Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm

Information spreads across social and technological networks, but often the network structures are hidden from us and we only observe the traces left by the diffusion processes, called cascades. Can we recover the hidden network structures from these observed cascades? What kind of cascades and how many cascades do we need? Are there some network structures which are more difficult than others to recover? Can we design efficient inference algorithms with provable guarantees? Despite the increasing availability of cascade data and methods for inferring networks from these data, a thorough theoretical understanding of the above questions remains largely unexplored in the literature. In this paper, we investigate the network structure inference problem for a general family of continuous-time diffusion models using an $l_1$-regularized likelihood maximization framework. We show that, as long as the cascade sampling process satisfies a natural incoherence condition, our framework can recover the correct network structure with high probability if we observe $O(d^3 \log N)$ cascades, where $d$ is the maximum number of parents of a node and $N$ is the total number of nodes. Moreover, we develop a simple and efficient soft-thresholding inference algorithm, which we use to illustrate the consequences of our theoretical results, and show that our framework outperforms other alternatives in practice.Comment: To appear in the 31st International Conference on Machine Learning (ICML), 201

Vectorial targeting of an endogenous apical membrane sialoglycoprotein and uvomorulin in MDCK cells.

We studied the cell-surface delivery pathways of newly synthesized membrane glycoproteins in MDCK cells and for this purpose we characterized an endogenous apical integral membrane glycoprotein. By combining a pulse-chase protocol with domain-selective cell-surface biotinylation, immune precipitation, and streptavidin-agarose precipitation (Le Bivic et al. 1989. Proc. Natl. Acad. Sci USA. 86:9313-9317), we followed the appearance at the cell surface of a major apical sialoglycoprotein, gp114, a basolateral protein, uvomorulin, and a transcytosing protein, the polyimmunoglobulin receptor (pIg-R). We determined that both gp114 and uvomorulin appeared to be delivered directly to their respective surface, with mistargeting levels of 8 and 2%, respectively. Using the same technique, the pIg-R was first detected on the basolateral domain and then on the apical domain, to be finally released into the apical medium, as described (Mostov, K. E., and D. L. Deitcher. 1986. Cell. 46:613-621). To directly determine whether the gp114 pool present on the basolateral surface was a precursor of the apical gp114, we compared it with the equivalent pIg-R pool, by labeling with sulfo-NHS-SS-biotin, a cleavable, tight junction-impermeable probe, and by following the fraction of this probe that became resistant to basal glutathione and accessible to apical glutathione during incubation at 37 degrees C. We found that, contrary to pIg-R, basolateral gp114 was poorly endocytosed and was not transcytosed to the apical side. These results demonstrate that an endogenous apical integral membrane glycoprotein of Madin-Darby canine kidney cells is sorted intracellularly and is vectorially targeted to the apical surface

The TRIZ-CBR synergy: A knowledge based innovation process

Today innovation is recognised as the main driving force in the market. This complex process involves several intangible dimensions, such as creativity, knowledge and social interactions among others. Creativity is the starting point of the process, and knowledge is the force that transforms and materialises creativity in new products, services and processes. In this paper a synergy that aims to assists the innovation process is presented. The synergy combines several concepts and tools of the theory of inventive problem solving (TRIZ) and the case-based reasoning (CBR) process. The main objective of this synergy is to support creative engineering design and problem solving. This synergy is based on the strong link between knowledge and action. In this link, TRIZ offers several concepts and tools to facilitate concept creation and to solve problems, and the CBR process offers a framework capable of storing and reusing knowledge with the aim of accelerating the innovation process

Shaping Social Activity by Incentivizing Users

Events in an online social network can be categorized roughly into endogenous events, where users just respond to the actions of their neighbors within the network, or exogenous events, where users take actions due to drives external to the network. How much external drive should be provided to each user, such that the network activity can be steered towards a target state? In this paper, we model social events using multivariate Hawkes processes, which can capture both endogenous and exogenous event intensities, and derive a time dependent linear relation between the intensity of exogenous events and the overall network activity. Exploiting this connection, we develop a convex optimization framework for determining the required level of external drive in order for the network to reach a desired activity level. We experimented with event data gathered from Twitter, and show that our method can steer the activity of the network more accurately than alternatives

JSBML: a flexible Java library for working with SBML

The specifications of the Systems Biology Markup Language (SBML) define standards for storing and exchanging computer models of biological processes in text files. In order to perform model simulations, graphical visualizations and other software manipulations, an in-memory representation of SBML is required. We developed JSBML for this purpose. In contrast to prior implementations of SBML APIs, JSBML has been designed from the ground up for the Java™ programming language, and can therefore be used on all platforms supported by a Java Runtime Environment. This offers important benefits for Java users, including the ability to distribute software as Java Web Start applications. JSBML supports all SBML Levels and Versions through Level 3 Version 1, and we have strived to maintain the highest possible degree of compatibility with the popular library libSBML. JSBML also supports modules that can facilitate the development of plugins for end user applications, as well as ease migration from a libSBML-based backend