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Article
Data Visualization through Graph Drawing
In this paper the problem of visualizing categorical multivariate data sets is considered. By representing the data as the adjacency matrix of an appropriately defined bipartite graph, the problem is transform...
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Article
Queueing Networks of Random Link Topology: Stationary Dynamics of Maximal Throughput Schedules
In this paper, we study the stationary dynamics of a processing system comprised of several parallel queues and a single server of constant rate. The connectivity of the server to each queue is randomly modula...
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Article
Profit-oriented resource allocation using online scheduling in flexible heterogeneous networks
In this paper, we discuss a generalized measurement-based adaptive scheduling framework for dynamic resource allocation in flexible heterogeneous networks, in order to ensure efficient service level performanc...
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Chapter
Data Visualization Through Their Graph Representations
The amount of data and information collected and retained by organizations and businesses is constantly increasing, due to advances in data collection, computerization of transactions, and breakthroughs in sto...
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Chapter
Smart Vehicles in the Smart Grid: Challenges, Trends, and Application to the Design of Charging Stations
Future “smart electric vehicles,” expected to evolve from emerging electric and plug-in hybrid electric vehicles (EV & PHEV) are becoming increasingly attractive. However, the current electric grid is not cons...
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Article
Open AccessTHINK Back: KNowledge-based Interpretation of High Throughput data
Results of high throughput experiments can be challenging to interpret. Current approaches have relied on bulk processing the set of expression levels, in conjunction with easily obtained external evidence, su...
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Article
Adaptive Thresholding for Reconstructing Regulatory Networks from Time-Course Gene Expression Data
Discovering regulatory interactions from time-course gene expression data constitutes a canonical problem in functional genomics and systems biology. The framework of graphical Granger causality allows one to ...
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Article
Open AccessCritical limitations of consensus clustering in class discovery
Consensus clustering (CC) has been adopted for unsupervised class discovery in many genomic studies. It calculates how frequently two samples are grouped together in repeated clustering runs and uses the resul...
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Chapter and Conference Paper
Changepoint Inference for Erdős–Rényi Random Graphs
We formulate a model for the off-line estimation of a changepoint in a network setting. The framework naturally allows the parameter space (network size) to grow with the number of observations. We compute the...
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Article
Operator-valued kernel-based vector autoregressive models for network inference
Reverse-engineering of high-dimensional dynamical systems from time-course data still remains a challenging and important problem in knowledge discovery. For this learning task, a number of approaches primaril...
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Article
Open AccessInhibition of the hexosamine biosynthetic pathway promotes castration-resistant prostate cancer
The precise molecular alterations driving castration-resistant prostate cancer (CRPC) are not clearly understood. Using a novel network-based integrative approach, here, we show distinct alterations in the hex...
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Chapter
Semi-supervised Smoothing for Large Data Problems
This book chapter is a description of some recent developments in non-parametric semi-supervised regression and is intended for someone with a background in statistics, computer science, or data sciences who i...
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Article
Open AccessCore community structure recovery and phase transition detection in temporally evolving networks
Community detection in time series networks represents a timely and significant research topic due to its applications in a broad range of scientific fields, including biology, social sciences and engineering....
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Chapter and Conference Paper
Directed Acyclic Graph Reconstruction Leveraging Prior Partial Ordering Information
Reconstructing directed acyclic graphs (DAGs) from observed data constitutes an important machine learning task. It has important applications in systems biology and functional genomics. However, it is a chall...
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Chapter and Conference Paper
Analyses of Multi-collection Corpora via Compound Topic Modeling
Popular probabilistic topic models have typically centered on one single text collection, which is deficient for comparative text analyses. We consider a setting where we have partitionable corpora. Each subco...
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Article
Preface: Computational biomedicine
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Article
Open AccessA comparative study of topology-based pathway enrichment analysis methods
Pathway enrichment extensively used in the analysis of Omics data for gaining biological insights into the functional roles of pre-defined subsets of genes, proteins and metabolites. A large number of methods ...
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Article
M-estimation in Multistage Sampling Procedures
Multi-stage (designed) procedures, obtained by splitting the sampling budget suitably across stages, and designing the sampling at a particular stage based on information about the parameter obtained from prev...
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Article
Open AccessCounty-level longitudinal clustering of COVID-19 mortality to incidence ratio in the United States
As of November 12, 2020, the mortality to incidence ratio (MIR) of COVID-19 was 5.8% in the US. A longitudinal model-based clustering system on the disease trajectories over time was used to identify “vulnerab...
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Article
Renin-angiotensin system inhibition reverses the altered triacylglycerol metabolic network in diabetic kidney disease
Dyslipidemia is a significant risk factor for progression of diabetic kidney disease (DKD). Determining the changes in individual lipids and lipid networks across a spectrum of DKD severity may identify lipids...
