Implementing the iHOP concept for navigation of biomedical literature

By Robert Hoffmann, Alfonso Valencia. 2005

241 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Molecular Biology

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Citations in the corpus

Natural Language Processing for EHR-Based Computational Phenotyping (2018, background): “[22] links interacting proteins to their corresponding databases and uses co-occurrence information to build a graphi-”
MeInfoText: associated gene methylation and cancer information from text mining (2008, background): “Over the past few years, a considerable number of studies have been made on the mining and extraction of information from biomedical literature, such as disease candidate genes [13,14], protein-protein interactions [15,16], protein functions [17] and modifications [18].”
Biomedical text mining and its applications in cancer research (2013, unknown): “iHOP [70,71,153] Information Hyperlinked over Proteins (iHOP) can generate a network of concurring genes and proteins from millions of PubMed abstracts.”
Identifying gene-disease associations using centrality on a literature mined gene-interaction network (2008, background): “It has been shown that the interaction networks constructed in either way, share similar topological properties such as being small-world and scale-free, with each other and with various nonbiological complex systems such as the WWW, the Internet, and social networks (Chen and Sharp, 2004; Hoffmann ”
The harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins (2016, background): “For example, resources such as WikiGenes (10), iHOP (11), Genes2Wordcloud (12) and EvidenceFinder (http://labs.europepmc.org/evf) identify and highlight genes and other semantic entities in sentences from abstracts and full-text publications to summarize gene and protein functions.”
Corpus annotation for mining biomedical events from literature (2008, background): “…it is reasonable to expect that the corpus will contribute to further progress in NLP-based TM techniques, including event or relation extraction [57-59], intelligent information retrieval [13,60], semantic enrichment of text [61], and integration of text information with pathway databases [11,58].”
Biospider: A Web Server for Automating Metabolome Annotations (2006, methodology): “Text mining tools such as MedMiner, iHOP [5], MedGene [6] and LitMiner [7] exploit the information contained within the PubMed database.”