Biomedical Engineering Reference
In-Depth Information
beyond the current technology of informatics which is typically focused on collecting,
representing and linking information and managing various aspects of both systemic
and semantic heterogeneity. In this regard, translational nanoinformatics can extend
the vision of translating basic research into clinical applications down to the nano
level. A wide number of applications can be envisioned along these lines.
4.11
Networks of International Researchers, Projects and Labs
Collaborative research and the development of tools, standards, databases, and
publications to support it have shown the feasibility of linking people with related
objectives to work together towards a common target. Recently, new opportunities
for funding have arisen, and European groups can now be funded by the US
National Institutes of Health (NIH) and National Science Foundation (NSF)
and vice versa. This new environment will facilitate collaborative research and
exchange, as happened earlier in joint initiatives like the Human Genome Project.
In the nano fields, such international collaborations are likely to be fundamental in
exploiting complementary strengths for advancing research.
4.12
Text Mining for Nanomedical Research
Text Mining (TM) techniques have been extensively used in Medical Informatics
(MI) and Bioinformatics (BI) research for different tasks involving the extraction
of data and knowledge from textual sources. These tasks include, among others, (i)
identifying and extracting named entities such as genes and/or proteins (Chang
et al.
2004
; Mika and Rost
2004
; Settles
2005
; Tanabe et al.
2005
; Torii et al.
2009
)
or sequences of nucleic acids and proteins (Mika and Rost
2004
; Wren et al.
2005
;
Aerts et al.
2008
; García-Remesal et al.
2010a
), (ii) supporting the semantic annota-
tion of textual documents by matching document terms to concepts belonging to
controlled vocabularies and ontologies (Aronson
2001
), (iii) building ontologies
and concept networks from textual resources (García-Remesal et al.
2007
), (iv)
identifying and extracting relationships between different concepts (Rindflesch and
Fiszman
2003
; Lussier et al.
2006
; García-Remesal et al.
2010b
), and (v) automati-
cally populating electronic health records and other biomedical databases with
information extracted from texts (Meystre et al.
2008
; de la Calle et al.
2009
,
García-Remesal et al.
2010c
).
From an informatics perspective, we believe that previous TM research carried
out within MI and BI can be adapted and reused to create novel methods, tools
and data resources to facilitate nanomedicine research. For instance, we have deve-
loped an informatics tool to identify and extract the toxic effects of nanoparticles
reported in the literature. Our tool was built by adapting and modifying the methods
and source code of ABNER (Settles
2005
), a tool for recognizing mention of
genes and proteins in scientific papers. Once the text has been analyzed by our tool
and the targets have been detected, the tool highlights the recognized entities with
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