246 research outputs found
Graph Drawing via Gradient Descent,
Readability criteria, such as distance or neighborhood preservation, are
often used to optimize node-link representations of graphs to enable the
comprehension of the underlying data. With few exceptions, graph drawing
algorithms typically optimize one such criterion, usually at the expense of
others. We propose a layout approach, Graph Drawing via Gradient Descent,
, that can handle multiple readability criteria. can optimize
any criterion that can be described by a smooth function. If the criterion
cannot be captured by a smooth function, a non-smooth function for the
criterion is combined with another smooth function, or auto-differentiation
tools are used for the optimization. Our approach is flexible and can be used
to optimize several criteria that have already been considered earlier (e.g.,
obtaining ideal edge lengths, stress, neighborhood preservation) as well as
other criteria which have not yet been explicitly optimized in such fashion
(e.g., vertex resolution, angular resolution, aspect ratio). We provide
quantitative and qualitative evidence of the effectiveness of with
experimental data and a functional prototype:
\url{http://hdc.cs.arizona.edu/~mwli/graph-drawing/}.Comment: Appears in the Proceedings of the 28th International Symposium on
Graph Drawing and Network Visualization (GD 2020
Analysis of gene regulatory networks of maize in response to nitrogen
Nitrogen (N) fertilizer has a major influence on the yield and quality. Understanding and optimising the response of crop plants to nitrogen fertilizer usage is of central importance in enhancing food security and agricultural sustainability. In this study, the analysis of gene regulatory networks reveals multiple genes and biological processes in response to N. Two microarray studies have been used to infer components of the nitrogen-response network. Since they used different array technologies, a map linking the two probe sets to the maize B73 reference genome has been generated to allow comparison. Putative Arabidopsis homologues of maize genes were used to query the Biological General Repository for Interaction Datasets (BioGRID) network, which yielded the potential involvement of three transcription factors (TFs) (GLK5, MADS64 and bZIP108) and a Calcium-dependent protein kinase. An Artificial Neural Network was used to identify influential genes and retrieved bZIP108 and WRKY36 as significant TFs in both microarray studies, along with genes for Asparagine Synthetase, a dual-specific protein kinase and a protein phosphatase. The output from one study also suggested roles for microRNA (miRNA) 399b and Nin-like Protein 15 (NLP15). Co-expression-network analysis of TFs with closely related profiles to known Nitrate-responsive genes identified GLK5, GLK8 and NLP15 as candidate regulators of genes repressed under low Nitrogen conditions, while bZIP108 might play a role in gene activation
Spartan Daily, April 1, 1986
Volume 86, Issue 39https://scholarworks.sjsu.edu/spartandaily/7428/thumbnail.jp
Spartan Daily, November 6, 1992
Volume 99, Issue 50https://scholarworks.sjsu.edu/spartandaily/8334/thumbnail.jp
Spartan Daily, February 19, 1993
Volume 100, Issue 16https://scholarworks.sjsu.edu/spartandaily/8373/thumbnail.jp
Spartan Daily, May 1, 1991
Volume 96, Issue 59https://scholarworks.sjsu.edu/spartandaily/8127/thumbnail.jp
Spartan Daily, April 16, 1993
Volume 100, Issue 48https://scholarworks.sjsu.edu/spartandaily/8406/thumbnail.jp
Spartan Daily, April 16, 1993
Volume 100, Issue 48https://scholarworks.sjsu.edu/spartandaily/8406/thumbnail.jp
Spartan Daily, April 7, 1993
Volume 100, Issue 41https://scholarworks.sjsu.edu/spartandaily/8399/thumbnail.jp
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