Created:
2011-10-24
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Networks of biological signals guide cells to formmulticellular patterns and structures. Understanding thedesign and function of these complex networks is a fundamentalchallenge in developmental biology and has clear implicationsfor biomedical applications, such as tissue engineering andregenerative medicine. Signaling networks are composed ofhi...
Creator:
Asthagiri, Anand R. (California Institute of Technology)
Created:
2008-04-25
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
The field of systems biology has emerged from a confluence of technological advances (DNA sequencing, gene expression profiling, proteomics, metabolomics etc.) and a "systems-level" understanding of biological processes, supported by network theory. Network models are essential in the interpretation of experimental results and, increasingly, in ...
Creator:
Pinney, John (Imperial College London)
Created:
2012-02-27
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Hawkes processes has been a popular point process model for capturing mutual excitation of discrete events. In the network setting, this can capture the mutual influence between nodes, which has a wide range of applications in neural science, social networks, and crime data analysis. In this talk, I will present a statistical change-point detect...
Creator:
Xie, Yao (Georgia Institute of Technology)
Created:
2018-04-24
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Homology on semimodule-valued sheaves naturally generalizes network flows from the setting of numerical capacity constraints to other sorts of constraints (e.g. stochastic, multicommodity). In this talk, we present new work relating the algebraic structure of flows with local network properties and algebraic properties of the ground semiring. Fo...
Creator:
Krishnan, Sanjeevi (University of Pennsylvania)
Created:
2014-03-03
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.