Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery is a research paper published in Briefings in Bioinformatics (2015). On theSindex it has a DataRank of 7.3. It has been cited 166 times, with 166 citing works in its 1-hop citation network.
Precision medicine will revolutionize the way we treat and prevent disease. A major barrier to the implementation of precision medicine that clinicians and translational scientists face is understanding the underlying mechanisms of disease. We are starting to address this challenge through automatic approaches for information extraction, representation and analysis. Recent advances in text and data mining have been applied to a broad spectrum of key biomedical questions in genomics, pharmacogenomics and other fields. We present an overview of the fundamental methods for text and data mining, as well as recent advances and emerging applications toward precision medicine.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.768
From this paper's citation signal
Citation Network Contribution
6.5
From 135 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 11% comes from its base citations and 89% from the citation network (135 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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