Mining the Biomedical Literature in the Genomic Era: An Overview

By Hagit Shatkay, Ronen Feldman. J. Comput. Biol., 2003

309 citations recorded by the source corpus.

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Extracting interactions between proteins from the literature (2008, unknown): “In general , the methods proposed so far rely on the techniques from one or more areas [29] [30] [31] [32] including Information Retrieval (IR) [27] [33], Machine Learning (ML) [34] [35], Natural Language Processing (NLP) [36] [37] [38], Information Extraction (IE) [39] [40] [41] [42] and Text…”
Predicting the Political Alignment of Twitter Users (2011, methodology): “In the simple case of binary classification, an SVM works by embedding data in a highdimensional space and attempting to find the hyperplane that best separates the two classes [25].”
Corpus annotation for mining biomedical events from literature (2008, background): “Background Due to the ever-increasing amount of scientific articles in the bio-medical domain, Text Mining (TM) has been recognized as one of the key technologies for future bio-medical research [1-8].”
CoPub Mapper: mining MEDLINE based on search term co-publication (2005, background): “Therefore, mining the MEDLINE database for all information on a set of genes of interest to extract and evaluate their cooccurrences with biological keywords and other genes, could reveal biologically relevant pathways [3-6].”
Protein complex prediction via cost-based clustering (2004, methodology): “Text analysis and manual curation of PubMed resources will help substantially (Shatkay and Feldman, 2003; Xenarioset al., 2000; Zanzoni et al., 2002; Periet al., 2003).”