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2017 ; 33
(24
): 3973-3981
Nephropedia Template TP
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Cancer Hallmarks Analytics Tool (CHAT): a text mining approach to organize and
evaluate scientific literature on cancer
#MMPMID29036271
Baker S
; Ali I
; Silins I
; Pyysalo S
; Guo Y
; Högberg J
; Stenius U
; Korhonen A
Bioinformatics
2017[Dec]; 33
(24
): 3973-3981
PMID29036271
show ga
MOTIVATION: To understand the molecular mechanisms involved in cancer
development, significant efforts are being invested in cancer research. This has
resulted in millions of scientific articles. An efficient and thorough review of
the existing literature is crucially important to drive new research. This
time-demanding task can be supported by emerging computational approaches based
on text mining which offer a great opportunity to organize and retrieve the
desired information efficiently from sizable databases. One way to organize
existing knowledge on cancer is to utilize the widely accepted framework of the
Hallmarks of Cancer. These hallmarks refer to the alterations in cell behaviour
that characterize the cancer cell. RESULTS: We created an extensive Hallmarks of
Cancer taxonomy and developed automatic text mining methodology and a tool (CHAT)
capable of retrieving and organizing millions of cancer-related references from
PubMed into the taxonomy. The efficiency and accuracy of the tool was evaluated
intrinsically as well as extrinsically by case studies. The correlations
identified by the tool show that it offers a great potential to organize and
correctly classify cancer-related literature. Furthermore, the tool can be
useful, for example, in identifying hallmarks associated with extrinsic factors,
biomarkers and therapeutics targets. AVAILABILITY AND IMPLEMENTATION: CHAT can be
accessed at: http://chat.lionproject.net. The corpus of hallmark-annotated PubMed
abstracts and the software are available at: http://chat.lionproject.net/about.
CONTACT: simon.baker@cl.cam.ac.uk. SUPPLEMENTARY INFORMATION: Supplementary data
are available at Bioinformatics online.