3.4 Tool and
Visualization of
Integration
Currently, the academic studies not only develop the biological or
computational techniques for integrative analysis but also provide
many software tools and visualization resources for iteratively
review by biologist or clinician as listed in Table5, to easily under-
stand the complicate structure and information in multi-view data
and their meta-outcome (seeNote 4).
As the general applications of integrative analysis and visualiza-
tion tool public accessible, Ensembl Genomes is an integrative
resource for genome-scale data from non-vertebrate species
[106], which exploits and extends technology developed in the
context of the Ensembl project and provides a complementary set
of resources for non-vertebrate species through a consistent set of
programmatic and interactive interfaces. Similarly, the cBioPortal
for Cancer Genomics provides a Web resource for exploring, visua-
lizing, and analyzing multidimensional cancer genomics data
[107], whose portal reduces molecular profiling data from cancer
tissues and cell lines into readily understandable genetic, epigenetic,
gene expression, and proteomic events.
Meanwhile, as expert approaches of integrative analysis and
visualization tool online, a Web tool, named Integrated Clustering
of Multidimensional biomedical data (ICM), can provide an inter-
face from which to fuse, cluster, and visualize multidimensional
biomedical data and knowledge or can explore the heterogeneity
of a disease or a biological process by identifying subgroups of
patients [108]. Next, an integrative meta-analysis of expression
data (INMEX) is designed to support meta-analysis of multiple
gene expression datasets, as well as datasets from gene expression
and metabolomics experiments, whose statistical analysis module
allows researchers to combine multiple datasets based onPvalues,
effect sizes, rank orders, and other features [109]. Then, a Web
server, SteinerNet, establishes a framework for integrating tran-
scriptional, proteomic, and interactome data by searching for the
solution to the prize-collecting Steiner tree problem [110]. Besides,
a new data integration framework, Anduril, is introduced for trans-
lating fragmented large-scale data into testable predictions, and it
allows rapid integration of heterogeneous data with state-of-the-art
computational methods and existing knowledge in
bio-databases [111].
Similarly, when taking particular focus on integrative analysis
and visualization on TCGA data, Web-TCGA, a Web-based, freely
accessible online tool, can also be run in a private instance, for
integrated analysis of molecular cancer datasets provided by
TCGA [68]. And MEXPRESS is developed as a straightforward
and easy-to-use Web tool for the integration and visualization of
the expression, DNA methylation, and clinical TCGA data on a
single-gene level, which offers clinical researchers a simple way to
evaluate the TCGA data for their genes or candidate biomarkers of
interest [64]. And CrossHub software is developed to enable124 Xiang-Tian Yu and Tao Zeng