Abstract
Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalography (EEG), magnetoencephalography (MEG), echocardiography (ECG), positron-emission tomography (PET) images. The importance of biomedical figures has been widely recognized in scientific and medicine communities, as they play a vital role in providing major original data, experimental and computational results in concise form. One major challenge for implementing a system for scientific literature analysis is extracting and analyzing text and figures from published PDF files by physical and logical document analysis. Here we present a product line architecture based bioinformatics tool 'Mining Scientific Literature (MSL)', which supports the extraction of text and images by interpreting all kinds of published PDF files using advanced data mining and image processing techniques. It provides modules for the marginalization of extracted text based on different coordinates and keywords, visualization of extracted figures and extraction of embedded text from all kinds of biological and biomedical figures using applied Optimal Character Recognition (OCR). Moreover, for further analysis and usage, it generates the system's output in different formats including text, PDF, XML and images files. Hence, MSL is an easy to install and use analysis tool to interpret published scientific literature in PDF format.
Highlights
There has been an enormous increase in the amount of the scientific literature in the last decades[1]
We developed Mining Scientific Literature (MSL)’s Text module, which is capable of processing Portable Document Format (PDF) files with single, double or multiple columns
In the case of text extraction we observed that the text was in reading order when using manuscripts from F1000Research and IEEE but text was without spaces in the manuscript from PLOS and with additional lines and extra spaces in the manuscript from Hindawi
Summary
There has been an enormous increase in the amount of the scientific literature in the last decades[1]. Most published scientific literature is available in Portable Document Format (PDF), a very common way for exchanging printable documents. This makes it all-important to extract text and figures from the PDF files to implement an efficient Natural Language Processing (NLP) based search application. PDF is only rich in displaying and printing but requires explicit efforts in the extraction of information, which significantly impacts the search and retrieval capabilities[2]. Due to this reason several document analysis based tools have been developed for physical and logical document structure analysis of this file type
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
