A survey on the densest subgraph problem and its variants
The Densest Subgraph Problem requires us to find, in a given graph, a subset of vertices
whose induced subgraph maximizes a measure of density. The problem has received a …
whose induced subgraph maximizes a measure of density. The problem has received a …
–Omic and electronic health record big data analytics for precision medicine
PY Wu, CW Cheng, CD Kaddi… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
Objective: Rapid advances of high-throughput technologies and wide adoption of electronic
health records (EHRs) have led to fast accumulation of–omic and EHR data. These …
health records (EHRs) have led to fast accumulation of–omic and EHR data. These …
[图书][B] Data mining: concepts and techniques
Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and
methods for mining patterns, knowledge, and models from various kinds of data for diverse …
methods for mining patterns, knowledge, and models from various kinds of data for diverse …
Graph clustering
SE Schaeffer - Computer science review, 2007 - Elsevier
In this survey we overview the definitions and methods for graph clustering, that is, finding
sets of “related” vertices in graphs. We review the many definitions for what is a cluster in a …
sets of “related” vertices in graphs. We review the many definitions for what is a cluster in a …
Integrating structured biological data by kernel maximum mean discrepancy
Motivation: Many problems in data integration in bioinformatics can be posed as one
common question: Are two sets of observations generated by the same distribution? We …
common question: Are two sets of observations generated by the same distribution? We …
A survey of frequent subgraph mining algorithms
Graph mining is an important research area within the domain of data mining. The field of
study concentrates on the identification of frequent subgraphs within graph data sets. The …
study concentrates on the identification of frequent subgraphs within graph data sets. The …
Comparing stars: On approximating graph edit distance
Graph data have become ubiquitous and manipulating them based on similarity is essential
for many applications. Graph edit distance is one of the most widely accepted measures to …
for many applications. Graph edit distance is one of the most widely accepted measures to …
Graph-based methods for analysing networks in cell biology
T Aittokallio, B Schwikowski - Briefings in bioinformatics, 2006 - academic.oup.com
Availability of large-scale experimental data for cell biology is enabling computational
methods to systematically model the behaviour of cellular networks. This review surveys the …
methods to systematically model the behaviour of cellular networks. This review surveys the …
A core-attachment based method to detect protein complexes in PPI networks
Background How to detect protein complexes is an important and challenging task in post
genomic era. As the increasing amount of protein-protein interaction (PPI) data are …
genomic era. As the increasing amount of protein-protein interaction (PPI) data are …
A survey of algorithms for dense subgraph discovery
In this chapter, we present a survey of algorithms for dense subgraph discovery. The
problem of dense subgraph discovery is closely related to clustering though the two …
problem of dense subgraph discovery is closely related to clustering though the two …