Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Kyle Kloster"'
Autor:
Daniel S. Himmelstein, Michael Zietz, Vincent Rubinetti, Kyle Kloster, Benjamin J. Heil, Faisal Alquaddoomi, Dongbo Hu, David N. Nicholson, Yun Hao, Blair D. Sullivan, Michael W. Nagle, Casey S. Greene
Hetnets, short for “heterogeneous networks”, contain multiple node and relationship types and offer a way to encode biomedical knowledge. One such example, Hetionet connects 11 types of nodes — including genes, diseases, drugs, pathways, and an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a8bceec1c5eedeec71a4db2d305d489
https://doi.org/10.1101/2023.01.05.522941
https://doi.org/10.1101/2023.01.05.522941
Autor:
Michael Zietz, Daniel S. Himmelstein, Kyle Kloster, Christopher Williams, Michael W. Nagle, Casey S. Greene
Important tasks in biomedical discovery such as predicting gene functions, gene-disease associations, and drug repurposing opportunities are often framed as network edge prediction. The number of edges connecting to a node, termed degree, can vary gr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0a3d870629db0849bb566ad42fab9cb7
https://doi.org/10.1101/2023.01.05.522939
https://doi.org/10.1101/2023.01.05.522939
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 12:1-27
Large graphs arise in a number of contexts and understanding their structure and extracting information from them is an important research area. Early algorithms for mining communities have focused on global graph structure, and often run in time pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::506a5ac2cf0298bd96f89b5a8b9bfa4f
https://doi.org/10.1145/3106370
https://doi.org/10.1145/3106370
Publikováno v:
Bioinformatics. 33:1829-1836
Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood- and module-based methods. Recent studies have shown that integrating the hierarchical structure
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fee7743a97d6c4875fd6b25d5465beb0
https://doi.org/10.1093/bioinformatics/btx029
https://doi.org/10.1093/bioinformatics/btx029
Matrix-based centrality measures have enjoyed significant popularity in network analysis, in no small part due to our ability to rigorously analyze their behavior as parameters vary. Recent work has considered the relationship between subgraph centra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10f7d0b8b862fab9fb781305819eeffd
http://arxiv.org/abs/1804.05966
http://arxiv.org/abs/1804.05966
Publikováno v:
Linear Algebra and its Applications
A graph is said to be walk-regular if, for each $\ell \geq 1$, every vertex is contained in the same number of closed walks of length $\ell$. We construct a $24$-vertex graph $H_4$ that is not walk-regular yet has maximized walk entropy, $S^V(H_4,\be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16115b7158f0705c97765bed91a58b84
Autor:
Michael P. O'Brien, Kyle Kloster, Andrew van der Poel, Philipp Kuinke, Fernando Sánchez Villaamil, Felix Reidl, Blair D. Sullivan
Publikováno v:
ALENEX
The Flow Decomposition problem, which asks for the smallest set of weighted paths that "covers" a flow on a DAG, has recently been used as an important computational step in transcript assembly. We prove the problem is in FPT when parameterized by th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d20d7301202d4bf7047b0d317d9f0cd4
https://doi.org/10.1137/1.9781611975055.7
https://doi.org/10.1137/1.9781611975055.7
Autor:
Kyle Kloster, David F. Gleich
Publikováno v:
Internet Mathematics. 11:352-384
We consider stochastic transition matrices from large social and information networks. For these matrices, we describe and evaluate three fast methods to estimate one column of the matrix exponential. The methods are designed to exploit the propertie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb3fe5813704a6dda00eb13833f02812
https://doi.org/10.1080/15427951.2014.971203
https://doi.org/10.1080/15427951.2014.971203
Autor:
Kyle Kloster, David F. Gleich
We study the behavior of network diffusions based on the PageRank random walk from a set of seed nodes. These diffusions are known to reveal small, localized clusters (or communities) and also large macro-scale clusters by varying a parameter that ha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d143b052504d530229163ab0168e25c
http://arxiv.org/abs/1503.00322
http://arxiv.org/abs/1503.00322