Title: Classification of TCGA-related research articles based on cancer types and experimental strategy

Authors: Deepika Kulshreshtha; Arindam Deb; Krishanpal Anamika

Addresses: Life Sciences Research Unit, CTO, Persistent Systems, Pune, India ' Life Sciences Research Unit, CTO, Persistent Systems, Pune, India ' Life Sciences Research Unit, CTO, Persistent Systems, Pune, India

Abstract: The Cancer Genome Atlas (TCGA) was launched in the year 2006 to accelerate the comprehensive understanding of the genetics of cancer using advanced high throughput technologies. It has been helping to generate new cancer therapies, prognostics methods, diagnostic methods and preventive strategies. This has led to an exponential increase in scientific articles utilising and corroborating information and data from TGCA to various related studies. With this exponential increase in the number of articles, it is challenging to identify specific articles of interest for a particular cancer type. It is even more challenging to identify articles by specific data types. In this work, we have built a web-tool, CTP (Classification of TCGA Publications), to systematically classify the articles that are utilising TCGA data. This tool enables users to access all the relevant articles available for a particular cancer type or experimental strategy utilising TCGA data.

Keywords: TCGA; cancer; web-tool; literature search; article classification.

DOI: 10.1504/IJDMB.2022.130332

International Journal of Data Mining and Bioinformatics, 2022 Vol.27 No.1/2/3, pp.221 - 229

Received: 28 Apr 2022
Accepted: 28 Nov 2022
Published online: 17 Apr 2023 *

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