Results 91 to 100 of about 704,956 (316)

Graph Kernels Exploiting Weisfeiler-Lehman Graph Isomorphism Test Extensions [PDF]

open access: yes, 2014
In this paper we present a novel graph kernel framework inspired the by the Weisfeiler-Lehman (WL) isomorphism tests. Any WL test comprises a relabelling phase of the nodes based on test-specific information extracted from the graph, for example the set ...
Giovanni Da San Martino   +5 more
core   +1 more source

Cell geometry and membrane protein crowding constrain Escherichia coli growth rate, overflow metabolism, respiration, and maintenance energy

open access: yesFEBS Letters, EarlyView.
The physical dimensions and shape of bacterial cells define the surface area available to acquire nutrients and the volume available for synthesizing proteins and DNA. Here, we use computational systems biology to decode the importance of cell geometry as a major determinant of prokaryotic phenotype, including growth rate and metabolic efficiency. This
Ross P. Carlson   +6 more
wiley   +1 more source

Graphical analysis of guideline adherence to detect systemwide anomalies in HIV diagnostic testing.

open access: yesPLoS ONE, 2022
BackgroundAnalyses of electronic medical databases often compare clinical practice to guideline recommendations. These analyses have a limited ability to simultaneously evaluate many interconnected medical decisions.
Ronald George Hauser   +4 more
doaj   +1 more source

Testing graphs against an unknown distribution [PDF]

open access: yesProceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019
The area of graph property testing seeks to understand the relation between the global properties of a graph and its local statistics. In the classical model, the local statistics of a graph is defined relative to a uniform distribution over the graph's vertex set. A graph property $\mathcal{P}$ is said to be testable if the local statistics of a graph
Lior Gishboliner, Asaf Shapira
openaire   +4 more sources

Online hierarchical graph drawing [PDF]

open access: yes, 2001
. We propose a heuristic for maintaining dynamic hierarchical graph layouts. The heuristic is an on-line interpretation of the static layout algorithm of Sugiyama, Togawa and Toda.
North, Stephen   +3 more
core   +1 more source

Salmonella lipopolysaccharide‐containing supported lipid bilayers as platforms to study bacteriophage interactions

open access: yesFEBS Letters, EarlyView.
We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace   +6 more
wiley   +1 more source

Introducing hat graphs

open access: yesCognitive Research, 2019
Visualizing data through graphs can be an effective way to communicate one’s results. A ubiquitous graph and common technique to communicate behavioral data is the bar graph.
Jessica K. Witt
doaj   +1 more source

Random graph models for wireless communication networks [PDF]

open access: yes, 2010
PhDThis thesis concerns mathematical models of wireless communication networks, in particular ad-hoc networks and 802:11 WLANs. In ad-hoc mode each of these devices may function as a sender, a relay or a receiver.
Song, Linlin
core  

Enhancing the efficacy of the 20 m multistage shuttle run test [PDF]

open access: yes, 2005
OBJECTIVE: Maximal oxygen uptake (Vo(2max)) of 44 ml kg(-1) min(-1) is an accepted criterion (Vo(2CR)) below which health and fitness for young male adults may be compromised.
A D Flouris   +8 more
core   +1 more source

Modelling stem cell differentiation related processes—A practical overview for biologists

open access: yesFEBS Letters, EarlyView.
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar   +4 more
wiley   +1 more source

Home - About - Disclaimer - Privacy