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.

MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format.

MSL (Mining Scientific Literature) is a tool to mine scientific literature. MSL can analyze PDF-format publications and extract text and images based on keywords or coordinates. MSL also uses OCR.  

MSL

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