Results 1  10
of
808,305
Estimating node degree in baitprey graphs
"... Motivation: Proteins work together to drive biological processes in cellular machines. Summarizing global and local properties of the set of protein interactions, the interactome, is necessary for describing cellular systems. We consider a relatively simple perprotein feature of the interactome: th ..."
Abstract

Cited by 5 (0 self)
 Add to MetaCart
to estimate node degree on portions of the interactome assayed by baitprey technologies. This approach yields substantial improvement in degree estimation over the current practice which naïvely sums observed edges. Accurate modeling of observed data in relation to true but unknown parameters of interest
Systems biology Estimating node degree in baitprey graphs
, 2007
"... Motivation: Proteins work together to drive biological processes in cellular machines. Summarizing global and local properties of the set of protein interactions, the interactome, is necessary for describing cellular systems. We consider a relatively simple perprotein feature of the interactome: th ..."
Abstract
 Add to MetaCart
to estimate node degree on portions of the interactome assayed by baitprey technologies. This approach yields substantial improvement in degree estimation over the current practice that naı̈vely sums observed edges. Accurate modeling of observed data in relation to true but unknown parameters of interest
Community detection in graphs
, 2009
"... The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of th ..."
Abstract

Cited by 801 (1 self)
 Add to MetaCart
The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices
Books in graphs
, 2008
"... A set of q triangles sharing a common edge is called a book of size q. We write β (n, m) for the the maximal q such that every graph G (n, m) contains a book of size q. In this note 1) we compute β ( n, cn 2) for infinitely many values of c with 1/4 < c < 1/3, 2) we show that if m ≥ (1/4 − α) ..."
Abstract

Cited by 2380 (22 self)
 Add to MetaCart
A set of q triangles sharing a common edge is called a book of size q. We write β (n, m) for the the maximal q such that every graph G (n, m) contains a book of size q. In this note 1) we compute β ( n, cn 2) for infinitely many values of c with 1/4 < c < 1/3, 2) we show that if m ≥ (1/4 − α
Factor Graphs and the SumProduct Algorithm
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 1998
"... A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple c ..."
Abstract

Cited by 1787 (72 self)
 Add to MetaCart
A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple
Graphs over Time: Densification Laws, Shrinking Diameters and Possible Explanations
, 2005
"... How do real graphs evolve over time? What are “normal” growth patterns in social, technological, and information networks? Many studies have discovered patterns in static graphs, identifying properties in a single snapshot of a large network, or in a very small number of snapshots; these include hea ..."
Abstract

Cited by 534 (48 self)
 Add to MetaCart
heavy tails for in and outdegree distributions, communities, smallworld phenomena, and others. However, given the lack of information about network evolution over long periods, it has been hard to convert these findings into statements about trends over time. Here we study a wide range of real graphs
High dimensional graphs and variable selection with the Lasso
 ANNALS OF STATISTICS
, 2006
"... The pattern of zero entries in the inverse covariance matrix of a multivariate normal distribution corresponds to conditional independence restrictions between variables. Covariance selection aims at estimating those structural zeros from data. We show that neighborhood selection with the Lasso is a ..."
Abstract

Cited by 751 (23 self)
 Add to MetaCart
is a computationally attractive alternative to standard covariance selection for sparse highdimensional graphs. Neighborhood selection estimates the conditional independence restrictions separately for each node in the graph and is hence equivalent to variable selection for Gaussian linear models. We
N Degrees of Separation: MultiDimensional Separation of Concerns
 IN PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING
, 1999
"... Done well, separation of concerns can provide many software engineering benefits, including reduced complexity, improved reusability, and simpler evolution. The choice of boundaries for separate concerns depends on both requirements on the system and on the kind(s) of decompositionand composition a ..."
Abstract

Cited by 514 (8 self)
 Add to MetaCart
Done well, separation of concerns can provide many software engineering benefits, including reduced complexity, improved reusability, and simpler evolution. The choice of boundaries for separate concerns depends on both requirements on the system and on the kind(s) of decompositionand composition a given formalism supports. The predominant methodologies and formalisms available, however, support only orthogonal separations of concerns, along single dimensions of composition and decomposition. These characteristics lead to a number of wellknown and difficult problems. This paper describes a new paradigm for modeling and implementing software artifacts, one that permits separation of overlapping concerns along multiple dimensions of composition and decomposition. This approach addresses numerous problems throughout the software lifecycle in achieving wellengineered, evolvable, flexible software artifacts and traceability across artifacts.
Secure Group Communications Using Key Graphs
, 1998
"... Many emerging applications (e.g., teleconference, realtime information services, pay per view, distributed interactive simulation, and collaborative work) are based upon a group communications model, i.e., they require packet delivery from one or more authorized senders to a very large number of au ..."
Abstract

Cited by 552 (17 self)
 Add to MetaCart
management. We formalize the notion of a secure group as a triple (U; K;R) where U denotes a set of users, K a set of keys held by the users, and R a userkey relation. We then introduce key graphs to specify secure groups. For a special class of key graphs, we present three strategies for securely
Results 1  10
of
808,305