William T. Hendrix

Works (5)

Updated: July 6th, 2023 11:35

2015 article

On size-constrained minimum s–t cut problems and size-constrained dense subgraph problems

Chen, W., Samatova, N. F., Stallmann, M. F., Hendrix, W., & Ying, W. (2015, October 30). Theoretical Computer Science, Vol. 609, pp. 434–442.

By: W. Chen *, N. Samatova n, M. Stallmann n , W. Hendrix n & W. Ying *

author keywords: At-least-k-subgraph problem; At-most-k-subgraph problem; Approximation algorithm; The minimum s-t cut with at-least-k vertices problem; The minimum s-t cut with at-most-k vertices problem; The minimum s-t cut with exactly k vertices problem
topics (OpenAlex): Complexity and Algorithms in Graphs; Advanced Graph Theory Research; Computational Geometry and Mesh Generation
TL;DR: The minimum s-t cut with at-least-k vertices problem, the minimum s -t cutWith at-most-k-subgraph problem, and the Minimum s-T cut with exactly k vertices problems are introduced and it is proved that they are NP-complete. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2012 article

Discovery of extreme events-related communities in contrasting groups of physical system networks

Chen, Z., Hendrix, W., Guan, H., Tetteh, I. K., Choudhary, A., Semazzi, F., & Samatova, N. F. (2012, August 31). Data Mining and Knowledge Discovery.

By: Z. Chen n, W. Hendrix n, H. Guan*, I. Tetteh n, A. Choudhary *, F. Semazzi n, N. Samatova n

author keywords: Spatio-temporal data mining; Complex network analysis; Community detection; Comparative analysis; Networkmotif detection; Extreme event prediction
topics (OpenAlex): Complex Network Analysis Techniques; Opinion Dynamics and Social Influence; Human Mobility and Location-Based Analysis
TL;DR: This paper forms a novel problem—detection of predictive and phase-biased communities in contrasting groups of networks, and proposes an efficient and effective machine learning solution for finding such anomalous communities. (via Semantic Scholar)
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13. Climate Action (Web of Science; OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2011 article

Community-based anomaly detection in evolutionary networks

Chen, Z., Hendrix, W., & Samatova, N. F. (2011, October 18). Journal of Intelligent Information Systems.

By: Z. Chen n, W. Hendrix n & N. Samatova n

topics (OpenAlex): Complex Network Analysis Techniques; Bioinformatics and Genomic Networks; Evolutionary Game Theory and Cooperation
TL;DR: This work develops a parameter-free and scalable algorithm using a proposed representative-based technique to detect all six possible types of community-based anomalies: grown, shrunken, merged, split, born, and vanished communities, and detail the underlying theory required to guarantee the correctness of the algorithm. (via Semantic Scholar)
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UN Sustainable Development Goal Categories
13. Climate Action (OpenAlex)
Source: NC State University Libraries
Added: August 6, 2018

2011 article

DENSE: efficient and prior knowledge-driven discovery of phenotype-associated protein functional modules

Hendrix, W., Rocha, A. M., Padmanabhan, K., Choudhary, A., Scott, K., Mihelcic, J. R., & Samatova, N. F. (2011, October 24). BMC Systems Biology.

By: W. Hendrix n, A. Rocha *, K. Padmanabhan n, A. Choudhary*, K. Scott *, J. Mihelcic *, N. Samatova n

MeSH headings : Animals; Binding Sites; Cattle; Cell Movement; Cells, Cultured; Computer Simulation; Extracellular Matrix / metabolism; Fibronectins / metabolism; Humans; Models, Biological; Neuropilin-1 / metabolism; Pancreatic Elastase / metabolism; Phenotype; Rats; Receptors, Vascular Endothelial Growth Factor / metabolism; Signal Transduction; Systems Biology; Vascular Endothelial Growth Factor A / chemistry; Vascular Endothelial Growth Factor A / metabolism; Vascular Endothelial Growth Factor A / physiology
topics (OpenAlex): Microbial Metabolic Engineering and Bioproduction; Bioinformatics and Genomic Networks; Computational Drug Discovery Methods
TL;DR: A fast and theoretically guranteed method called DENSE (Dense and ENriched Subgraph Enumeration) that can take in as input a biologist's prior knowledge as a set of query proteins and identify all the dense functional modules in a biological network that contain some part of the query vertices is introduced. (via Semantic Scholar)
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Source: Web Of Science
Added: August 6, 2018

2010 article

Theoretical underpinnings for maximal clique enumeration on perturbed graphs

Hendrix, W., Schmidt, M. C., Breimyer, P., & Samatova, N. F. (2010, March 11). Theoretical Computer Science, Vol. 411, pp. 2520–2536.

By: W. Hendrix n, M. Schmidt n , P. Breimyer n & N. Samatova n

author keywords: Graph perturbation theory; Maximal clique enumeration; Graph algorithms; Uncertain and noisy data
topics (OpenAlex): Bioinformatics and Genomic Networks; Gene Regulatory Network Analysis; Gene expression and cancer classification
TL;DR: By enumerating only the difference set between the baseline and perturbed graphs' MCEs, the computational cost of enumerating the maximal cliques of the perturbed graph can be reduced. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

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