Results 51 to 60 of about 258,118 (263)

The Connectome Visualization Utility: software for visualization of human brain networks.

open access: yesPLoS ONE, 2014
In analysis of the human connectome, the connectivity of the human brain is collected from multiple imaging modalities and analyzed using graph theoretical techniques. The dimensionality of human connectivity data is high, and making sense of the complex
Roan A LaPlante   +3 more
doaj   +1 more source

From mice to humans—divergent strategies for intestinal homeostasis and regeneration

open access: yesFEBS Letters, EarlyView.
Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa   +2 more
wiley   +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

Big Data and IT Network Data Visualization [PDF]

open access: yesInternational Journal of Mathematical, Engineering and Management Sciences, 2018
Visualization with graphs is popular in the data analysis of Information Technology (IT) networks or computer networks. An IT network is often modelled as a graph with hosts being nodes and traffic being flows on many edges. General visualization methods
Lidong Wang
doaj   +1 more source

Explorative Graph Visualization

open access: yes, 2010
Netzwerkstrukturen (Graphen) sind heutzutage weit verbreitet. Ihre Untersuchung dient dazu, ein besseres Verständnis ihrer Struktur und der durch sie modellierten realen Aspekte zu gewinnen. Die Exploration solcher Netzwerke wird zumeist mit Visualisierungstechniken unterstützt.
openaire   +2 more sources

Multilevel visualization of clustered graphs [PDF]

open access: yes, 1997
Clustered graphs are graphs with recursive clustering structures over the vertices. This type of structure appears in many systems. Examples include CASE tools, management information systems, VLSI design tools, and reverse engineering systems. Existing layout algorithms represent the clustering structure as recursively nested regions in the plane ...
Peter Eades, Qing-Wen Feng
openaire   +1 more source

Design and analysis strategies for robust microbiome ageing research

open access: yesFEBS Letters, EarlyView.
The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik   +5 more
wiley   +1 more source

Spherical Layout for 3D Graph Visualization

open access: yesJournal of Computer Science and Technology, 2007
The goal of this work was centered in the graph visualization. The hope is that the extra dimension would give, literally, more space, and that this would ease the problem of displaying large structures.
Martín Leonardo Larrea
doaj  

Graph Visualization Tools: A Comparative Analysis

open access: yesJISR on Computing, 2015
Data visualization is becoming a necessity for big organizations as the social networking data is growing rapidly. It is becoming difficult to visualize data and perform complex comparisons.
Fariha Majeed, Saif-ur-Rahman
doaj   +1 more source

Decoding the dynamic extracellular matrix in cancer—3D models and bioscaffolds rewire the rules of tumor progression

open access: yesFEBS Letters, EarlyView.
Cancer progression is regulated by the dynamic matrix code of the tumor microenvironment, which influences cellular behavior and disease development. Importantly, matrix remodeling in three‐dimensional cancer models more accurately reflects in vivo conditions compared to conventional two‐dimensional systems.
Sylvia Mangani   +3 more
wiley   +1 more source

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